阅读说明：本技术 一种永磁无刷直流电机转速波动抑制方法 (Method for inhibiting rotation speed fluctuation of permanent magnet brushless direct current motor ) 是由 冒建亮 白国超 张传林 于 2021-07-13 设计创作，主要内容包括：本发明涉及一种永磁无刷直流电机转速波动抑制方法,所述方法通过采集永磁无刷直流电机速度反馈信号以及d-q轴电流反馈信号,构造非线性速度比例积分器、速度变化估计器、非线性多源干扰估计器、非线性电流比例积分器、电流变化估计器和动态补偿器,实现了对永磁无刷直流电机转速波动抑制控制。利用速度反馈信号和q轴电流反馈信号,对伺服系统中的转矩脉动、负载干扰、信号测量误差、模型参数不确定性等时变干扰因素进行在线精确估计；结合前馈和反馈相综合的非线性复合控制器策略,实现转速跟随的有限时间稳定控制。与现有技术相比,本发明对无刷直流电机的转速波动具有很好的抑制作用,具有响应快、精度高、抗干扰性强等优点。(The invention relates to a method for suppressing the rotation speed fluctuation of a permanent magnet brushless direct current motor, which realizes the suppression control of the rotation speed fluctuation of the permanent magnet brushless direct current motor by acquiring a speed feedback signal and a d-q axis current feedback signal of the permanent magnet brushless direct current motor and constructing a nonlinear speed proportional integrator, a speed change estimator, a nonlinear multisource interference estimator, a nonlinear current proportional integrator, a current change estimator and a dynamic compensator. The method comprises the following steps of performing online accurate estimation on time-varying interference factors such as torque ripple, load interference, signal measurement errors, model parameter uncertainty and the like in a servo system by using a speed feedback signal and a q-axis current feedback signal; and the nonlinear composite controller strategy which combines feedforward and feedback is combined to realize the finite time stable control of the following of the rotating speed. Compared with the prior art, the invention has good inhibition effect on the rotation speed fluctuation of the brushless direct current motor, and has the advantages of fast response, high precision, strong anti-interference performance and the like.)

1. A method for suppressing the rotation speed fluctuation of a permanent magnet brushless direct current motor is characterized by comprising the following steps:

acquiring a rotor position theta of a permanent magnet brushless direct current motor, and calculating to obtain a speed feedback signal omega; simultaneously collecting A phase current i of permanent magnet brushless direct current motor winding_aAnd phase B current i_bPerforming coordinate transformation to obtain d-axis current feedback signal i_dAnd q-axis current feedback signal i_q；

Step two, setting a signal omega according to the speed of the permanent magnet brushless direct current motor_rAnd the speed feedback signal omega to obtain a speed deviation signal e_ω＝ω_rOmega, constructing a nonlinear speed proportional integrator to obtain a speed deviation feedback control quantity u_ωn；

Step three, setting a signal omega according to the speed_rConstructing a speed change estimator to obtain a speed change feedforward control quantity u_ωf；

Step four, according to the speedFeedback signal omega and q-axis current feedback signal i_qConstructing a nonlinear multi-source interference estimator to obtain an interference compensation feedforward control quantity u_ωd；

Step five, feeding back the control quantity u according to the speed deviation obtained in the step two to the step four_ωnSpeed change feedforward control quantity u_ωfAnd disturbance compensation feedforward control quantity u_ωdTo obtain a q-axis current given signal i_qr＝u_ωn+u_ωf+u_ωd；

Step six, according to the q-axis current given signal i obtained in the step five_qrAnd q-axis current feedback signal i_qTo obtain a q-axis current deviation signal e_iq＝i_qr-i_qSetting signal i according to d-axis current_dr0 and d-axis current feedback signal i_dObtaining d-axis current deviation signal e_iq＝i_qr-i_qConstructing a nonlinear current proportional integrator to obtain a current deviation feedback control matrix

Step seven, a q-axis current given signal i is obtained according to the step five_qrConstructing a current change estimator to obtain a feedforward control quantity u of the q-axis current change_iqf；

Step eight, according to the speed feedback signal omega and the q axis current feedback signal i_qAnd d-axis current feedback signal i_dConstructing a dynamic compensator to obtain a dynamic compensation control matrix

Step nine, according to the current deviation feedback control matrix obtained in the step six to the step eightFeed-forward control quantity u of q-axis current change_iqfAnd a dynamic compensation control matrixObtaining a voltage given signal matrix

Step ten, giving a q-axis voltage to a signal u_qrAnd d-axis voltage given signal u_drAnd sequentially inputting the signals to the inverse transformation module and the space voltage vector PWM module to obtain a PWM driving signal.

2. The method for suppressing the rotation speed fluctuation of the permanent magnet brushless direct current motor according to claim 1, wherein coordinate transformation in the first step is Clarke transformation and Park transformation; the inverse transform in the step ten is inverse Park transform; and the PWM driving signal in the step ten is a three-phase inverter bridge 6-path PWM driving signal.

3. The method for suppressing rotation speed fluctuation of a permanent magnet brushless direct current motor according to claim 1, wherein the non-linear speed proportional integrator in the second step is specifically:

wherein k is_pω1Denotes the first proportional gain, k, of the velocity_pω2Representing a second proportional gain, k, of speed_iωRepresenting the velocity integral gain, sign (-) representing a sign function, u_ωnThe speed deviation feedback control amount is indicated.

4. The method for suppressing the rotation speed fluctuation of the permanent magnet brushless direct current motor according to claim 1, wherein the speed change estimator in the third step is specifically:

wherein the content of the first and second substances,representing a speed-setting signal omega_rIs determined by the estimated value of (c),indicating rate of change of speed given signalEstimate of (c), xi₁And xi₂Representing an estimator parameter;

the speed change feedforward control quantity in the third step is specifically as follows:wherein, J_mRepresenting the moment of inertia of the motor, K_eRepresenting the electromagnetic torque coefficient, L, of the machine_dRepresenting d-axis inductance, L_qRepresenting the q-axis inductance, n_pDenotes the number of pole pairs, phi_vRepresenting the rotor flux linkage; the electromagnetic torque coefficient is as follows:

5. the method according to claim 1, wherein the nonlinear multi-source interference estimator in step four is specifically:

wherein, J_mRepresenting the moment of inertia of the motor, K_eRepresenting the electromagnetic torque coefficient of the electrical machine,representing an estimate of the velocity feedback signal omega,representing multi-source disturbances d in servo systems_ωEstimate of (a) ("lambda₀、λ₁And λ₂Both represent estimator parameters, B_fIndicating the viscous friction coefficient.

6. The method for suppressing the rotation speed fluctuation of the permanent magnet brushless direct current motor according to claim 1, wherein the disturbance compensation feedforward control quantity in the fourth step is as follows:

wherein J_mThe moment of inertia of the motor is represented,representing multi-source disturbances d in servo systems_ωEstimated value of, B_fDenotes the coefficient of viscous friction, K_eRepresenting the electromagnetic torque coefficient of the machine.

7. The method for suppressing rotation speed fluctuation of a permanent magnet brushless direct current motor according to claim 1, wherein the non-linear current proportional integrator in the sixth step is specifically:

wherein, K_pI1＝diag(k_p11,k_p12) Representing a first proportional gain matrix of currents, K_pI2＝diag(k_p21,k_p22) Representing a second proportional gain matrix of current, K_iI＝diag(k_i1,k_i2) Representing a current integral gain matrix, diag (-) representing a diagonal matrix, u_iqnRepresenting the q-axis current deviation feedback control quantity, u_idnRepresenting d-axis current deviation feedback control quantity, k_p11、k_p12、k_p21、k_p22、k_i1、k_i2Are positive real numbers.

8. The method for suppressing rotation speed fluctuation of a permanent magnet brushless dc motor according to claim 1, wherein the current change estimator in the seventh step is specifically:

wherein the content of the first and second substances,representing the q-axis current given signal i_qrIs determined by the estimated value of (c),representing the rate of change of a given signal for the q-axis currentEstimate of (e ∈)₁And ε₂Representing the estimator parameters.

9. The method for suppressing rotation speed fluctuation of a permanent magnet brushless DC motor according to claim 1, wherein the q-axis current change feedforward control quantity in the seventh step

Wherein L is_qThe q-axis inductance is represented by,representing the rate of change of a given signal for the q-axis currentAn estimate of (d).

10. A permanent magnet according to claim 1The method for suppressing the fluctuation of the rotating speed of the brushless DC motor is characterized in that the dynamic compensator in the step eight

Wherein R is_sDenotes the stator resistance, L_qRepresenting the q-axis inductance, n_pDenotes the number of pole pairs, phi_vRepresenting the rotor flux linkage, u_iqbRepresents the amount of dynamic compensation of the q-axis current, u_idbRepresenting the dynamic compensation quantity of the d-axis current;

the voltage given signal matrix in the step nine is as follows:

wherein u is_qrGiving a signal, u, for the q-axis voltage_drThe signal is given for the d-axis voltage.

Technical Field

The invention relates to the field of permanent magnet direct current motors, in particular to a rotation speed fluctuation suppression method of a permanent magnet brushless direct current motor based on a nonlinear composite controller.

Background

The permanent magnet brushless direct current motor has the characteristics of high response speed, high positioning precision, large speed regulation range, strong overload capacity and the like, and is widely applied to a plurality of high-performance industrial occasions, such as robots, numerical control machines, machining centers, even aerospace and other fields. In an actual servo system, many factors affecting speed tracking performance exist, such as torque ripple, load interference, signal measurement error, model parameter uncertainty and the like, and the existence of the nonlinear disturbances can cause rotation speed fluctuation of the permanent magnet brushless direct current motor and reduce the control performance of the system, and even affect the stability of the system in a serious case. The traditional cascade PI controller cannot meet the requirement in high-performance speed regulation occasions, and many existing technical methods provide effective disturbance suppression measures for one or more specific disturbances, which are summarized as follows:

1) many technical inventions and scientific and technical literature adopt iterative learning control or repetitive control methods to suppress torque ripple caused by non-sinusoidal distribution of air gap flux density and air gap reluctance change, such as patents (CN 105337550B, a method for suppressing torque ripple of a permanent magnet brushless dc motor, 2018.02.16) and literature (stored sword wave, etc., a method for suppressing rotational speed ripple of a permanent magnet brushless dc motor [ J ], published by the electrotechnical science, 2009, 24(12): 43-49; the algorithm research [ J ], the electric transmission, 2015, 45(9):15-19) of the motor torque ripple suppression at high, wide and low speeds has the advantages that the algorithm is suitable for processing the periodic form disturbance, the construction of a control algorithm does not depend on a system accurate mathematical model, and the suppression capability of the time-varying disturbance with unknown frequency, such as external load variation, parameter perturbation and the like, is poor.

2) For uncertainty of model parameters and external load interference, in recent years, a complex disturbance rejection control method combining a disturbance observer and sliding mode control is adopted in scientific and technical documents to improve the speed regulation performance of a servo system, for example, in patent (CN 104601071B, a permanent magnet brushless direct current motor current loop sliding mode control system based on a disturbance observer, 2017.06.06), document (liu ying and the like, a permanent magnet brushless direct current motor sliding mode control [ J ] based on a novel disturbance observer, chinese motor engineering report, 2010, 30(9):80-85), but due to the effect of a high-frequency switching term in a sliding mode control law, a buffeting problem exists in q-axis current in a closed-loop system, so that unmodeled high-frequency dynamics in the servo system can be excited, and the stability of the system is damaged.

In addition, the design method for the speed regulating system of the permanent magnet brushless direct current motor generally realizes the asymptotic convergence characteristic of the rotating speed tracking, namely the following error of the rotating speed cannot be converged to a balance point within a limited specified time, and when the system has uncertainty and time-varying interference, the asymptotic stable tracking of the rotating speed cannot be realized, so that the speed regulating response performance of the system is limited to a certain extent. Compared with the asymptotic stability Control theory, the proposed finite time Control concept can make the system state have fast convergence performance near the equilibrium point (Bernouan E, Robust fine-time output feedback stability of the double integrator [ J ], International Journal of Control,2015,88(3): 451-460).

Therefore, by designing an efficient and reliable control method, the dynamic response performance of the system is improved while the influence of the rotation speed fluctuation caused by the multi-source interference is reduced, and the method is a difficult point in the development of a servo system.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provide a method for suppressing the rotation speed fluctuation of a permanent magnet brushless direct current motor based on a nonlinear composite controller.

The purpose of the invention can be realized by the following technical scheme:

according to one aspect of the invention, a method for suppressing the rotation speed fluctuation of a permanent magnet brushless direct current motor is provided, and is characterized by comprising the following steps:

acquiring a rotor position theta of a permanent magnet brushless direct current motor, and calculating to obtain a speed feedback signal omega; simultaneously collecting A phase current i of permanent magnet brushless direct current motor winding_aAnd phase B current i_bPerforming coordinate transformation to obtain d-axis current feedback signal i_dAnd q-axis current feedback signal i_q；

Step two, setting a signal omega according to the speed of the permanent magnet brushless direct current motor_rAnd the speed feedback signal omega to obtain a speed deviation signal e_ω＝ω_rOmega, constructing a nonlinear speed proportional integrator to obtain a speed deviation feedback control quantity u_ωn；

Step three, setting a signal omega according to the speed_rConstructing a speed change estimator to obtain a speed change feedforward control quantity u_ωf；

Step four, according to the speed feedback signal omega and the q-axis current feedback signal i_qConstructing a nonlinear multi-source interference estimator to obtain an interference compensation feedforward control quantity u_ωd；

Step five, feeding back the control quantity u according to the speed deviation obtained in the step two to the step four_ωnSpeed change feedforward control quantity u_ωfAnd disturbance compensation feedforward control quantity u_ωdTo obtain a q-axis current given signal i_qr＝u_ωn+u_ωf+u_ωd；

Step six, according to the q-axis current given signal i obtained in the step five_qrAnd q-axis current feedback signal i_qTo obtain a q-axis current deviation signal e_iq＝i_qr-i_qSetting signal i according to d-axis current_dr0 and d-axisCurrent feedback signal i_dObtaining d-axis current deviation signal e_iq＝i_qr-i_qConstructing a nonlinear current proportional integrator to obtain a current deviation feedback control matrix

Step seven, a q-axis current given signal i is obtained according to the step five_qrConstructing a current change estimator to obtain a feedforward control quantity u of the q-axis current change_iqf；

Step eight, according to the speed feedback signal omega and the q axis current feedback signal i_qAnd d-axis current feedback signal i_dConstructing a dynamic compensator to obtain a dynamic compensation control matrix

Step nine, according to the current deviation feedback control matrix obtained in the step six to the step eightFeed-forward control quantity u of q-axis current change_iqfAnd a dynamic compensation control matrixObtaining a voltage given signal matrix

Step ten, giving a q-axis voltage to a signal u_qrAnd d-axis voltage given signal u_drAnd sequentially inputting the signals to the inverse transformation module and the space voltage vector PWM module to obtain a PWM driving signal.

As a preferred technical solution, the coordinate transformation in the first step is Clarke transformation and Park transformation; the inverse transform in the step ten is inverse Park transform; and the PWM driving signal in the step ten is a three-phase inverter bridge 6-path PWM driving signal.

As a preferred technical solution, the non-linear velocity proportional-integral device in the second step is specifically:

wherein k is_pω1Denotes the first proportional gain, k, of the velocity_pω2Representing a second proportional gain, k, of speed_iωRepresenting the velocity integral gain, sign (-) representing a sign function, u_ωnThe speed deviation feedback control amount is indicated.

As a preferred technical solution, the speed change estimator in the third step specifically is:

wherein the content of the first and second substances,representing a speed-setting signal omega_rIs determined by the estimated value of (c),indicating rate of change of speed given signalEstimate of (c), xi₁And xi₂Representing an estimator parameter;

the speed change feedforward control quantity in the third step is specifically as follows:wherein, J_mRepresenting the moment of inertia of the motor, K_eRepresenting the electromagnetic torque coefficient, L, of the machine_dRepresenting d-axis inductance, L_qRepresenting the q-axis inductance, n_pDenotes the number of pole pairs, phi_vRepresenting the rotor flux linkage; the electromagnetic torque coefficient is as follows:

as a preferred technical solution, the non-linear multi-source interference estimator in the fourth step specifically includes:

wherein, J_mRepresenting the moment of inertia of the motor, K_eRepresenting the electromagnetic torque coefficient of the electrical machine,representing an estimate of the velocity feedback signal omega,representing multi-source disturbances d in servo systems_ωEstimate of (a) ("lambda₀、λ₁And λ₂Both represent estimator parameters, B_fIndicating the viscous friction coefficient.

As a preferred technical solution, the disturbance compensation feedforward control amount in the fourth step is:

wherein J_mThe moment of inertia of the motor is represented,representing multi-source disturbances d in servo systems_ωEstimated value of, B_fDenotes the coefficient of viscous friction, K_eRepresenting the electromagnetic torque coefficient of the machine.

As a preferred technical solution, the non-linear current proportional integrator in the step six is specifically:

wherein, K_pI1＝diag(k_p11,k_p12) Representing a first proportional gain matrix of currents, K_pI2＝diag(k_p21,k_p22) Second proportional gain representing currentMatrix, K_iI＝diag(k_i1,k_i2) Representing a current integral gain matrix, diag (-) representing a diagonal matrix, u_iqnRepresenting the q-axis current deviation feedback control quantity, u_idnRepresenting d-axis current deviation feedback control quantity, k_p11、k_p12、k_p21、k_p22、k_i1、k_i2Are positive real numbers.

As a preferred technical solution, the current change estimator in the step seven specifically comprises:

wherein the content of the first and second substances,representing the q-axis current given signal i_qrIs determined by the estimated value of (c),representing the rate of change of a given signal for the q-axis currentEstimate of (e ∈)₁And ε₂Representing the estimator parameters.

Preferably, the q-axis current change feedforward control amount in the step seven is

Wherein L is_qThe q-axis inductance is represented by,representing the rate of change of a given signal for the q-axis currentAn estimate of (d).

As a preferred technical solution, the dynamic compensator in the step eight

Wherein R is_sDenotes the stator resistance, L_qRepresenting the q-axis inductance, n_pDenotes the number of pole pairs, phi_vRepresenting the rotor flux linkage, u_iqbRepresents the amount of dynamic compensation of the q-axis current, u_idbRepresenting the dynamic compensation quantity of the d-axis current;

the voltage given signal matrix in the step nine is as follows:

wherein u is_qrGiving a signal, u, for the q-axis voltage_drThe signal is given for the d-axis voltage.

Compared with the prior art, the invention has the following advantages:

1) the nonlinear multi-source interference estimator is constructed by utilizing the speed feedback signal and the q-axis current feedback signal, time-varying interference factors such as torque ripple, load interference, signal measurement error, model parameter uncertainty and the like in a servo system are accurately estimated and compensated, and compared with a traditional Extended State Observer (ESO), a Disturbance Observer (DOB) and a limited time observer (FTDO), the interference estimation precision and efficiency are improved;

2) the method is based on PI control and nonlinear control design ideas, realizes a continuous finite time control scheme, eliminates buffeting influence caused by discontinuous switching items compared with a scheme based on terminal sliding mode control, and simultaneously ensures the robustness and stability of the system;

3) compared with the existing control scheme based on asymptotic stability, the nonlinear composite controller strategy combining feedforward and feedback provided by the invention is stable in limited time, and the dynamic response performance and the anti-interference capability of a servo system are improved.

Drawings

FIG. 1 is a system block diagram of a nonlinear composite controller of the present invention;

FIG. 2 is a schematic diagram of a non-linear velocity proportional-integrator;

FIG. 3 is a schematic diagram of a speed variation estimator;

FIG. 4 is a schematic diagram of a non-linear multi-source interference estimator;

FIG. 5 is a speed response graph for a step speed given signal;

FIG. 6 is a graph of q-axis current for a given step speed signal;

FIG. 7 is a graph of d-axis and q-axis voltage for a given step speed signal;

FIG. 8 is a graph of speed response for a sinusoidal speed given signal;

FIG. 9 is a graph of q-axis current for a given sinusoidal velocity signal;

FIG. 10 is a graph of d-axis and q-axis voltage for a given sinusoidal velocity signal.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.

Examples

According to the invention, a nonlinear speed proportional integrator, a speed change estimator, a nonlinear multisource interference estimator, a nonlinear current proportional integrator, a current change estimator and a dynamic compensator are constructed by collecting a speed feedback signal and a d-q axis current feedback signal of the permanent magnet brushless direct current motor, so that the suppression control of the rotation speed fluctuation of the permanent magnet brushless direct current motor is realized; a nonlinear multi-source interference estimator is constructed by utilizing a speed feedback signal and a q-axis current feedback signal, and time-varying interference factors such as torque ripple, load interference, signal measurement errors, model parameter uncertainty and the like in a servo system are accurately estimated and compensated; the nonlinear composite controller strategy of combining feedforward and feedback achieves finite time stability. Therefore, the invention realizes a method for suppressing the rotation speed fluctuation of a permanent magnet brushless direct current motor based on a nonlinear composite controller, the design block diagram is shown in fig. 1, and the method comprises the following specific steps:

acquiring a rotor position theta of a permanent magnet brushless direct current motor and calculating to obtain a speed feedback signal omega; collecting permanent magnet brushless DC motor winding current i_aAnd i_bObtaining a d-axis current feedback signal i by Clarke transformation and Park transformation calculation_dAnd q-axis current feedback signal i_q；

Step two, setting a signal omega according to the speed of the permanent magnet brushless direct current motor_rAnd the speed feedback signal omega to obtain a speed deviation signal e_ω＝ω_r- ω, constructing a non-linear velocity proportional integrator, as shown in fig. 2:

wherein k is_pω1Denotes the first proportional gain, k, of the velocity_pω2Representing a second proportional gain, k, of speed_iωRepresenting the velocity integral gain, sign (-) representing a sign function, u_ωnIndicating a speed deviation feedback control quantity;

step three, setting a signal omega according to the speed_rThe velocity variation estimator is constructed as shown in fig. 3:

wherein the content of the first and second substances,representing a speed-setting signal omega_rIs determined by the estimated value of (c),indicating rate of change of speed given signalEstimate of (c), xi₁And xi₂Representation estimationA counter parameter;

calculating a speed change feedforward control quantity:wherein J_mRepresenting the moment of inertia of the motor, K_eRepresenting an electromagnetic torque coefficient of the electric machine;

step four, according to the speed feedback signal omega and the q-axis current feedback signal i_qAnd constructing a nonlinear multi-source interference estimator, as shown in fig. 4:

whereinRepresenting an estimate of the velocity feedback signal omega,representing multi-source disturbances d in servo systems_ωEstimate of (a) ("lambda₀、λ₁And λ₂Representing the estimator parameters, B_fRepresents a viscous friction coefficient;

calculating disturbance compensation feedforward control quantity

Step five, feeding back the control quantity u according to the speed deviation obtained in the step two to the step four_ωnSpeed change feedforward control quantity u_ωfAnd disturbance compensation feedforward control quantity u_ωdCalculating a q-axis current given signal i_qr＝u_ωn+u_ωf+u_ωd；

Step six, according to the q-axis current given signal i obtained in the step five_qrAnd q-axis current feedback signal i_qTo obtain a q-axis current deviation signal e_iq＝i_qr-i_qSetting signal i according to d-axis current_dr0 and d-axis current feedback signal i_dObtaining d-axis current deviation signale_iq＝i_qr-i_qConstructing a nonlinear current proportional integrator:wherein K_pI1＝diag(k_p11,k_p12) Representing a first proportional gain matrix of currents, K_pI2＝diag(k_p21,k_p22) Representing a second proportional gain matrix of current, K_iI＝diag(k_i1,k_i2) Representing a current integral gain matrix, diag (-) representing a diagonal matrix,representing a current deviation feedback control matrix;

step seven, a q-axis current given signal i is obtained according to the step five_qrConstructing a current variation estimatorWherein the content of the first and second substances,representing the q-axis current given signal i_qrIs determined by the estimated value of (c),representing the rate of change of a given signal for the q-axis currentEstimate of (e ∈)₁And ε₂Representing an estimator parameter;

calculating a feedforward control quantity of the change of the q-axis current

Step eight, according to the speed feedback signal omega and the q axis current feedback signal i_qAnd d-axis current feedback signal i_dTo construct a dynamic compensatorWherein R is_sThe resistance of the stator is represented by,representing a dynamic compensation control matrix;

step nine, according to the current deviation feedback control matrix obtained in the step six-eightFeed-forward control quantity u of q-axis current change_iqfAnd a dynamic compensation control matrixCalculating a voltage given signal matrixWherein u is_qrGiving a signal, u, for the q-axis voltage_drA signal is given for the d-axis voltage,

step ten, mixing u_qrAnd u_drAnd respectively inputting the signals to a Park inverse transformation and space voltage vector PWM module so as to obtain 6 paths of PWM driving signals of the three-phase inverse transformation bridge.

In this embodiment, the electrical parameters of the permanent magnet brushless dc motor are selected as follows:

(symbol)	means of	Numerical value
			P	Rated power	100W
U	Rated voltage	48V
			IN	Rated current	2.5A
TN	Rated torque	0.64N·m
			Jm	Moment of inertia	1.469×10-5kg·m2
np	Number of pole pairs	5
			Rs	Stator resistor	3.435Ω
Ld、Lq	d-axis and q-axis inductors	9.15mH
			Bf	Coefficient of viscous friction	6.5×10-5N·m·s/rad
φv	Rotor flux linkage	0.09wb

In addition, the control parameter adjustment rule involved in the nonlinear composite controller of the present invention is as follows:

1) first proportional gain k of velocity in nonlinear velocity proportional integrator_pω1Velocity second proportional gain k_pω2And velocity integral gain k_iωFor adjusting the convergence rate of the speed deviation signal to satisfy k_pω1＞0、k_pω2＞0、k_iωThe gain is more than 0, and the gain size and the convergence rate form a positive correlation;

2) parameter xi in speed variation estimator₁And xi₂The estimation error for regulating the change rate of speed given signal satisfies xi₁＞0、ξ₂If the parameter is more than 0, the parameter size and the estimation error form a negative correlation relation;

3) parameter lambda in non-linear multi-source interference estimator₀、λ₁And λ₂For adjusting interference estimation error to satisfy lambda₀＞0、λ₁＞0、λ₂If the parameter is more than 0, the parameter size and the estimation error form a negative correlation relation;

4) current first proportional gain matrix K in nonlinear current proportional integrator_pI1＝diag(k_p11,k_p12) Current second proportional gain matrix K_pI2＝diag(k_p21,k_p22) And current integral gain matrix K_iI＝diag(k_i1,k_i2) For adjusting the convergence rate of the d-axis and q-axis current deviation signals to satisfy k_p11＞0、k_p12＞0、k_p21＞0、k_p22＞0、k_i1＞0、k_i2The gain is more than 0, and the gain size and the convergence rate form a positive correlation;

5) parameter epsilon in current variation estimator₁And ε₂The estimation error for regulating the change rate of the given signal of the q-axis current satisfies epsilon₁＞0、ε₂> 0, the parameter magnitude is inversely related to the estimation error.

Two permanent magnet brushless dc motor conditions were set to illustrate the effectiveness of the invention:

1) given step speed given signal omega_r500rpm, disturbance torque set to d_ω＝0.1sin(16πt)+0.5；

2) Given sinusoidal velocity given signal ω_r500sin (10 π t) rpm, disturbance moment set to d_ω＝0.1sin(16πt)+0.5。

According to the parameter selection rule and in combination with the permanent magnet brushless direct current motor selected in the embodiment, the control parameters are set as follows:

meanwhile, in order to compare the effectiveness of the control scheme, compared with the scheme based on the common PI controller, the PI controller is designed as follows:

1) speed loop PI controller

2) Current loop PI controllerThe control parameters are selected as follows:

module	Parameter(s)
		Speed loop PI controller	kpω＝0.5，kiω＝100
Current loop PI controller	KpI＝diag(200,200)，KiI＝diag(104,104)

FIGS. 5-7 show the response curves of rotor speed, q-axis current, d-axis and q-axis voltage, respectively, for a given step speed signal; fig. 8-10 show the response curves of rotor speed, q-axis current, d-axis and q-axis voltage, respectively, for a given sinusoidal speed signal. The test result shows that the design method of the nonlinear composite controller can well inhibit the influence of multi-source interference on the speed control precision and improve the dynamic response performance of a servo system.

While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.