Rotating speed flux linkage cascade robust control method and system of permanent magnet motor system

Abstract

The invention discloses a rotating speed flux linkage cascade robust control method and system for a permanent magnet motor system, and the method comprises the steps: firstly obtaining motor parameters of a permanent magnet motor, and then carrying out the observation of a system operation process through a composite discrete extended state observer; a rotating speed flux linkage cascade model-free predictive controller is built based on a super-local model, a lumped disturbance value estimated by the observer is input into the rotating speed flux linkage cascade model-free predictive controller, a q-axis flux linkage instruction value is output by a rotating speed ring through a given value and a response value, and a required dq-axis voltage instruction value is output by a flux linkage ring; and a pulse signal is generated to drive the permanent magnet motor after reverse Park conversion and an SVPWM modulation module. From a new angle of combination of inherent structure improvement of model predictive control and observer compensation, the problem of parameter mismatch of the permanent magnet motor system is solved, the dependence of the control system on a motor mathematical model is reduced, the influence caused by parameter perturbation and external disturbance is suppressed, and the control performance of the permanent magnet motor system is improved.

Description

Technical Field

[0001] The present invention relates to a control technology of a permanent magnet motor system, and in particular to a speed flux cascade robust control method and system of a permanent magnet motor system, in particular to a control technology applied to a large permanent magnet motor system. Background Art

[0002] Permanent magnet motor system has the characteristics of high efficiency and high power density, and has been widely studied and paid attention to in heavy-duty mining trucks, new energy passenger vehicles, wind power generation and other equipment. As the key and core component of the composite transmission system, the control performance and reliability of the permanent magnet motor system are the key to its development.

[0003] Model predictive control technology is a high-performance control method that realizes optimal control based on the current state variables and discrete mathematical models of the controlled system. It is suitable for multi-objective control of the system. With its advantages of fast dynamic response speed, simple algorithm implementation, zero steady-state error and no overshoot, it has become a representative of the successful application of advanced control technology for motor systems in the industrial field. However, the traditional model predictive control of permanent magnet motor systems is heavily dependent on mathematical models. When the parameters are mismatched, it will lead to large flux linkage, torque pulsation and high current distortion rate. Especially under extreme working conditions such as heavy load uphill, large load impact, and high speed domain, the control effect is not ideal, which seriously restricts the application of permanent magnet motor model predictive control. Therefore, the control technology to solve the parameter mismatch problem is what needs to be explored in this field; among them, at present, for the parameter mismatch problem of model predictive control of permanent magnet motor systems, the observer is mainly used to simply compensate for the unknown disturbance caused by parameter mismatch, and the model predictive control structure has not been improved. Summary of the invention

[0004] The purpose of the present invention is to solve the parameter mismatch problem of the permanent magnet motor system model predictive control with another technical idea, reduce the dependence of the predictive control system on the mathematical model of the motor, that is, to solve the parameter mismatch problem of the permanent magnet motor system from a new perspective of combining the improvement of the inherent structure of the model predictive control and the observer compensation; among them, the speed flux cascade model-free predictive controller designed using the super-local model theory only needs to set the system input and output, does not involve any motor parameters, and has an ideal control effect, especially in electric power transportation equipment.

[0005] To this end, the present invention provides the following technical solutions:

[0006] On the one hand, the present invention provides a speed flux cascade robust control method for a permanent magnet motor system, comprising the following steps:

[0007] S1: Obtaining motor parameters of the permanent magnet motor, wherein the motor parameters include at least the current, actual flux linkage, and actual speed of the motor;

[0008] S2: Based on the composite discrete extended state observer, the actual speed and actual flux are used to observe the operation process of the permanent magnet motor to obtain a lumped disturbance, a flux observation value and a speed observation value, wherein the lumped disturbance includes a speed loop lumped disturbance and a flux loop lumped disturbance;

[0009] S3: Feeding back the lumped disturbance, flux observation value, and speed observation value to a speed flux cascade model-free predictive controller designed based on a super-local model to obtain a q-axis voltage command value, wherein the speed flux cascade model-free predictive controller includes a speed model-free predictive controller and a flux model-free predictive controller connected to each other;

[0010] The speed loop lumped disturbance and the speed observation value are input into the speed model-free predictive controller to predict the q-axis flux command value; the flux loop lumped disturbance, the flux observation value and the dq-axis flux command value are input into the flux model-free predictive controller to predict the dq-axis voltage command value, and the d-axis flux command value is preset;

[0011] S4: Inputting the αβ phase voltage command value transformed based on the dq axis voltage command value into the modulation module of the permanent magnet motor to realize motor control.

[0012] The technical solution of the present invention is dedicated to solving the mismatch of inductance and flux parameters under complex working conditions, involving an outer speed loop and an inner flux loop, eliminating the influence of different parameter perturbations in controller design, and not involving the application of cascade controllers of inductance and flux to the inner and outer loops. The observation error of the speed and the observation error of the flux are then used to estimate the input states and disturbance terms of the inner and outer loops through a composite discrete extended state observer to achieve smooth operation and precise control of the controller.

[0013] Optionally, the control model of the speed model-free predictive controller is expressed as:

[0014]

[0015] Using the Lagrange interpolation method, we can get:

[0016] ψ q ref (k+1)=3ψ q ref (k)-3ψ q ref (k-1)+ψ q ref (k-2)

[0017] In the formula, ψ q ref (k-2),ψ q ref (k-1),ψ qref (k),ψ q ref (k+1) are the q-axis flux command values ​​at k-2, k-1, k, and k+1 time / sampling points, ω ref (k+1) is the reference speed at k+1 time / sampling point, is the observed speed value at time k+1 / sampling point, is the total disturbance of the speed loop at time k+1 / sampling point, α is the gain of the speed super-local model, T s is the sampling period.

[0018] Optionally, the control model of the flux linkage model-free predictive controller is expressed as:

[0019]

[0020] In the formula, Indicates the predicted d-axis and q-axis voltage command values ​​at time k / sampling point vector, T is the matrix transpose symbol, Represents the lumped disturbance of the d- and q-axis magnetic flux loops at time k+1 / sampling point The vector of Indicates the observed value of d-axis and q-axis magnetic flux at time k+1 / sampling point The vector of Indicates the d-axis and q-axis flux command values ​​at k+1 time / sampling point The vector of s is the sampling period, and β is the gain of the magnetic flux hyperlocal model.

[0021] Optionally, the speed model-free predictive controller and the flux model-free predictive controller are constructed based on reasoning based on establishing a hyperlocal model for speed control and establishing a hyperlocal model for flux control, respectively;

[0022] The hyperlocal model of speed control is expressed as:

[0023]

[0024] Where α is the gain of the speed super-local model, d is the speed loop lumped disturbance, ω e is the speed, t is the time;

[0025] The hyperlocal model of flux linkage control is expressed as:

[0026]

[0027] In the formula, ψ s represents the d- and q-axis stator flux ψ d ,q The vector, U s is the d and q axis voltage vector, F s is the lumped disturbance vector of the d- and q-axis flux loops, and β is the gain of the flux hyperlocal model.

[0028] Optionally, the observation model of the composite discrete extended state observer is expressed as:

[0029]

[0030] There exists, the x matrix of k moments / sampling points The actual value of the stator flux of the d and q axes at the k time / sampling point ψ d (k),ψ q (k), actual speed value ω e (k) constitutes; the state matrix observation value of k time / sampling point The d-axis and q-axis stator flux observation values ​​at k time / sampling point Speed ​​observation value Composition; error matrix of k time / sampling point The flux error e at time k / sampling point s (k), speed error e ω (k) constitutes; U at k moment / sampling point o matrix The d-axis and q-axis stator voltages u at the k moment / sampling point are d (k),u q (k), q-axis magnetic flux ψ q (k) constitutes; the lumped disturbance matrix of k time / sampling point The speed loop lumped disturbance at k time / sampling point Magnetic flux ring lumped disturbance Composition; Matrix Matrix N = T s I 3×3 ,matrix matrix

[0031] Where, T s is the sampling time, γ1 and γ2 are the speed loop observer gains; β is the gain of the flux hyperlocal model, α is the gain of the speed hyperlocal model; λ1 and λ2 are the flux loop observer gains.

[0032] Optionally, the observation model of the composite discrete extended state observer is obtained by discretizing the speed observation model and the flux observation model of the composite discrete extended state observer;

[0033] Among them, the state input of the speed control system is defined as the q-axis flux and the speed loop lumped disturbance, corresponding to the speed observation model of the composite discrete extended state observer, which is expressed as:

[0034]

[0035] The state input of the flux control system is defined as the dq-axis stator voltage and the flux ring lumped disturbance. The flux observation model corresponding to the composite discrete extended state observer is expressed as:

[0036]

[0037] In the formula, ω e They are the observed speed value and the actual speed value respectively; ψ s are the observed value of magnetic flux vector and the actual value of magnetic flux vector, respectively. s is the d and q axis voltage vector; is the observed value of the lumped disturbance vector of the d-axis and q-axis flux loops, and β is the gain of the flux hyperlocal model.

[0038] In another aspect, the present invention provides a control system based on the above control method, comprising at least:

[0039] The composite discrete extended state observer uses the actual speed and actual flux of the permanent magnet motor to observe the operation process of the permanent magnet motor to obtain lumped disturbances, flux observation values ​​and speed observation values, wherein the lumped disturbances include the speed loop lumped disturbances and the flux loop lumped disturbances;

[0040] A speed model-free predictive controller predicts a q-axis flux command value using the speed loop lumped disturbance and the speed observation value;

[0041] A flux model-free predictive controller predicts a dq axis voltage command value using the flux loop lumped disturbance, the flux observation value, and a dq axis flux command value, wherein the d axis flux command value is preset;

[0042] An inverse Park transformation module is used to transform the dq axis voltage command value into the αβ phase voltage command value;

[0043] The modulation module generates motor commands using the αβ phase voltage command values ​​to achieve motor control.

[0044] In a third aspect, the present invention provides a permanent magnet motor provided with the above-mentioned control system, wherein the control system is connected to the permanent magnet motor body and is used to control the operation of the permanent magnet motor.

[0045] In a fourth aspect, the present invention provides an electronic device, comprising: one or more processors and a memory storing one or more computer programs;

[0046] The processor calls the computer program to implement:

[0047] Acquire motor parameters of the permanent magnet motor, wherein the motor parameters at least include the current, actual flux linkage, and actual speed of the motor;

[0048] Based on the observation of the composite discrete extended state observer, the actual speed and the actual flux are used to observe the lumped disturbance of the permanent magnet motor operation process to obtain the lumped disturbance, the flux observation value and the speed observation value, wherein the lumped disturbance includes the speed loop lumped disturbance and the flux loop lumped disturbance;

[0049] The dq axis voltage command values ​​are obtained by using the lumped disturbance, flux observation value, speed observation value and the control model of the speed flux cascade model-free predictive controller designed based on the hyperlocal model;

[0050] The αβ phase voltage command value transformed based on the dq axis voltage command value is modulated to generate a motor command for the permanent magnet motor, thereby realizing motor control.

[0051] In a fifth aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program is called by a processor to implement:

[0052] Acquire motor parameters of the permanent magnet motor, wherein the motor parameters at least include the current, actual flux linkage, and actual speed of the motor;

[0053] Based on the observation of the composite discrete extended state observer, the actual speed and the actual flux are used to observe the lumped disturbance of the permanent magnet motor operation process to obtain the lumped disturbance, the flux observation value and the speed observation value, wherein the lumped disturbance includes the speed loop lumped disturbance and the flux loop lumped disturbance;

[0054] The dq axis voltage command values ​​are obtained by using the lumped disturbance, flux observation value, speed observation value and the control model of the speed flux cascade model-free predictive controller designed based on the hyperlocal model;

[0055] The αβ phase voltage command value transformed based on the dq axis voltage command value is modulated to generate a motor command for the permanent magnet motor, thereby realizing motor control.

[0056] Beneficial Effects

[0057] Compared with the existing method, the advantages of the present invention are:

[0058] 1. Aiming at the high requirements of the control system on the accuracy of the motor mathematical model, the technical solution of the present invention uses the hyperlocal model to design interconnected speed model-free predictive controller and flux model-free predictive controller. Among them, the controller built based on the hyperlocal model only needs the input and output of the system, and does not involve any motor parameters such as inductance and flux. It can effectively suppress the internal disturbance caused by parameter drift and reduce the sensitivity of the control system to parameter changes.

[0059] 2. The composite discrete extended state observer designed in the preferred solution of the present invention can accurately estimate the lumped disturbances generated by the speed loop and the flux loop during the system operation process and timely feed back to the cascade prediction controller, with good convergence and high control accuracy. At the same time, the observer avoids tedious parameter setting and reduces the difficulty of designing the control algorithm. That is, the technical solution of the present invention can simultaneously observe the output state of the speed loop and the flux loop and the disturbance term of each loop. In the past, the speed loop was usually ignored and PI control or traditional model prediction was directly used. This observer can be applied to the observation of both the speed loop and the flux loop.

[0060] 3. The present invention can directly output the required q-axis stator flux command value from the speed loop, and both the speed and flux are model-free predictive control methods, avoiding the coupling problem in the system. In addition, delay compensation is considered, eliminating the inherent one-shot delay of the digital system, and improving the multi-type anti-disturbance performance of the control system.

[0061] 4. The technical solution of the present invention has a remarkable effect when applied to electric power transmission equipment. Electric power transmission equipment works in a high-voltage and wide-temperature environment and is subjected to gravity loading all year round. In this case, it is easy to induce perturbations in the actual parameters of the generator. Traditional model predictions rely heavily on accurate motor mathematical models, and it is not realistic to achieve precise control under harsh conditions. Therefore, in order to solve the problem of motor parameter mismatch, the traditional model prediction is improved. The controllers for the speed loop and the flux loop eliminate the influence of parameters, and the composite discrete extended state observer is used to ensure the stability and accuracy of the two newly proposed controllers. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic diagram of a basic flow chart of a method according to an embodiment of the present invention;

[0063] Figure 2 A schematic diagram of the control principle of the method according to an embodiment of the present invention;

[0064] Figure 3 It is a schematic diagram of simulation of torque and current control performance when the inductance parameters are perturbed by the control algorithm of the present invention;

[0065] Figure 4 It is a schematic diagram of simulation of stator flux control performance when the inductance parameter is perturbed by the control algorithm of the present invention;

[0066] Figure 5 It is a schematic diagram of the simulation of torque and current control performance when the permanent magnet flux is demagnetized by using the control algorithm of the present invention;

[0067] Figure 6 Schematic diagram of simulation of stator flux control performance when permanent magnet flux is demagnetized using the control algorithm of the present invention. DETAILED DESCRIPTION

[0068] The present invention provides a speed flux cascade robust control method and system for a permanent magnet motor system, which provides a new feasible way to solve the parameter mismatch problem of the permanent magnet motor system by improving the inherent structure of the model predictive control and combining it with observer compensation, reduces the dependence of the model predictive control system on the motor mathematical model, suppresses the influence of parameter perturbations and external disturbances, and improves the control performance of the permanent magnet motor system, so that when the present invention is applied to electric transport equipment, the effect is significant, effectively overcomes the defect of the traditional model predictive control in the extreme working conditions such as heavy load uphill, large load impact, high speed domain, etc., and ensures the application of the permanent magnet motor model predictive control in electric transport equipment. The present invention will be further described in conjunction with the embodiments below.

[0069] like Figure 1 and Figure 2 As shown, this embodiment provides a speed flux cascade robust control method for a permanent magnet motor system, comprising the following steps:

[0070] Step 1) Get the actual speed ω of the permanent magnet motor at the current moment e , d-axis current i d , q-axis current i q , and the current d-axis magnetic flux ψ d , q-axis flux ψ q ; Among them, the current d-axis flux ψ is obtained through the flux state calculation module d , q-axis flux ψ q ,Since the flux state calculation module is ,realizable by existing technology, it will not be elaborated in detail.

[0071] Step 2) Design a composite discrete extended state observer to transform the speed ω obtained in step 1) e 、d-axis flux ψ d , q-axis flux ψ q Input the composite discrete extended state observer to obtain the speed observation value generated by the speed loop and the flux link loop during the system operation process q-axis magnetic flux observation value And the lumped disturbance, the lumped disturbance includes the speed loop lumped disturbance and the flux ring lumped disturbance

[0072]

[0073] Among them, the reasoning construction process of the composite discrete extended state observer is as follows:

[0074] 2.1) The state equation of the permanent magnet motor under fault conditions is expressed as follows:

[0075]

[0076] Where x is the matrix composed of dq axis stator flux and motor speed, u is the matrix composed of dq axis stator voltage and q axis stator flux, and f a is the disturbance term, f b is the torque term, A, B, C, D are the coefficient terms of the state equation; the specific expression is as follows:

[0077]

[0078] C=diag(1,1,1),D=[00-p / J] T

[0079] Where, T L is the load torque, f d 、f q 、f ω are the mismatches caused by internal and external disturbances, and the specific expressions are as follows:

[0080]

[0081] In the formula, ψ d is the d-axis stator flux, ψ q is the q-axis stator flux, ω e is the motor speed, u d is the d-axis voltage, u q is the q-axis voltage, T L is the load torque, R o is the nominal value of stator resistance, L o is the nominal value of stator inductance, ψ fo is the nominal value of permanent magnet flux, p is the number of motor pole pairs, J is the motor moment of inertia, ΔL is the stator inductance mismatch, Δψ f is the rotor flux mismatch, ΔT L is the load torque variation.

[0082] 2.2) Constructing an observer, which includes the speed observation design and the flux observation design. In this embodiment, the speed and flux control systems are both first-order, and a second-order extended state observer can be used.

[0083] Among them, the state input of the speed observation system is defined as the q-axis flux and the speed loop lumped disturbance, and the speed observation design of the composite discrete extended state observer is constructed as follows:

[0084]

[0085] In the formula, ω e is the actual speed value, is the observed value of speed, e ω is the error between the observed speed and the actual speed, ψ q is the actual value of the q-axis flux, α is the gain of the speed super-local model, is the lumped disturbance generated by the speed response process, γ1 and γ2 are the speed loop observer gains.

[0086] The state input of the flux observation system is defined as the dq-axis stator voltage and the flux ring lumped disturbance, and the composite discrete extended state observer flux observation design is constructed as follows:

[0087]

[0088] In the formula, ψ s is the actual value of stator flux, is the observed value of stator flux, e s is the error between the observed value and the actual value of the stator flux, U s is the actual value of voltage, β is the gain of the flux hyperlocal model, is the lumped disturbance generated by the flux response process, λ1 and λ2 are the speed loop observer gains, which are expressed in detail as follows:

[0089]

[0090] 2.3) Discretize the observer and use the forward Euler method to get the discrete state expression as shown in formula (5):

[0091]

[0092] In the formula, T s is the sampling period, N = T s I 3×3 ,

[0093] At this point, this embodiment preferably uses the composite discrete extended state observer shown in formula (5) to observe the lumped disturbance Matrix representing flux observations and speed observations Other feasible embodiments, such as sliding mode observer, Lumberg observer and other alternative methods can also obtain the above parameters, which are applicable to the technical solution of the present invention.

[0094] Step 3) Based on the hyperlocal model of speed control, a speed model-free predictive controller is designed, and the speed is adjusted according to the reference speed. The lumped disturbance of the speed loop is obtained in the composite discrete extended state observer and speed observations Perform predictive calculation to obtain the q-axis flux command value Among them, the reasoning and construction process of the speed model-free predictive controller is as follows:

[0095] The ultra-local model structure of speed control is established as shown in formula (6):

[0096]

[0097] Formula (6) is discretized using the forward Euler discretization method to obtain formula (7):

[0098]

[0099] This embodiment takes into account the one-shot delay of the digital system and performs delay compensation on the controller to obtain the final q-axis flux command value:

[0100]

[0101] ψ q ref (k+1)=3ψ q ref (k)-3ψ q ref (k-1)+ψ q ref (k-2)(9)

[0102] In the formula, ψ q ref (k-2),ψ q ref (k-1),ψ q ref (k),ψ q ref (k+1) are the q-axis flux command values ​​at the k-2, k-1, k, and k+1 moments / sampling points respectively, is the speed command value, is the observed value of the speed, is the lumped disturbance observation value of the speed loop, T s is the sampling period.

[0103] Step 4) Based on the ultra-local model of flux control, a flux model-free predictive controller is designed to obtain the dq axis voltage command value, and the ultra-local model structure of flux control is established as shown in formula (10):

[0104]

[0105] In the formula, ψ s is the stator flux vector, U s is the dq axis voltage vector, F s is the lumped disturbance of the flux control system, which is specifically expressed as:

[0106] U s =[u d u q ] T , F s =[F d F q ] T ,

[0107] f s =[f d f q ] T .

[0108] This embodiment also considers the delay compensation to obtain the final dq axis voltage command value as shown in formula (11):

[0109]

[0110] It should be understood that when the technical solution of the present invention uses the super-local model to design the speed model-free predictive controller and the flux model-free predictive controller, the structure shown in formulas (6) and (10) is built. It can be seen from the above that α and β are both tried out in the simulation process, F and d are both obtained by the observer, and parameters such as inductance and flux are not used; and because the disturbance caused by resistance mismatch is very small and can be ignored, the resistance is not considered.

[0111] Step 5) Set the d-axis voltage command value and q-axis voltage command value The voltage command value in the two-phase stationary coordinate system is obtained by inverse Park transformation

[0112] Step 6) The obtained α phase voltage command value and β phase voltage command value The required signal is input into the SV-PWM modulation module to drive the permanent magnet motor to operate.

[0113] It should be understood that step 5 and step 6 are conventional technical means of permanent magnet motors in the art, and therefore, they will not be elaborated in detail.

[0114] In order to verify the effect of the technical solution of the present invention, the present invention applies the control method to electric power transport equipment and obtains the following conclusions:

[0115] Figure 3 This is a schematic diagram of torque and current under the condition of inductance parameter perturbation when the parameter mismatch robust predictive control method is used for permanent magnet motor system of electric vehicle equipment. In the figure, T e is the electromagnetic torque, i abc is the three-phase current of the motor. It can be seen from the figure that the torque current responds quickly, the torque static error is small and there is no obvious pulsation, the three-phase current waveform is stable, and there is no current distortion.

[0116] Figure 4 This is a schematic diagram of the stator flux linkage when the inductance parameter is perturbed when the parameter mismatch robust predictive control method for permanent magnet motor system for electric vehicle equipment is used. In the figure, is the stator flux command value, ψ s is the actual value of stator flux, is the α-axis flux command value, ψ α is the actual value of the α-axis magnetic flux, is the β-axis flux command value, ψ β It is the actual value of the β-axis flux. It can be seen from the figure that the actual value of the stator flux can accurately track the command value, and the actual values ​​of the αβ-axis flux components can also effectively track the command value, with small static error and no obvious pulsation.

[0117] Figure 5 The torque and current diagram of the permanent magnet flux loss case when the permanent magnet motor system parameter mismatch robust predictive control method is used for electric vehicle equipment. In the figure, T e is the electromagnetic torque, i abc is the three-phase current of the motor. It can be seen from the figure that the torque current responds quickly, the torque static error is small and there is no obvious pulsation, the three-phase current waveform is stable, and there is no current distortion.

[0118] Figure 6 This is a schematic diagram of the stator flux linkage when the inductance parameter is perturbed when the parameter mismatch robust predictive control method for permanent magnet motor system for electric vehicle equipment is used. In the figure, is the stator flux command value, ψ s is the actual value of stator flux, is the α-axis flux command value, ψ α is the actual value of the α-axis magnetic flux, is the β-axis flux command value, ψ β It is the actual value of the β-axis flux. It can be seen from the figure that the actual value of the stator flux can accurately track the command value, and the actual values ​​of the αβ-axis flux components can also effectively track the command value, with small static error and no obvious pulsation.

[0119] In summary, this embodiment can effectively control permanent magnet motors for electric vehicle equipment with parameter mismatches under extreme working conditions, effectively suppress the flux, torque pulsation and motor current distortion generated under multiple types of disturbances, significantly improve the anti-interference performance of the motor control system, and achieve high-performance control of permanent magnet motors under complex working conditions.

[0120] In some embodiments, the present invention further provides a control system based on the above control method, comprising at least:

[0121] The composite discrete extended state observer uses the actual speed and actual flux of the permanent magnet motor to observe the operation process of the permanent magnet motor to obtain lumped disturbances, flux observation values ​​and speed observation values, wherein the lumped disturbances include the speed loop lumped disturbances and the flux loop lumped disturbances;

[0122] A speed model-free predictive controller predicts a q-axis flux command value using the speed loop lumped disturbance and the speed observation value;

[0123] A flux model-free predictive controller predicts a dq axis voltage command value using the flux loop lumped disturbance, the flux observation value, and a dq axis flux command value, wherein the d axis flux command value is preset;

[0124] An inverse Park transformation module is used to transform the dq axis voltage command value into the αβ phase voltage command value;

[0125] The modulation module generates a motor command using the αβ phase voltage command value to realize motor control.

[0126] It should be understood that the connection relationship and signal transmission relationship between the above elements in this embodiment can be specifically referred to Figure 2 The above functional modules may be implemented in hardware or software, and the present invention does not impose any specific limitation on this.

[0127] In other embodiments, the control system mentioned above can be regarded as a subsystem of the permanent magnet motor, which is connected to the permanent magnet motor body and is used to control the operation of the permanent magnet motor.

[0128] In other embodiments, the present invention further provides an electronic device, comprising: one or more processors and a memory storing one or more computer programs;

[0129] The processor calls the computer program to implement: a speed flux cascade robust control method for a permanent magnet motor system. Specifically:

[0130] Acquire motor parameters of the permanent magnet motor, wherein the motor parameters at least include the current, actual flux linkage, and actual speed of the motor;

[0131] Based on the observation of the composite discrete extended state observer, the actual speed and the actual flux are used to observe the lumped disturbance of the permanent magnet motor operation process to obtain the lumped disturbance, the flux observation value and the speed observation value, wherein the lumped disturbance includes the speed loop lumped disturbance and the flux loop lumped disturbance;

[0132] The dq axis voltage command values ​​are obtained by using the lumped disturbance, flux observation value, speed observation value and the control model of the speed flux cascade model-free predictive controller designed based on the hyperlocal model;

[0133] The αβ phase voltage command value transformed based on the dq axis voltage command value is modulated to generate a motor command for the permanent magnet motor, thereby realizing motor control.

[0134] It should be understood that the electronic device can be understood as an electronic component with a processor and a memory and built into the permanent magnet motor; it can also be understood as an electronic component independent of the permanent magnet motor and communicatively connected to the motor body of the permanent magnet motor.

[0135] In other embodiments, the present invention further provides a computer-readable storage medium storing a computer program, wherein the computer program is called by a processor to implement: a speed flux cascade robust control method for a permanent magnet motor system.

[0136] Specific examples include:

[0137] Acquire motor parameters of the permanent magnet motor, wherein the motor parameters at least include the current, actual flux linkage, and actual speed of the motor;

[0138] Based on the observation of the composite discrete extended state observer, the actual speed and the actual flux are used to observe the lumped disturbance of the permanent magnet motor operation process to obtain the lumped disturbance, the flux observation value and the speed observation value, wherein the lumped disturbance includes the speed loop lumped disturbance and the flux loop lumped disturbance;

[0139] The dq axis voltage command values ​​are obtained by using the lumped disturbance, flux observation value, speed observation value and the control model of the speed flux cascade model-free predictive controller designed based on the hyperlocal model;

[0140] The αβ phase voltage command value transformed based on the dq axis voltage command value is modulated to generate a motor command for the permanent magnet motor, thereby realizing motor control.

[0141] It should be understood that the implementation process of some steps and whether to execute some steps and the execution order can refer to the implementation process of the aforementioned embodiment.

[0142] The readable storage medium is a computer-readable storage medium, which may be an internal storage unit of the controller described in any of the foregoing embodiments, such as a hard disk or memory of the controller. The readable storage medium may also be an external storage device of the controller, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the controller. Further, the readable storage medium may also include both an internal storage unit of the controller and an external storage device. The readable storage medium is used to store the computer program and other programs and data required by the controller. The readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0143] Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned readable storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), disk or optical disk, etc. Various media that can store program codes.

[0144] It should be emphasized that the examples described in the present invention are illustrative rather than restrictive, and therefore the present invention is not limited to the examples described in the specific embodiments. Any other embodiments derived by those skilled in the art based on the technical solution of the present invention that do not depart from the purpose and scope of the present invention, whether modified or replaced, also fall within the scope of protection of the present invention.

Claims

1. A speed flux cascade robust control method for a permanent magnet motor system, characterized by: The following steps are involved: S1: Obtaining motor parameters of the permanent magnet motor, wherein the motor parameters include at least the current, actual flux linkage, and actual speed of the motor; S2； Based on the composite discrete extended state observer, the actual speed and actual flux are used to observe the operation process of the permanent magnet motor to obtain a lumped disturbance, a flux observation value and a speed observation value, wherein the lumped disturbance includes a speed loop lumped disturbance and a flux loop lumped disturbance; S3: Feeding back the lumped disturbance, flux observation value, and speed observation value to a speed flux cascade model-free predictive controller designed based on a super-local model to obtain a q-axis voltage command value, wherein the speed flux cascade model-free predictive controller includes a speed model-free predictive controller and a flux model-free predictive controller connected to each other; The speed loop lumped disturbance and the speed observation value are input into the speed model-free predictive controller to predict the q-axis flux command value; the flux loop lumped disturbance, the flux observation value and the dq-axis flux command value are input into the flux model-free predictive controller to predict the dq-axis voltage command value, and the d-axis flux command value is preset; S4: Inputting the αβ phase voltage command value transformed based on the dq axis voltage command value into the modulation module of the permanent magnet motor to realize motor control.

2. The method according to claim 1, characterized in that: The control model of the speed model-free predictive controller is expressed as: Using the Lagrange interpolation method, we can get: In the formula, are the q-axis flux command values ​​at the k-2, k-1, k, and k+1 moments / sampling points respectively, is the reference speed at time k+1 / sampling point, is the observed speed value at time k+1 / sampling point, is the total disturbance of the speed loop at time k+1 / sampling point, α is the gain of the speed super-local model, T s Indicates the sampling period.

3. The method according to claim 1, characterized in that: The control model of the flux linkage model-free predictive controller is expressed as: In the formula, Indicates the predicted d-axis and q-axis voltage command values ​​at time k / sampling point vector, T is the matrix transpose symbol, Represents the lumped disturbance of the d- and q-axis magnetic flux loops at time k+1 / sampling point The vector of Indicates the observed value of d-axis and q-axis magnetic flux at time k+1 / sampling point The vector of Indicates the d-axis and q-axis flux command values ​​at k+1 time / sampling point The vector of s is the sampling period, and β is the gain of the magnetic flux hyperlocal model.

4. The method according to claim 1, characterized in that: The speed model-free predictive controller and the flux model-free predictive controller are constructed based on reasoning based on establishing a super-local model of speed control and establishing a super-local model of flux control respectively; The hyperlocal model of speed control is expressed as: Where α is the gain of the speed super-local model, d is the speed loop lumped disturbance, ω e is the speed, t is the time; The hyperlocal model of flux linkage control is expressed as: In the formula, ψ s represents the d- and q-axis stator flux ψ d , q The vector, U s is the d and q axis voltage vector, F s is the lumped disturbance vector of the d- and q-axis flux loops, and β is the gain of the flux hyperlocal model.

5. The method according to claim 1, characterized in that: The observation model of the composite discrete extended state observer is expressed as: There exists, the x matrix of k moments / sampling points The actual value of the stator flux of the d and q axes at the k time / sampling point ψ d (k),ψ q (k), actual speed value ω e (k) constitutes; the state matrix observation value of k time / sampling point The d-axis and q-axis stator flux observation values ​​at k time / sampling point Speed ​​observation value Composition; error matrix of k time / sampling point The flux error e at time k / sampling point s (k), speed error e ω (k) constitutes; U at k time / sampling point o matrix The d-axis and q-axis stator voltages u at the k moment / sampling point are d (k),u q (k), q-axis magnetic flux ψ q (k) constitutes; the lumped disturbance matrix of k time / sampling point The speed loop lumped disturbance at k time / sampling point Magnetic flux ring lumped disturbance Composition; Matrix Matrix N = T s I 3×3 ,matrix matrix Where, T s is the sampling time, γ1 and γ2 are both speed loop observer gains; β is the gain of the flux hyperlocal model, α is the gain of the speed hyperlocal model; λ1 and λ2 are the flux loop observer gains, I 3×3 is the third-order identity matrix.

6. The method according to claim 5, characterized in that: The observation model of the composite discrete extended state observer is obtained by discretizing the speed observation model and the flux observation model of the composite discrete extended state observer; Among them, the state input of the speed control system is defined as the q-axis flux and the speed loop lumped disturbance, corresponding to the speed observation model of the composite discrete extended state observer, which is expressed as: The state input of the flux control system is defined as the dq-axis stator voltage and the flux ring lumped disturbance. The flux observation model corresponding to the composite discrete extended state observer is expressed as: In the formula, ω e They are the observed speed value and the actual speed value respectively; ψ s are the observed value of magnetic flux vector and the actual value of magnetic flux vector, respectively. s is the d and q axis voltage vector; is the observed value of the lumped disturbance vector of the d-axis and q-axis flux loops, and β is the gain of the flux hyperlocal model.

7. A control system based on the method according to any one of claims 1 to 6, characterized in that: At least: The composite discrete extended state observer uses the actual speed and actual flux of the permanent magnet motor to observe the operation process of the permanent magnet motor to obtain lumped disturbances, flux observation values ​​and speed observation values, wherein the lumped disturbances include the speed loop lumped disturbances and the flux loop lumped disturbances; A speed model-free predictive controller predicts a q-axis flux command value using the speed loop lumped disturbance and the speed observation value; A flux model-free predictive controller predicts a dq axis voltage command value using the flux loop lumped disturbance, the flux observation value, and a dq axis flux command value, wherein the d axis flux command value is preset; An inverse Park transformation module is used to transform the dq axis voltage command value into the αβ phase voltage command value; The modulation module generates motor commands using the αβ phase voltage command values ​​to achieve motor control.

8. A permanent magnet motor, characterized in that: A control system as claimed in claim 7 is provided, and the control system is connected to the permanent magnet motor body and is used to control the operation of the permanent magnet motor.

9. An electronic device, characterized in that: include: one or more processors; a memory storing one or more computer programs; The processor calls the computer program to implement: Acquire motor parameters of the permanent magnet motor, wherein the motor parameters at least include the current, actual flux linkage, and actual speed of the motor; Based on the observation of the composite discrete extended state observer, the actual speed and the actual flux are used to observe the lumped disturbance of the permanent magnet motor operation process to obtain the lumped disturbance, the flux observation value and the speed observation value, wherein the lumped disturbance includes the speed loop lumped disturbance and the flux loop lumped disturbance; The dq axis voltage command values ​​are obtained by using the lumped disturbance, flux observation value, speed observation value and the control model of the speed flux cascade model-free predictive controller designed based on the hyperlocal model; The αβ phase voltage command value transformed based on the dq axis voltage command value is modulated to generate a motor command for the permanent magnet motor, thereby realizing motor control.

10. A computer-readable storage medium, characterized in that: A computer program is stored, which is called by a processor to implement: Acquire motor parameters of the permanent magnet motor, wherein the motor parameters at least include the current, actual flux linkage, and actual speed of the motor; Based on the observation of the composite discrete extended state observer, the actual speed and the actual flux are used to observe the lumped disturbance of the permanent magnet motor operation process to obtain the lumped disturbance, the flux observation value and the speed observation value, wherein the lumped disturbance includes the speed loop lumped disturbance and the flux loop lumped disturbance; The dq axis voltage command values ​​are obtained by using the lumped disturbance, flux observation value, speed observation value and the control model of the speed flux cascade model-free predictive controller designed based on the hyperlocal model; The αβ phase voltage command value transformed based on the dq axis voltage command value is modulated to generate a motor command for the permanent magnet motor, thereby realizing motor control.

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