阅读说明：本技术 一种呼吸系统潮气量控制方法、装置及设备 (Tidal volume control method, device and equipment for respiratory system ) 是由 薛健 白晶 邢吉生 董胜 张玉欣 李鹏威 付伟 邹青宇 于 2021-09-17 设计创作，主要内容包括：本申请提供一种呼吸系统潮气量控制方法、装置及设备,该方法可以通过上一时刻模拟肺模块在本呼吸系统自身扰动下输出的肺内部气体体积输入到前馈控制器中得到肺内部压力,并将肺内部气体体积和期望肺模块输出的内部气体体积的差值输入至反滤滤波器得到压力误差；将肺内部压力、压力误差以及预先配置的当前时刻的白噪声信号分别输入至模拟肺模块中,输出当前时刻模拟肺模块的肺内部气体体积,以实现呼吸系统实时对潮气量的控制。应用本实施例提供的技术方案既能够保证本呼吸系统的跟随性,又能够消除本呼吸系统自身扰动和噪声干扰,进而进一步能够保证本呼吸系统的抗扰性,从而能够给提高本呼吸系统参数的鲁棒性。(The application provides a tidal volume control method, a tidal volume control device and tidal volume control equipment for a respiratory system, wherein the method can input the internal gas volume of a lung output by a simulated lung module under the self-disturbance of the respiratory system at the last moment into a feedforward controller to obtain the internal pressure of the lung, and input the difference value between the internal gas volume of the lung and the internal gas volume output by an expected lung module into a reverse filter to obtain a pressure error; and respectively inputting the lung internal pressure, the pressure error and a preconfigured white noise signal at the current moment into the lung simulating module, and outputting the lung internal gas volume of the lung simulating module at the current moment so as to realize the real-time control of the respiratory system on the tidal volume. By applying the technical scheme provided by the embodiment, the following performance of the respiratory system can be ensured, the self disturbance and noise interference of the respiratory system can be eliminated, and the disturbance resistance of the respiratory system can be further ensured, so that the robustness of the parameters of the respiratory system can be improved.)

1. A tidal volume control method of a respiratory system is characterized in that the tidal volume control method is applied to a controller of the respiratory system, the respiratory system further comprises a feedforward controller, a back filter, an expected lung module and a simulated lung module for simulating human lungs, the expected lung module is the simulated lung module under the condition that the respiratory system has no self-disturbance and noise interference, and the method comprises the following steps:

obtaining the volume of the gas inside the lung output by the lung simulation module under the self-disturbance of the respiratory system at the previous moment;

inputting the lung internal gas volume into the feedforward controller to obtain the lung internal pressure output by the feedforward controller at the current moment;

inputting the difference value between the internal gas volume of the lung and the internal gas volume output by the expected lung module corresponding to the simulated lung module into a reverse filtering filter to obtain a pressure error;

and respectively inputting the lung internal pressure, the pressure error and a preconfigured white noise signal at the current moment into the simulated lung module, so that the simulated lung module outputs the lung internal gas volume with noise and system disturbance eliminated at the current moment, and the control of the tidal volume of the respiratory system is realized.

2. The method of claim 1, wherein the desired lung module is determined using the steps of:

obtaining the volume of the gas inside the lung output by the lung simulation module under the self-disturbance of the respiratory system at the previous moment;

inputting the volume of the gas in the lung into a feedforward controller to obtain the pressure in the lung;

respectively inputting the lung internal pressure and a preset white noise signal at the current moment into a simulated lung module to obtain the volume of the gas inside the lung output by the simulated lung module at the current moment;

and establishing an adaptive filter for representing the mechanical characteristics of the gas operation in the lung at the current moment according to the pressure in the lung, the white noise signal and the gas volume in the lung output by the simulated lung module at the current moment, so that an error signal between the gas volume in the lung output by the adaptive filter and the gas volume in the lung output by the simulated lung module at the current moment is close to the system disturbance and the existing noise caused by the respiratory system at the current moment under the excitation of the white noise signal, and determining the adaptive filter as an expected lung module.

3. The method of claim 2, wherein the establishing an adaptive filter for characterizing the mechanical characteristics of the operation of the lung internal gas at the current time according to the lung internal pressure, the white noise signal and the lung internal gas volume output by the analog lung module at the current time comprises:

establishing an initial adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the output internal gas volume of the lung;

respectively inputting the lung internal pressure and a white noise signal at the current moment configured in advance into an initial adaptive filter to obtain a first lung internal gas volume at the current moment output by the initial adaptive filter;

inputting the lung internal pressure into an initial adaptive filter to obtain a second lung internal gas volume at the current moment output by the initial adaptive filter;

respectively calculating a noise error signal between the first lung internal gas volume and the lung internal gas volume output by the simulated lung module and a disturbance error signal between the second lung internal gas volume and the lung internal gas volume output by the simulated lung module according to the first lung internal gas volume and the second lung internal gas volume;

judging whether the difference between the sum of the noise error signal and the disturbance error signal and a system interference signal is in a preset range, wherein the system interference signal is a self disturbance signal of the respiratory system and a noise interference signal of the system;

if the current lung pressure is not within the preset range, feeding the sum of the noise error signal and the disturbance error signal back to an adaptive filter, using the sum of the noise error signal and the disturbance error signal and a white noise signal as the input of the initial adaptive filter, and returning to the step of obtaining the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

and if the initial adaptive filter is within the preset range, determining the established initial adaptive filter as the expected lung module.

4. A method according to claim 3, characterized in that the feedforward controller is built up by the steps of:

inputting the volume of the gas inside the lung output by the lung simulation module at the last moment into an initial feedforward controller to obtain the pressure inside the lung;

inputting the obtained lung internal pressure and a preconfigured white noise signal at the current moment into the simulated lung module to obtain a third lung internal gas volume output by the simulated lung module at the current moment;

inputting the lung internal pressure and a preconfigured white noise signal at the current moment into the expected lung module to obtain a fourth lung internal gas volume output by the expected lung module;

correcting the expected lung module by using the difference value of the third lung internal gas volume and the fourth lung internal gas volume, and inputting the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the current moment into the corrected expected lung module to obtain the fourth lung internal gas volume output by the corrected expected lung module;

determining a target value matched with the lung internal pressure at the current moment by using a pre-configured reference model, obtaining an inverse model enabling the fourth lung internal gas volume to be close to the target value according to the target value and the fourth lung internal gas volume, and determining the inverse model as a feedforward controller.

5. The method of claim 4, wherein the inverse filter is established by:

obtaining the volume of the gas in the third lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

respectively inputting the lung internal pressure and a white noise signal at the preset current moment into the expected lung module to obtain a fifth lung internal gas volume at the current moment output by the expected lung module;

inputting the lung interior pressure into the desired lung module, resulting in a sixth lung interior gas volume at the current time that is output by the desired lung module;

determining an inverse filter using a perturbation error between the third lung internal gas volume and the fifth lung internal gas volume, a noise error between the third lung internal gas volume and the sixth lung internal gas volume, and a frequency at a current time.

6. The utility model provides a respiratory tidal volume controlling means, its characterized in that is applied to respiratory's controller, respiratory still includes feedforward controller, anti-filter, expects lung module and simulation lung module, expect lung module for simulation lung module under this respiratory does not have self disturbance and noise interference condition the device includes:

the gas volume obtaining module is used for obtaining the internal gas volume of the lung output by the lung simulating module under the self-disturbance of the respiratory system at the previous moment;

the internal lung pressure obtaining module is used for inputting the internal lung gas volume into the feedforward controller to obtain the internal lung pressure output by the feedforward controller at the current moment;

the pressure error obtaining module is used for inputting the difference value between the internal gas volume of the lung and the internal gas volume output by the expected lung module corresponding to the simulated lung module into a reverse filtering filter to obtain a pressure error;

and the tidal volume control module is used for respectively inputting the lung internal pressure, the pressure error and a preconfigured white noise signal at the current moment into the simulated lung module so as to enable the simulated lung module to output the lung internal gas volume for eliminating noise and system disturbance at the current moment, thereby realizing the control of the tidal volume of the respiratory system.

7. The apparatus of claim 6, further comprising a desired lung module establishing module for establishing a desired lung module, the desired lung module establishing module comprising:

the first gas volume obtaining submodule is used for obtaining the internal gas volume of the lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

the internal lung pressure sub-obtaining module is used for inputting the internal lung gas volume into a feedforward controller to obtain the internal lung pressure;

the second gas volume obtaining submodule is used for respectively inputting the lung internal pressure and a preset white noise signal at the current moment into the lung simulating module to obtain the lung internal gas volume output by the lung simulating module at the current moment;

and the expected lung module determining submodule is used for establishing an adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the internal gas volume of the lung output by the simulated lung module at the current moment, so that an error signal between the internal gas volume of the lung output by the adaptive filter and the internal gas volume of the lung output by the simulated lung module at the current moment is close to the system disturbance and the existing noise caused by the respiratory system at the current moment under the excitation of the white noise signal, and determining the adaptive filter as the expected lung module.

8. The apparatus of claim 7, wherein the desired lung module determination submodule is specifically configured to:

establishing an initial adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the output internal gas volume of the lung;

respectively inputting the lung internal pressure and a white noise signal at the current moment configured in advance into an initial adaptive filter to obtain a first lung internal gas volume at the current moment output by the initial adaptive filter;

inputting the lung internal pressure into an initial adaptive filter to obtain a second lung internal gas volume at the current moment output by the initial adaptive filter;

respectively calculating a noise error signal between the first lung internal gas volume and the lung internal gas volume output by the simulated lung module and a disturbance error signal between the second lung internal gas volume and the lung internal gas volume output by the simulated lung module according to the first lung internal gas volume and the second lung internal gas volume;

judging whether the difference between the sum of the noise error signal and the disturbance error signal and a system interference signal is in a preset range, wherein the system interference signal is a self disturbance signal of the respiratory system and a noise interference signal of the system;

if the current lung pressure is not within the preset range, feeding the sum of the noise error signal and the disturbance error signal back to an adaptive filter, using the sum of the noise error signal and the disturbance error signal and a white noise signal as the input of the initial adaptive filter, and returning to the step of obtaining the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

and if the initial adaptive filter is within the preset range, determining the established initial adaptive filter as the expected lung module.

9. The apparatus of claim 8, further comprising a feedforward controller setup module to set up a feedforward controller, the feedforward controller setup module to:

inputting the volume of the gas inside the lung output by the lung simulation module at the last moment into an initial feedforward controller to obtain the pressure inside the lung;

inputting the obtained lung internal pressure and a preconfigured white noise signal at the current moment into the simulated lung module to obtain a third lung internal gas volume output by the simulated lung module at the current moment;

inputting the lung internal pressure and a preconfigured white noise signal at the current moment into the expected lung module to obtain a fourth lung internal gas volume output by the expected lung module;

correcting the expected lung module by using the difference value of the third lung internal gas volume and the fourth lung internal gas volume, and inputting the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the current moment into the corrected expected lung module to obtain the fourth lung internal gas volume output by the corrected expected lung module;

determining a target value matched with the lung internal pressure at the current moment by using a pre-configured reference model, obtaining an inverse model enabling the fourth lung internal gas volume to be close to the target value according to the target value and the fourth lung internal gas volume, and determining the inverse model as a feedforward controller.

10. An electronic device, comprising: a processor and a memory;

the memory for storing machine executable instructions;

the processor is used for reading and executing the machine executable instructions stored by the memory so as to realize the method of any one of claims 1 to 5.

Technical Field

The application relates to the technical field of biology, in particular to a tidal volume control method, a tidal volume control device and tidal volume control equipment of a respiratory system.

Background

The breathing rhythm given by the respiratory system is achieved during artificial respiration, the modern respiratory system can monitor most indexes of the respiratory system and perform related operations, and changes of various airway pressures, flow rates and volumes, such as inspiration end blocking and end blocking operations, pressure-time, flow rate-time and volume-time curves, a pressure-volume (P-V) ring, a flow rate-volume (F-V) ring and the like.

Disclosure of Invention

The application provides a tidal volume control method, a tidal volume control device and tidal volume control equipment of a respiratory system, so that robustness of the respiratory system is improved.

In a first aspect, an embodiment of the present application provides a tidal volume control method for a respiratory system, which is applied to a controller of the respiratory system, the respiratory system further includes a feedforward controller, a back-filtering filter, an expected lung module, and a simulated lung module for simulating a human lung, where the expected lung module is the simulated lung module under the condition that the respiratory system has no self-disturbance and no noise interference, and the method includes:

obtaining the volume of the gas inside the lung output by the lung simulation module under the self-disturbance of the respiratory system at the previous moment;

inputting the lung internal gas volume into the feedforward controller to obtain the lung internal pressure output by the feedforward controller at the current moment;

inputting the difference value between the internal gas volume of the lung and the internal gas volume output by the expected lung module corresponding to the simulated lung module into a reverse filtering filter to obtain a pressure error;

and respectively inputting the lung internal pressure, the pressure error and a preconfigured white noise signal at the current moment into the simulated lung module, so that the simulated lung module outputs the lung internal gas volume with noise and system disturbance eliminated at the current moment, and the control of the tidal volume of the respiratory system is realized.

In one embodiment of the present application, the desired lung module is determined using the following steps:

obtaining the volume of the gas inside the lung output by the lung simulation module under the self-disturbance of the respiratory system at the previous moment;

inputting the volume of the gas in the lung into a feedforward controller to obtain the pressure in the lung;

respectively inputting the lung internal pressure and a preset white noise signal at the current moment into a simulated lung module to obtain the volume of the gas inside the lung output by the simulated lung module at the current moment;

and establishing an adaptive filter for representing the mechanical characteristics of the gas operation in the lung at the current moment according to the pressure in the lung, the white noise signal and the gas volume in the lung output by the simulated lung module at the current moment, so that an error signal between the gas volume in the lung output by the adaptive filter and the gas volume in the lung output by the simulated lung module at the current moment is close to the system disturbance and the existing noise caused by the respiratory system at the current moment under the excitation of the white noise signal, and determining the adaptive filter as an expected lung module.

In an embodiment of the application, the establishing an adaptive filter for characterizing the mechanical characteristics of the operation of the lung internal gas at the current time according to the lung internal pressure, the white noise signal and the lung internal gas volume output by the analog lung module at the current time includes:

establishing an initial adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the output internal gas volume of the lung;

respectively inputting the lung internal pressure and a white noise signal at the current moment configured in advance into an initial adaptive filter to obtain a first lung internal gas volume at the current moment output by the initial adaptive filter;

inputting the lung internal pressure into an initial adaptive filter to obtain a second lung internal gas volume at the current moment output by the initial adaptive filter;

respectively calculating a noise error signal between the first lung internal gas volume and the lung internal gas volume output by the simulated lung module and a disturbance error signal between the second lung internal gas volume and the lung internal gas volume output by the simulated lung module according to the first lung internal gas volume and the second lung internal gas volume;

judging whether the difference between the sum of the noise error signal and the disturbance error signal and a system interference signal is in a preset range, wherein the system interference signal is a self disturbance signal of the respiratory system and a noise interference signal of the system;

if the current lung pressure is not within the preset range, feeding the sum of the noise error signal and the disturbance error signal back to an adaptive filter, using the sum of the noise error signal and the disturbance error signal and a white noise signal as the input of the initial adaptive filter, and returning to the step of obtaining the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

and if the initial adaptive filter is within the preset range, determining the established initial adaptive filter as the expected lung module.

In one embodiment of the present application, the feedforward controller is built by:

inputting the volume of the gas inside the lung output by the lung simulation module at the last moment into an initial feedforward controller to obtain the pressure inside the lung;

inputting the obtained lung internal pressure and a preconfigured white noise signal at the current moment into the simulated lung module to obtain a third lung internal gas volume output by the simulated lung module at the current moment;

inputting the lung internal pressure and a preconfigured white noise signal at the current moment into the expected lung module to obtain a fourth lung internal gas volume output by the expected lung module;

correcting the expected lung module by using the difference value of the third lung internal gas volume and the fourth lung internal gas volume, and inputting the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the current moment into the corrected expected lung module to obtain the fourth lung internal gas volume output by the corrected expected lung module;

determining a target value matched with the lung internal pressure at the current moment by using a pre-configured reference model, obtaining an inverse model enabling the fourth lung internal gas volume to be close to the target value according to the target value and the fourth lung internal gas volume, and determining the inverse model as a feedforward controller.

In one embodiment of the present application, the inverse filter is established by the following steps:

obtaining the volume of the gas in the third lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

respectively inputting the lung internal pressure and a white noise signal at the preset current moment into the expected lung module to obtain a fifth lung internal gas volume at the current moment output by the expected lung module;

inputting the lung interior pressure into the desired lung module, resulting in a sixth lung interior gas volume at the current time that is output by the desired lung module;

determining an inverse filter using a perturbation error between the third lung internal gas volume and the fifth lung internal gas volume, a noise error between the third lung internal gas volume and the sixth lung internal gas volume, and a frequency at a current time.

In a second aspect, the present application provides a respiratory system tidal volume control apparatus, which is applied to a controller of a respiratory system, the respiratory system further includes a feedforward controller, an inverse filter, an expected lung module, and a simulated lung module, the expected lung module is the simulated lung module under the condition that the respiratory system has no self-disturbance and noise interference, the apparatus includes:

the gas volume obtaining module is used for obtaining the internal gas volume of the lung output by the lung simulating module under the self-disturbance of the respiratory system at the previous moment;

the internal lung pressure obtaining module is used for inputting the internal lung gas volume into the feedforward controller to obtain the internal lung pressure output by the feedforward controller at the current moment;

the pressure error obtaining module is used for inputting the difference value between the internal gas volume of the lung and the internal gas volume output by the expected lung module corresponding to the simulated lung module into a reverse filtering filter to obtain a pressure error;

and the tidal volume control module is used for respectively inputting the lung internal pressure, the pressure error and a preconfigured white noise signal at the current moment into the simulated lung module so as to enable the simulated lung module to output the lung internal gas volume for eliminating noise and system disturbance at the current moment, thereby realizing the control of the tidal volume of the respiratory system.

In one embodiment of the application, the apparatus further comprises a desired lung module establishing module for establishing a desired lung module, the desired lung module establishing module comprising:

the first gas volume obtaining submodule is used for obtaining the internal gas volume of the lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

the internal lung pressure sub-obtaining module is used for inputting the internal lung gas volume into a feedforward controller to obtain the internal lung pressure;

the second gas volume obtaining submodule is used for respectively inputting the lung internal pressure and a preset white noise signal at the current moment into the lung simulating module to obtain the lung internal gas volume output by the lung simulating module at the current moment;

and the expected lung module determining submodule is used for establishing an adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the internal gas volume of the lung output by the simulated lung module at the current moment, so that an error signal between the internal gas volume of the lung output by the adaptive filter and the internal gas volume of the lung output by the simulated lung module at the current moment is close to the system disturbance and the existing noise caused by the respiratory system at the current moment under the excitation of the white noise signal, and determining the adaptive filter as the expected lung module.

In one embodiment of the application, the desired lung module determination submodule is specifically configured to:

establishing an initial adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the output internal gas volume of the lung;

respectively inputting the lung internal pressure and a white noise signal at the current moment configured in advance into an initial adaptive filter to obtain a first lung internal gas volume at the current moment output by the initial adaptive filter;

inputting the lung internal pressure into an initial adaptive filter to obtain a second lung internal gas volume at the current moment output by the initial adaptive filter;

respectively calculating a noise error signal between the first lung internal gas volume and the lung internal gas volume output by the simulated lung module and a disturbance error signal between the second lung internal gas volume and the lung internal gas volume output by the simulated lung module according to the first lung internal gas volume and the second lung internal gas volume;

judging whether the difference between the sum of the noise error signal and the disturbance error signal and a system interference signal is in a preset range, wherein the system interference signal is a self disturbance signal of the respiratory system and a noise interference signal of the system;

if the current lung pressure is not within the preset range, feeding the sum of the noise error signal and the disturbance error signal back to an adaptive filter, using the sum of the noise error signal and the disturbance error signal and a white noise signal as the input of the initial adaptive filter, and returning to the step of obtaining the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

and if the initial adaptive filter is within the preset range, determining the established initial adaptive filter as the expected lung module.

In an embodiment of the present application, the apparatus further includes a feedforward controller establishing module configured to establish a feedforward controller, where the feedforward controller establishing module is specifically configured to:

inputting the volume of the gas inside the lung output by the lung simulation module at the last moment into an initial feedforward controller to obtain the pressure inside the lung;

inputting the obtained lung internal pressure and a preconfigured white noise signal at the current moment into the simulated lung module to obtain a third lung internal gas volume output by the simulated lung module at the current moment;

inputting the lung internal pressure and a preconfigured white noise signal at the current moment into the expected lung module to obtain a fourth lung internal gas volume output by the expected lung module;

correcting the expected lung module by using the difference value of the third lung internal gas volume and the fourth lung internal gas volume, and inputting the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the current moment into the corrected expected lung module to obtain the fourth lung internal gas volume output by the corrected expected lung module;

determining a target value matched with the lung internal pressure at the current moment by using a pre-configured reference model, obtaining an inverse model enabling the fourth lung internal gas volume to be close to the target value according to the target value and the fourth lung internal gas volume, and determining the inverse model as a feedforward controller.

In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory;

the memory for storing machine executable instructions;

the processor is configured to read and execute the machine executable instructions stored in the memory to implement the method steps of the tidal volume control method of the respiratory system according to the above embodiments.

According to the technical scheme, the internal lung gas volume output by the lung simulation module under the self-disturbance of the respiratory system at the previous moment is input into the feedforward controller to obtain the internal lung pressure, and the difference value between the internal lung gas volume and the internal gas volume output by the expected lung module corresponding to the lung simulation module is input into the inverse filter to obtain the pressure error; finally, the internal pressure of the lung, the pressure error and the white noise signal of the preset current moment are respectively input into the lung simulating module, and the internal gas volume of the lung simulating module at the current moment is output to realize the real-time control of the respiratory system on the tidal volume.

Drawings

Fig. 1 is a schematic flow chart of a tidal volume control method of a respiratory system according to an embodiment of the present application;

FIG. 2 is a schematic diagram of adaptive filter modeling of an additive white noise signal provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of online modeling in the presence of a perturbation in a simulated lung module provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of an adaptive filter modeling with a disturbance cancellation loop provided by an embodiment of the present application;

FIG. 5 is a schematic diagram illustrating an implementation of adaptive inverse control to achieve tidal volume automatic control according to an embodiment of the present application;

fig. 6 is a schematic hardware configuration diagram of a respiratory system tidal volume control apparatus according to an embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions in the embodiments of the present invention better understood and make the above objects, features, and advantages of the embodiments of the present invention more comprehensible, it is obvious that the technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, fig. 1 is a schematic flowchart of a tidal volume control method of a respiratory system according to an embodiment of the present application, where the method may be applied to a controller of the respiratory system, the respiratory system further includes a feedforward controller, a back-filtering filter, an expected lung module, and a simulated lung module for simulating human lungs, and the expected lung module is the simulated lung module in a situation where the respiratory system has no self-disturbance and no noise interference.

As shown in fig. 1, the process may include the following steps:

and step 110, obtaining the volume of the gas inside the lung output by the simulated lung module at the previous moment under the self-disturbance of the respiratory system.

In practical application, each respiratory system has a self-disturbance phenomenon, and the step acquires the internal gas volume of the lung at the last moment obtained by simulating the lung module under the self-disturbance of the respiratory system.

As an example, the patient's P-V curve is described using a clinical low flow method or an end-of-inspiration blocking method, wherein the simulated lung module operates according to a P-V curve that conforms to mechanical features that characterize the user's static characteristics. In the present embodiment, a simulated lung model fitted to a clinical P-V curve is used as the controlled object.

And 102, inputting the internal gas volume of the lung into the feedforward controller to obtain the internal pressure of the lung output by the feedforward controller at the current moment.

The feed forward controller inputs the lung internal gas volume and outputs the lung internal pressure. The feedforward controller will not be described in detail herein, and the establishment of the feedforward controller will be described in detail later.

And 103, inputting the difference value between the internal gas volume of the lung and the internal gas volume output by the expected lung module corresponding to the simulated lung module into a reverse filtering filter to obtain a pressure error.

It is expected that the lung module may be understood as a simulated lung module that operates in accordance with the P-V curve of the patient without the present respiratory system's own perturbations and noise disturbances.

The volume of the gas inside the lung in the step is the volume of the gas inside the lung output by the simulated lung module under the self-disturbance and the system noise interference of the respiratory system. Based on this, the self-disturbance and noise interference of the respiratory system can be removed in two parts, firstly, as shown in FIG. 2, the adaptive filter G_m(z) is the established object model, the replica filter G_m(z) and G_m(z) exactly the same, copy G_mThe input (z) and the object input are both u (k), u (k) is the superposition value of the white noise signal delta (k) and the lung internal pressure output by the feedforward controller, and k is a signal serial number. Subject (simulated lung module) G_p(z) subtracting the adaptive filter G from the internal pulmonary pressure output by the respiratory system under its own perturbation_m(z) output lung internal pressure, i.e. for G with a signal providing a desired response_m(z) adaptation. As can be seen from fig. 1, the error signal e (k) ═ uG_p(z)+n-uG_m(z) u is a controlled variable, when G_m(z) convergence to approximately G_p(z) when matching, the error e (k) of the adaptive process is almost completely equal to the unique object output disturbance n, which is the minimum error that can be achieved by modeling the object under the condition of full excitation with white noise, and the self-disturbance of the respiratory system is removed firstly.

As an example, the desired lung module may be determined by the following steps a to D:

and step A, obtaining the volume of the gas inside the lung output by the simulated lung module at the previous moment under the self-disturbance of the respiratory system.

And B, inputting the volume of the gas in the lung into a feedforward controller to obtain the pressure in the lung.

The volume of the gas inside the lung is the volume of the gas inside the lung which is output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment.

And step C, respectively inputting the lung internal pressure and a preset white noise signal at the current moment into a simulated lung module to obtain the lung internal gas volume output by the simulated lung module at the current moment.

And D, establishing an adaptive filter for representing the mechanical operation characteristics of the gas in the lung at the current moment according to the pressure in the lung, the white noise signal and the gas volume in the lung output by the simulated lung module at the current moment, so that an error signal between the gas volume in the lung output by the adaptive filter and the gas volume in the lung output by the simulated lung module at the current moment is close to the system disturbance and the existing noise caused by the respiratory system at the current moment under the excitation of the white noise signal, and determining the adaptive filter as the expected lung module.

As an embodiment, one way to implement step D may be to implement step D1 to step D7:

and D1, establishing an initial adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the output internal gas volume of the lung.

And D2, respectively inputting the lung internal pressure and a white noise signal configured in advance at the current moment into an initial adaptive filter to obtain a first lung internal gas volume at the current moment output by the initial adaptive filter.

Step D3, inputting the lung internal pressure into the initial adaptive filter, and obtaining a second lung internal gas volume at the current time outputted by the initial adaptive filter.

Step D4, calculating a noise error signal between the first lung internal gas volume and the lung internal gas volume output by the simulated lung module, and a disturbance error signal between the second lung internal gas volume and the lung internal gas volume output by the simulated lung module, respectively, according to the first lung internal gas volume and the second lung internal gas volume.

The first lung interior gas volume is a name given for convenience of distinction from the lung interior gas volume hereinafter, and is not intended to limit a certain lung interior gas volume.

Here, the second lung interior gas volume is only named for convenience of description and is not used to limit a certain lung interior gas volume.

Step D5, judging whether the difference between the sum of the noise error signal and the disturbance error signal and a system interference signal is in a preset range, wherein the system interference signal is the self disturbance signal of the respiratory system and the noise interference signal of the system; if not, go to step D6, and if it is, go to step D7.

And D6, feeding back the sum of the noise error signal and the disturbance error signal to an adaptive filter, using the sum of the noise error signal and the disturbance error signal and a white noise signal as the input of the initial adaptive filter, and returning to execute the step A.

Step D7, the established initial adaptive filter will be determined as the desired lung module.

Therefore, in the technical scheme provided by the embodiment of the application, the determined expected lung module is an adaptive filter for eliminating self-disturbance and noise interference of the respiratory system, and reference can be made for eliminating disturbance and noise interference caused by the respiratory system in real time subsequently.

As shown in fig. 3, in the adaptive inverse control system, the inverse of the adaptive object is used as a feedforward controller in the control structure. G is to be_p(z) simulation of the lung Module as the controlled object, the inverse of the ideal objectIs G_c0(z) and the inverse obtained using some adaptive or modeling method is denoted as G_c(z). However, in an actual respiratory system, a disturbance always exists in a subject, and if modeling is performed without disturbance, only one off-set solution can be obtained in the case of actual disturbance, and a correct inverse cannot be obtained. For this purpose, the input signals of the inverse model are processed during the inverse modeling of the actual breathing system. G, even in the presence of noise, due to object modeling_m(z) none of the resulting solutions deviate from the optimal solution. Therefore, can utilize G_m(z) obtaining an inverse of the model, and using an output signal of the target model as an input signal of the inverse model. In this embodiment, the inverse of the adaptive object (the simulated lung module) is used as the feedforward controller in the control structure.

As an embodiment, the implementation of the feedforward controller may include the following steps E to I:

and E, inputting the volume of the gas inside the lung output by the lung simulation module at the last moment into an initial feedforward controller to obtain the pressure inside the lung.

In this step, the initial feedforward controller may be established based on a variable step LMS adaptive filtering algorithm of a variable discourse domain, specifically:

e(k)＝d(k)-X^T(k)W(k)

W(k+1)＝W(k)+2μ(k)e(k)X(k)

0＜μ＜1/λ_max；

wherein W (k) is a weight vector of the adaptive filter at the current time k, x (k) is an input signal vector at the current time k, d (k) is an expected output value, e (k) is an error signal, T is a transposition, W (k +1) is a weight vector of the adaptive filter at the next time k +1, and the convergence condition of the LMS algorithm is as follows: mu is more than 0 and less than 1/lambda_max，λ_maxIs the largest eigenvalue of the autocorrelation matrix of the input signal. [ -U, U [ -U ]]For the universe of discourse for the output variable μ (k), U is the maximum tidal volume value, e.g., U canTaking any value of 8-12 ml/kg, { A_j}_(1≤j≤m)For fuzzy partition on input variable e (k) domain, α (x) is scale factor, α (x) is 1-a. exp (-kx)²)，a∈(0,1),k>0，K_IIs a proportionality constant which can be considered as a design parameter, P_n＝(p₁,p₂,…,p_n)^TTo make the error vector a scalar constant vector, p₁Is a constant vector with sequence number 1, p₂Is a constant vector with sequence number 2, p_nIn the constant vector corresponding to the sequence number n, β (0) is an initial value and can be determined as a design parameter according to the actual situation, and β (0) is usually assumed to be 1.

And F, inputting the obtained lung internal pressure and a preset white noise signal at the current moment into the simulated lung module to obtain a third lung internal gas volume output by the simulated lung module at the current moment.

The third lung interior gas volume is a designation for convenience of distinction from the lung interior gas volumes hereinafter, and is not intended to limit a certain lung interior gas volume.

And G, inputting the lung internal pressure and a preset white noise signal at the current moment into the expected lung module to obtain a fourth lung internal gas volume output by the expected lung module.

Here, the fourth lung interior gas volume is a name for convenience of description only, and is not intended to limit a certain lung interior gas volume.

And H, correcting the expected lung module by using the difference value of the third lung internal gas volume and the fourth lung internal gas volume, and inputting the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the current moment into the corrected expected lung module to obtain the fourth lung internal gas volume output by the expected lung module after correction.

The difference between the third lung interior gas volume and the fourth lung interior gas volume is the perturbation error.

Step I, a target value matched with the lung internal pressure at the current moment is determined by utilizing a pre-configured reference model, an inverse model enabling the fourth lung internal gas volume to be close to the target value is obtained according to the target value and the fourth lung internal gas volume, and the inverse model is determined to be a feedforward controller.

The reference model in this step may be a preset linear model or a number, and what kind of model is selected for the reference model is related to actual experience. The reference model is shown as M (z) in FIG. 2.

The above inverse model may be understood as the inverse model of the desired lung module, i.e. the inverse model of the adaptive filter.

In the embodiment of the application, the target value can be set to be 1 according to the reference model configured in advance, and the feedforward controller is established by white noise and a lung simulation module.

As shown in FIG. 4, the adaptive inverse control object perturbation adopts a perturbation elimination technique, the object input drives both the object and its model (which is free of noise and perturbation), the difference between the object output and the object model output is the noise and perturbation of the object, the noise and perturbation is used to drive the inverse of the model and subtracted from the object input, and the final effect is to eliminate the object noise and perturbation from the object output under ideal positive and inverse model conditions, i.e., under ideal positive and inverse model conditionsWhen the transfer function from the disturbance to the output is 0, the disturbance is not suppressed but eliminated, and here, the meaning of the value of s may be different according to the transformation, specifically, when s is obtained by laplace transformation, s is frequency, which may be equivalent to j ω, ω is angular velocity, and j is an imaginary part. Since the laplace transform can be regarded as a general form of fourier transform, s ═ j ω can be substituted to analyze characteristics on a signal spectrum. In addition, considering the form of s δ + j ω, the real part δ, imaginary part δ, mode length, phase angle, etc. of s can be correlated with system performance due to the nature of the lagrange transformation. For example, in a transfer function concerning s discussed in theory such as automatic control, the pole s of the function can be found to be p_i(i ═ 1, 2.., n), which is changed from the Ralski (anti) state after molecular resolutionThe conversion property can be deduced to obtain the function pole s ═ p_iWhether it lies in the left half plane of the s-plane determines the stability of the system.

As an embodiment, the anti-filtering filter is established by adopting the following steps J to M:

and step J, obtaining the volume of the gas in the third lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment.

The third lung interior gas volume of this step is determined in the presence of disturbances in the respiratory system itself and in the presence of noise disturbances.

And K, respectively inputting the lung internal pressure and a preset white noise signal at the current moment into the expected lung module to obtain a fifth lung internal gas volume at the current moment output by the expected lung module.

Here, the fifth lung interior gas volume is only named for convenience of description and is not intended to limit a certain lung interior gas volume.

The fifth lung internal gas volume of this step is determined in the presence of noise in the present respiratory system.

And L, inputting the lung internal pressure into the expected lung module to obtain a sixth lung internal gas volume output by the expected lung module at the current moment.

Here, the sixth lung interior gas volume is a name for convenience of description only, and is not intended to limit a certain lung interior gas volume.

The sixth lung internal gas volume of this step is determined in case of a perturbation of the present respiratory system itself.

And step M, determining an inverse filter by using a disturbance error between the third lung internal gas volume and the fifth lung internal gas volume, a noise error between the third lung internal gas volume and the sixth lung internal gas volume and the frequency at the current moment.

In this step, based on the analysis of the third lung internal gas volume, the fifth lung internal gas volume, and the sixth lung internal gas volume, a disturbance error between the third lung internal gas volume and the fifth lung internal gas volume is a difference between the third lung internal gas volume and the fifth lung internal gas volume, and a noise error between the third lung internal gas volume and the sixth lung internal gas volume is a difference between the third lung internal gas volume and the sixth lung internal gas volume.

It can be seen that, in the technical solution provided in the embodiment of the present application, the lung internal pressure corresponding to the disturbance error and the noise error may be determined by using an inverse filter, so as to subtract the lung internal pressure corresponding to the disturbance error and the noise error when the input quantity of the object (the simulated lung module) is input, so as to eliminate the object noise and the disturbance in the object output, and under the conditions of an ideal positive model and an ideal inverse model, the transfer function from the disturbance to the output is 0, thereby achieving the purpose of eliminating the disturbance and the noise for the respiratory system.

Based on the analysis, the pressure error is the internal lung pressure corresponding to the disturbance error and the noise error.

And 104, respectively inputting the lung internal pressure, the pressure error and a preset white noise signal at the current moment into the simulated lung module, so that the simulated lung module outputs the lung internal gas volume with noise and system disturbance eliminated at the current moment, and the control of the tidal volume of the respiratory system is realized.

The method and the device have the advantages that by means of the positive correlation of the tidal volume and the gas volume inside the lung, the control on the gas volume inside the lung is converted into the control on the tidal volume by utilizing the correlation.

In this step, as an embodiment, the pressure error (the lung internal pressure corresponding to the disturbance error and the noise error) is subtracted from the superimposed value of the lung internal pressure and the white noise signal, so that the input quantity input into the simulated lung module has no disturbance error caused by the disturbance of the respiratory system, and the noise error caused by the noise interference, that is, the disturbance and the noise interference caused by the respiratory system are eliminated from the input quantity of the simulated lung module. Under such prerequisite, the inside gaseous volume of lung that the simulation lung module output more closely accords with the inside gaseous of lung of ideal that the patient breathed for the breathing of patient is more smooth and comfortable.

In this embodiment, the self-interference of the system may be interference of the respiratory system, such as random uncertainties of various parameters, such as lung elasticity and damping, and sensor noise.

As shown in FIG. 5, an on-line pair feedforward controller G is used_c(z) inverse wave filter G_q(z) modeling. Due to the feedforward controller G_c(z) inverse filter G_q(z) is different in that the former is used to follow the set point and the latter is used to cancel the interference, so the modeling signal is also different for G_c(z), ideally, G_cThe output of (z) should be the input signal of the analog lung module, so for G_c(z) taking the object input signal as the modeling signal, i.e. extracting G from point G_c(z) the modeled signal; for G_q(z), ideally, should be able to cancel load disturbances (self-disturbances of the respiratory system and noise disturbances), i.e. to ensure that the error signal (n) at point E passes through z^-1、G_q(z)、G_p(z) to cancel n and noise interference, for which purpose G is paired_q(z) the modeled signal takes the position E of the signal point, i.e. G is drawn from point E_q(z) modeling signal. In FIG. 5, the upper part of FIG. 5 is to obtain a model G of the object_m(z), the lower left half of FIG. 5 is to obtain the feedforward controller G_c(z) model, the right half of FIG. 5 below is the inverse filter G_q(z) model. The input signal is the last time lung internal gas volume, the control signal is the lung internal pressure, and the output signal is the current time lung internal gas volume.

In the embodiment, the human respiratory system is used as a controlled object, and the tidal volume of human respiration is consistent with the set value of the artificial respirator through the self-adaptive inverse control strategy. The adaptive inverse control system adopts the idea of adaptive and inverse control for following the set value, when the transfer function of the controller is the inverse of the transfer function of the object, the cascade transfer function of the controller and the object is 1, so that the output of the system follows the set input; because the respiratory system has the random uncertainty of various parameters such as the elasticity and the damping of the lung and the interference such as the noise of a sensor, the adaptive inverse control adopts a disturbance elimination technology to the disturbance of an object, the object input drives the object and also drives a model (which has no noise and disturbance), the difference between the output of the object and the output of the object model is the noise and the disturbance of the object, the noise and the disturbance are used to drive the inverse of the model and are subtracted from the object input, the final effect is not to inhibit the disturbance, the noise and the disturbance of the object are eliminated from the output of the object, and the control performance of the artificial respirator is improved. The feedforward controller realizes the following of the given value; the anti-filtering filter realizes the elimination of the disturbance.

In the embodiment of the application, the respiratory system is used as a controlled object, and the tidal volume of human respiration is consistent with the set value of the artificial respirator through the self-adaptive inverse control strategy. The adaptive inverse control system adopts the idea of adaptive and inverse control for following the set value, when the transfer function of the controller is the inverse of the transfer function of the object, the cascade transfer function of the controller and the object is 1, so that the output of the system follows the set input; because the respiratory system has the random uncertainties of various parameters such as the elasticity and the damping of the lung and the interference such as the noise of a sensor, the adaptive inverse control adopts a disturbance elimination technology to the disturbance of an object, the object input drives the object and also drives a model (which has no noise and disturbance), the difference between the output of the object and the output of the object model is the noise and the disturbance of the object, the noise and the disturbance are used to drive the inverse of the model and are subtracted from the object input, the final effect is not to inhibit the disturbance, the noise and the disturbance of the object are eliminated from the output of the object, and the control performance of the artificial respirator is improved. The feedforward controller realizes the following of the given value; the anti-filtering filter realizes the elimination of the disturbance.

The control of tidal volume can be realized by using an adaptive inverse control strategy on the basis of the feedforward controller, the inverse filter and the expected lung module. In the embodiment, the tidal volume of human breathing is consistent with the set value of the artificial respirator by taking the breathing system as a controlled object and adopting an adaptive inverse control strategy. The adaptive inverse control system adopts the idea of adaptive and inverse control for following the set value, and when the transfer function of the controller is the inverse of the transfer function of the object, the cascade transfer function of the controller and the object is 1, so that the system output follows the set input. Because the respiratory system has random uncertainties of various parameters such as lung elasticity and damping, and interference such as sensor noise (noise of the respiratory system), the adaptive inverse control adopts a disturbance elimination technology for object disturbance, the object input drives the object and also drives a model (which has no noise and disturbance), the difference between the object output and the object model output is the noise and the disturbance of the object, the noise and the disturbance are used for eliminating the inverse of the driving model and are subtracted from the object input, the final effect is not to inhibit the disturbance, the object noise and the disturbance are eliminated from the object output, and the control performance of the artificial respirator is improved. The feedforward controller realizes the following of the given value; the anti-filtering filter realizes the elimination of the disturbance. Because the respiratory system has random uncertainties of various parameters such as lung elasticity and damping, and interferences such as sensor noise, the adaptive inverse control adopts a disturbance elimination technology for object disturbance, the object input drives an object and also drives an expected lung model (which has no noise and disturbance), the difference between the object output and the expected lung model output is the noise and the disturbance of the object, the noise and the disturbance are used for eliminating the inverse of the driving model and are subtracted from the object input, the final effect is not to inhibit the disturbance, the object noise and the disturbance are eliminated from the object output, and the control performance of the artificial respirator is improved. The feedforward controller realizes the following of the given value; the anti-filtering filter realizes the elimination of the disturbance.

The description of the embodiment shown in fig. 1 is thus completed.

Therefore, according to the technical scheme described in the flowchart shown in the figure, in the embodiment of the present application, the internal lung gas volume output by the simulated lung module under the self-disturbance of the respiratory system at the previous time is input into the feedforward controller to obtain the internal lung pressure, and the difference value between the internal lung gas volume and the internal gas volume output by the expected lung module corresponding to the simulated lung module is input into the inverse filter to obtain the pressure error; finally, the internal pressure of the lung, the pressure error and the white noise signal of the preset current moment are respectively input into the lung simulating module, and the internal gas volume of the lung simulating module at the current moment is output to realize the real-time control of the respiratory system on the tidal volume.

To this end, the description of the method provided by the present application is completed, and the following describes the apparatus provided by the present application:

referring to fig. 6, fig. 6 is a schematic structural diagram of a tidal volume control apparatus of a respiratory system according to an embodiment of the present application, which is applied to a controller of the respiratory system, the respiratory system further includes a feedforward controller, an inverse filter, a desired lung module, and a simulated lung module, where the desired lung module is the simulated lung module in the absence of self-disturbance and noise interference in the respiratory system, and the apparatus includes:

the gas volume obtaining module 601 is used for obtaining the internal gas volume of the lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

a lung internal pressure obtaining module 602, configured to input the lung internal gas volume into the feed-forward controller, and obtain a lung internal pressure output by the feed-forward controller at a current time;

a pressure error obtaining module 603, configured to input a difference between the internal gas volume of the lung and an internal gas volume output by the simulated lung module corresponding to the expected lung module to a back filter to obtain a pressure error;

and a tidal volume control module 604, configured to input the lung internal pressure, the pressure error, and a preconfigured white noise signal at the current time into the simulated lung module, respectively, so that the simulated lung module outputs a lung internal gas volume at the current time, where noise and system disturbance are eliminated, to implement control of tidal volume of the respiratory system.

In one embodiment of the application, the apparatus further comprises a desired lung module establishing module for establishing a desired lung module, the desired lung module establishing module comprising:

the first gas volume obtaining submodule is used for obtaining the internal gas volume of the lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

the internal lung pressure sub-obtaining module is used for inputting the internal lung gas volume into a feedforward controller to obtain the internal lung pressure;

the second gas volume obtaining submodule is used for respectively inputting the lung internal pressure and a preset white noise signal at the current moment into the lung simulating module to obtain the lung internal gas volume output by the lung simulating module at the current moment;

and the expected lung module determining submodule is used for establishing an adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the internal gas volume of the lung output by the simulated lung module at the current moment, so that an error signal between the internal gas volume of the lung output by the adaptive filter and the internal gas volume of the lung output by the simulated lung module at the current moment is close to the system disturbance and the existing noise caused by the respiratory system at the current moment under the excitation of the white noise signal, and determining the adaptive filter as the expected lung module.

In one embodiment of the application, the desired lung module determination submodule is specifically configured to:

establishing an initial adaptive filter for representing the mechanical characteristics of the internal gas operation of the lung at the current moment according to the internal pressure of the lung, the white noise signal and the output internal gas volume of the lung;

respectively inputting the lung internal pressure and a white noise signal at the current moment configured in advance into an initial adaptive filter to obtain a first lung internal gas volume at the current moment output by the initial adaptive filter;

inputting the lung internal pressure into an initial adaptive filter to obtain a second lung internal gas volume at the current moment output by the initial adaptive filter;

respectively calculating a noise error signal between the first lung internal gas volume and the lung internal gas volume output by the simulated lung module and a disturbance error signal between the second lung internal gas volume and the lung internal gas volume output by the simulated lung module according to the first lung internal gas volume and the second lung internal gas volume;

judging whether the difference between the sum of the noise error signal and the disturbance error signal and a system interference signal is in a preset range, wherein the system interference signal is a self disturbance signal of the respiratory system and a noise interference signal of the system;

if the current lung pressure is not within the preset range, feeding the sum of the noise error signal and the disturbance error signal back to an adaptive filter, using the sum of the noise error signal and the disturbance error signal and a white noise signal as the input of the initial adaptive filter, and returning to the step of obtaining the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

and if the initial adaptive filter is within the preset range, determining the established initial adaptive filter as the expected lung module.

In an embodiment of the present application, the apparatus further includes a feedforward controller establishing module configured to establish a feedforward controller, where the feedforward controller establishing module is specifically configured to:

inputting the volume of the gas inside the lung output by the lung simulation module at the last moment into an initial feedforward controller to obtain the pressure inside the lung;

inputting the obtained lung internal pressure and a preconfigured white noise signal at the current moment into the simulated lung module to obtain a third lung internal gas volume output by the simulated lung module at the current moment;

inputting the lung internal pressure and a preconfigured white noise signal at the current moment into the expected lung module to obtain a fourth lung internal gas volume output by the expected lung module;

correcting the expected lung module by using the difference value of the third lung internal gas volume and the fourth lung internal gas volume, and inputting the lung internal pressure output by the simulated lung module under the self-disturbance of the respiratory system at the current moment into the corrected expected lung module to obtain the fourth lung internal gas volume output by the corrected expected lung module;

determining a target value matched with the lung internal pressure at the current moment by using a pre-configured reference model, obtaining an inverse model enabling the fourth lung internal gas volume to be close to the target value according to the target value and the fourth lung internal gas volume, and determining the inverse model as a feedforward controller.

In an embodiment of the present application, the apparatus further includes an inverse filter establishing module configured to establish an inverse filter, where the inverse filter establishing module is specifically configured to:

obtaining the volume of the gas in the third lung output by the simulated lung module under the self-disturbance of the respiratory system at the previous moment;

respectively inputting the lung internal pressure and a white noise signal at the preset current moment into the expected lung module to obtain a fifth lung internal gas volume at the current moment output by the expected lung module;

inputting the lung interior pressure into the desired lung module, resulting in a sixth lung interior gas volume at the current time that is output by the desired lung module;

determining an inverse filter using a perturbation error between the third lung internal gas volume and the fifth lung internal gas volume, a noise error between the third lung internal gas volume and the sixth lung internal gas volume, and a frequency at a current time.

The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.

In the electronic device provided in the embodiment of the present application, from a hardware level, a schematic diagram of a hardware architecture can be seen in fig. 7. The method comprises the following steps: a machine-readable storage medium and a processor, wherein: the machine-readable storage medium stores machine-executable instructions executable by the processor; the processor is configured to execute machine executable instructions to implement the respiratory system tidal volume control operations disclosed in the above examples.

A machine-readable storage medium is provided by embodiments of the present application that stores machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement the respiratory system tidal volume control operations disclosed in the examples above.

Here, a machine-readable storage medium may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and so forth. For example, the machine-readable storage medium may be: a RAM (random Access Memory), a volatile Memory, a non-volatile Memory, a flash Memory, a storage drive (e.g., a hard drive), a solid state drive, any type of storage disk (e.g., an optical disk, a dvd, etc.), or similar storage medium, or a combination thereof.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Furthermore, these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.