Motor current prediction control method and device based on sliding mode observer and storage medium

Abstract

The invention provides a motor current prediction control method and device based on a sliding-mode observer and a storage medium, and relates to the technical field of motor control, and the method comprises the steps: building a first model of a permanent magnet synchronous motor in a d-q rotating coordinate system, and obtaining a current prediction model; a disturbance value in the first model is observed by using a first sliding mode observer; constructing a cost function, and substituting the output values of the current prediction model into the cost function one by one to control the on-off of an inverter power switch; establishing a second model in the alpha-beta static coordinate system to construct a second sliding mode observer; and improving the second sliding-mode observer by using a power reaching law, and introducing fuzzy control into the power reaching law to obtain a third sliding-mode observer. According to the invention, the buffeting phenomenon of the sliding-mode observer is effectively suppressed, the observation precision of the rotating speed of the motor and the position of the rotor is improved, and the stable operation of the permanent magnet synchronous motor can still be ensured under the conditions of parameter mismatch and external load disturbance.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and in particular to a permanent magnet synchronous motor current prediction control method, device and storage medium based on a fuzzy sliding mode observer. Background Art

[0002] Permanent magnet synchronous motors are widely used in high-performance speed regulation systems due to their high torque ratio, high efficiency, high speed, high power density, high reliability and excellent control performance.

[0003] At present, the commonly used motor current predictive control mainly uses back-EMF or stator flux to estimate the speed and position information, such as model reference adaptive method, extended Kalman filter method, sliding mode observer method, least squares method, etc. In contrast, the sliding mode observer method has been more widely used due to its advantages such as simple calculation, good robustness and easy implementation.

[0004] However, the traditional sliding mode observer has its own problems such as jitter phenomenon and slow response speed, which makes the permanent magnet synchronous motor susceptible to internal and external unknown disturbances during operation, resulting in motor parameter mismatch, thus causing a decrease in control performance. Summary of the invention

[0005] The present invention provides a motor current prediction control method, device and storage medium based on a sliding mode observer, which realizes motor current prediction control and sensorless control and solves the problem of severe chattering in the traditional sliding mode observer itself.

[0006] In a first aspect, the present invention provides a motor current predictive control method based on a sliding mode observer, the method comprising:

[0007] A first model of the permanent magnet synchronous motor in the dq rotating coordinate system is established based on the super-local model, and the first model is discretized and compensated in sequence to obtain a current prediction model; wherein a first sliding mode observer is used to observe the d-axis disturbance value and the q-axis disturbance value in the first model;

[0008] Constructing a cost function, substituting the output values ​​of the current prediction model into the cost function one by one, and selecting the inverter switch combination that minimizes the cost function as the output to control the on and off of the inverter power switch;

[0009] Establishing a second model of the permanent magnet synchronous motor in the α-β stationary coordinate system, and constructing a second sliding mode observer based on the second model; taking a continuous saturation function as a switching function, designing the second sliding mode observer using a power reaching law, and introducing fuzzy control into the power reaching law to achieve adaptive adjustment of current, thereby obtaining a third sliding mode observer;

[0010] The motor speed is obtained based on the third sliding mode observer and is fed back to realize sensorless control of the motor.

[0011] Furthermore, a cost function is constructed according to the sum of the absolute value of the difference between the predicted value and the reference value of the d-axis stator current and the absolute value of the difference between the predicted value and the reference value of the q-axis stator current.

[0012] Furthermore, the cost function J is:

[0013]

[0014] in, is the reference value of the d-axis stator current; is the reference value of the q-axis stator current; i d (k+2), i q (k+2) are the predicted values ​​of the stator current of the d-axis and q-axis at time k+2 respectively.

[0015] Furthermore, the first sliding mode observer is:

[0016]

[0017] in, is the estimated value of the d-axis disturbance; is the estimated value of the q-axis disturbance; L s is the stator inductance; u d 、u q are the stator voltages of the d-axis and q-axis respectively; m d 、m q They are the first sliding mode control laws for the d-axis and q-axis respectively;

[0018] The first sliding surface is a nonlinear sliding surface:

[0019]

[0020] The first sliding mode control law is:

[0021]

[0022] in, is the error state equation; c and β are both constants, c>0, β>0; are the estimated values ​​of the stator currents of the d-axis and q-axis, respectively, i d 、i q are the stator currents of the d-axis and q-axis respectively; μ is the terminal sliding mode factor, 0<μ<1; τ and k1 are the gains of the first sliding mode control law; ζ d and qThe initial value of is 0; and They are d and q The derivative of .

[0023] Furthermore, the second sliding mode observer is:

[0024]

[0025] The second sliding surface is:

[0026]

[0027] The second sliding mode control law is:

[0028]

[0029] in, i α 、i β The estimated value of α 、i β are the stator currents of the α-axis and β-axis respectively; R s is the stator resistance; L s is the stator inductance; u a and u β are the stator voltages of the α-axis and β-axis respectively; ν α , ν β E α 、E β The estimated value, E α 、E β are the back electromotive force of the α-axis and the β-axis corresponding to the second model respectively; are the estimated errors of the stator currents of the α-axis and β-axis, k3 represents the gain of the second sliding mode control law.

[0030] Furthermore, the power reaching law is:

[0031]

[0032] Wherein, k4 is the gain of the power reaching law, k4>0; s is the distance between the system moving point and the second sliding surface; is the power reaching law; 0 <m<1。

[0033] Furthermore, the third sliding mode control law of the third sliding mode observer is:

[0034]

[0035] Where k4 is the gain of the power reaching law, k4>0; s α andβ is the second sliding surface; m is the output variable of fuzzy control.

[0036] Furthermore, the calculation formula for the rotation speed and the rotor position based on the third sliding mode observer is:

[0037]

[0038] in, is the speed of the permanent magnet synchronous motor; is the rotor position of the permanent magnet synchronous motor; are the estimated values ​​of the back electromotive force of the α-axis and β-axis corresponding to the second sliding mode observer respectively; ω c is the cutoff frequency of the low-pass filter.

[0039] In a second aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any one of the above methods.

[0040] In a third aspect, the present invention provides a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of any of the above-mentioned methods when executed by a processor.

[0041] In general, the present invention provides a motor current prediction control method, device and storage medium based on a sliding mode observer, which can achieve the following beneficial effects compared with the prior art:

[0042] The present invention constructs a first sliding mode observer with a high-order fast terminal to observe the d-axis disturbance value and the q-axis disturbance value in the first model of the permanent magnet synchronous motor in the dq rotating coordinate system established based on the super local model; the output values ​​of the current prediction model are substituted into the cost function one by one, and the inverter switch combination that minimizes the cost function is selected as the output to control the on and off of the inverter power switch; at the same time, the continuous saturation function is used as the switching function, and the power reaching law is used to design the second sliding mode observer of the permanent magnet synchronous motor in the α-β stationary coordinate system, and fuzzy control is introduced into the power reaching law to obtain an improved third sliding mode observer; based on the third sliding mode observer, the motor speed is obtained and fed back to realize the sensorless control of the motor, the chattering phenomenon of the sliding mode observer is effectively suppressed, the harmonic content in the estimated back electromotive force corresponding to the third sliding mode observer is reduced, and the observation accuracy of the motor speed and the rotor position is improved, so that the stable operation of the permanent magnet synchronous motor can still be guaranteed under the conditions of parameter mismatch and external load disturbance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a schematic diagram of the method steps of a motor current prediction control method based on a sliding mode observer provided by the present invention;

[0045] Figure 2 It is a schematic diagram of the control method principle of a motor current prediction control method based on a sliding mode observer provided by the present invention;

[0046] Figure 3 It is a schematic diagram of the principle of a first sliding mode observer of a motor current predictive control method based on a sliding mode observer provided by the present invention;

[0047] Figure 4 It is a schematic diagram of the spatial distribution of the voltage vector of a motor current prediction control method based on a sliding mode observer provided by the present invention;

[0048] Figure 5 It is a fuzzy rule schematic diagram of a motor current prediction control method based on a sliding mode observer provided by the present invention;

[0049] Figure 6 is an input variable of a motor current prediction control method based on a sliding mode observer provided by the present invention. Schematic diagram of membership function;

[0050] Figure 7 It is a schematic diagram of a membership function of an output variable m of a motor current prediction control method based on a sliding mode observer provided by the present invention;

[0051] Figure 8 is an input variable s of a motor current prediction control method based on a sliding mode observer provided by the present invention, Schematic diagram of the mapping relationship with the output variable m;

[0052] Fig. 9 It is a schematic diagram of the principle of a third sliding mode observer of a motor current predictive control method based on a sliding mode observer provided by the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings and embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0054] It should be noted that, in the description of the embodiments of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a method, step or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such method, step or device. In the absence of further restrictions, the elements defined by the sentence "include a ..." do not exclude the existence of other identical elements in the method, step or device including the elements.

[0055] like Figures 1-2 As shown, a motor current prediction control method based on a sliding mode observer is provided. On the one hand, a first model of a permanent magnet synchronous motor in a dq rotating coordinate system is established, and a first sliding mode observer with a high-order fast terminal is designed to estimate the unknown part in the first model and compensate for the delay of the permanent magnet synchronous motor system to obtain a current prediction model; on the other hand, the second sliding mode observer of the permanent magnet synchronous motor constructed in the α-β stationary coordinate system is improved based on the power reaching law, and fuzzy control is introduced into the power reaching law to obtain an improved third sliding mode observer; finally, the motor current is controlled through the current prediction model and the third sliding mode observer and the cost function is used to suppress jitter, realize accurate observation of the speed and the rotor position, and realize stable operation of the motor under the conditions of parameter mismatch and external load disturbance.

[0056] Specifically, if Figure 1 As shown, the method includes:

[0057] S100: establishing a first model of the permanent magnet synchronous motor in a dq rotating coordinate system based on the super-local model, and performing discretization processing and compensation processing on the first model in sequence to obtain a current prediction model.

[0058] As an example, the first model may be:

[0059]

[0060] Where: α is the scale factor, F d is the d-axis disturbance value, F q is the q-axis disturbance value,

[0061] More specifically, the establishment of the first model includes:

[0062] S1011: Obtaining a first state equation of the motor stator current according to a mathematical model of the permanent magnet synchronous motor in a dq rotating coordinate system;

[0063] It should be noted that the mathematical model of the permanent magnet synchronous motor in the dq rotating coordinate system can be:

[0064]

[0065] Where: i d 、i q are the stator currents of the d-axis and q-axis respectively; u d 、u q are the stator voltages of the d-axis and q-axis respectively; L s is the stator inductance; R s is the stator resistance; ω e is the electrical angular velocity; ψ f is the permanent magnet flux.

[0066] The first state equation of the motor stator current can be:

[0067]

[0068] Where: i d 、i q are the stator currents of the d-axis and q-axis respectively; u d 、u q are the stator voltages of the d-axis and q-axis respectively; L s is the stator inductance; R s is the stator resistance; ω e is the electrical angular velocity; ψ f is the permanent magnet flux.

[0069] S1012: Establishing a first model of the permanent magnet synchronous motor based on a super local model according to the input and output of the permanent magnet synchronous motor system.

[0070] Since the hyperlocal model does not require the current of the permanent magnet synchronous motor, the first model can be established only by relying on the input and output of the permanent magnet synchronous motor system, which can greatly reduce the dependence of the permanent magnet synchronous motor system on high-precision models.

[0071] The first-order hyperlocal model of a single-input single-output system can be expressed as: Among them, y and u are the output and input of the permanent magnet synchronous motor system respectively, α is the proportional factor; F is the sum of known and unknown disturbances of the permanent magnet synchronous motor system.

[0072] The disturbances of the d-axis and q-axis in the first state equation of the motor stator current are set as corresponding variables respectively, thereby obtaining a first model; thus, the d-axis disturbance value and the q-axis disturbance value in the first model can be observed using a first sliding mode observer.

[0073] Increasing the proportional factor can speed up the response but will also cause overshoot, so the proportional factor needs to be adjusted to balance the response speed and overshoot.

[0074] It should be noted that the d-axis disturbance value and the q-axis disturbance value in the first model may be observed by using the first sliding mode observer.

[0075] like Figure 3 As shown, the first sliding mode observer is a high-order fast terminal sliding mode observer, which is used to observe the d-axis disturbance value and the q-axis disturbance value in the first model.

[0076] As an embodiment, the first sliding mode observer may be:

[0077]

[0078] in, is the estimated value of the d-axis disturbance; is the estimated value of the q-axis disturbance; L s is the stator inductance; u d 、u q are the stator voltages of the d-axis and q-axis respectively; m d 、m q are the first sliding mode control laws for the d-axis and q-axis respectively; the superscript ^ indicates that the item is an estimated value.

[0079] In order to improve the accuracy and convergence speed of motor current control, the first sliding surface is preferably a nonlinear sliding surface, which can be specifically designed as follows:

[0080]

[0081] Furthermore, the first sliding mode control law can be designed as:

[0082]

[0083] in, is the error state equation; c and β are both constants, c>0, β>0; are the estimated values ​​of the stator currents of the d-axis and q-axis, respectively, i d 、i q are the stator currents of the d-axis and q-axis respectively; μ is the terminal sliding mode factor, 0<μ<1; τ and k1 are the gains of the first sliding mode control law; ζ dand q The initial value of is 0; and They are d and q The derivative of d (0) = ζ q (0) = 0. It should be noted that the performance of the first sliding mode observer can be guaranteed by setting the values ​​of τ and k1.

[0084] More specifically, the first error state equation for:

[0085]

[0086] in, is the estimated value of the d-axis disturbance; is the estimated value of the q-axis disturbance; F d is the d-axis disturbance value; F q is the q-axis disturbance value; m s 、m q They are the first sliding mode control laws for the d-axis and q-axis respectively.

[0087] The derivative of the total disturbance can be:

[0088]

[0089] Where k2 is the disturbance gain; s d and q is the first sliding surface.

[0090] It should be noted that the stability of the first sliding mode observer is analyzed using Lyapunov's theorem.

[0091] As an embodiment, the stability condition of the first sliding mode observer is:

[0092]

[0093] Among them, τ and k1 are the gains of the first sliding mode control law, ζ d and q The initial value of is 0. k2 is the disturbance gain; s d and q is the first sliding surface; is the derivative of the d-axis disturbance value; is the derivative of the q-axis disturbance value; σ is a very small number,

[0094] Only when the stability condition of the first sliding mode observer is met, the first sliding mode observer is stable, and the permanent magnet synchronous motor system can reach the sliding mode surface in a finite time at any initial state and run stably on the sliding mode surface.

[0095] More specifically, the stability analysis process includes:

[0096] S1021: Derivative the Lyapunov function to obtain the first derivative equation

[0097] Among them, the Lyapunov function is:

[0098]

[0099] S1022: Substitute the first sliding mode control law and the first error state equation into the first sliding surface to obtain a first equation, and differentiate the first equation to obtain a first derivative equation.

[0100] The first equation is:

[0101] Taking the derivative of s, we get the first derivative equation:

[0102]

[0103] S1023: Based on the first derivative equation and the first derivative equation, a second derivative equation is obtained.

[0104] Among them, the second derivative equation is:

[0105]

[0106] S1024: The second derivative equation is less than zero, and the stability condition of the first sliding mode observer is obtained. That is:

[0107] The first model is sequentially subjected to discretization processing and compensation processing to obtain a current prediction model.

[0108] It should be noted that the discretization process may be: discretizing the first model using the forward Euler discretization method to obtain the predicted current equation of the permanent magnet synchronous motor. The purpose of the discretization process is to transform the continuous time model into a discrete time model.

[0109] As an embodiment, the predicted current equation of the permanent magnet synchronous motor may be:

[0110]

[0111] Where: i d (k+1) and i q(k+1) are the predicted values ​​of the stator current of the d-axis and q-axis at time k+1 respectively; and F d and F q The estimated value at time k; T s is the sampling time; u d (k) and u q (k) is the voltage value at time k; i d (k) and i q (k) is the current value at time k.

[0112] Since there is an operation delay in the digital control system, in order to eliminate the operation delay, the present invention adopts a two-step method to compensate the permanent magnet synchronous motor system, and then obtains a current prediction model.

[0113] As an embodiment, the current prediction model is a prediction current equation at time k+2, specifically:

[0114]

[0115] Among them, i d (k+2) and i q (k+2) are the predicted values ​​of the stator current of the d-axis and q-axis at time k+2 respectively; and F d and F q The estimated value at time k+1; T s is the sampling time; u d (k+1) and u q (k+1) is the voltage value at time k+1; i d (k+1) and i q (k+1) is the current value at time k+1.

[0116] S200: constructing a cost function, inputting the output values ​​of the current prediction model into the cost function one by one, and selecting the inverter switch combination that minimizes the cost function as the output to control the on and off of the inverter power switch.

[0117] Since the current prediction control target is to make the d-axis and q-axis currents of the permanent magnet synchronous motor follow their given reference values, the present invention constructs a cost function based on the sum of the absolute value of the difference between the predicted value and the reference value of the d-axis stator current and the absolute value of the difference between the predicted value and the reference value of the q-axis stator current.

[0118] As a specific embodiment, the cost function J is:

[0119]

[0120] in, is the reference value of the d-axis stator current; is the reference value of the q-axis stator current; i d (k+2), i q (k+2) are the predicted values ​​of the stator current of the d-axis and q-axis at time k+2 respectively.

[0121] The proposed finite control set The control set of the model-free predictive current control is finite. For the two-level three-phase voltage source inverter, the applied control set consists of 6 non-zero vectors and 2 zero vectors.

[0122] As a specific embodiment, the current is predicted respectively by the prediction equation of the stator current according to the eight basic voltage vectors, the predicted values ​​of the current are substituted into the cost function one by one, and the inverter switch state combination that minimizes the cost function is selected as the output by enumeration method to control the on and off of the inverter power switch.

[0123] It should be noted that the current prediction model can also be updated according to the spatial distribution of the voltage vector output by the cost function; the first model and the first sliding mode observer can be updated in real time according to the voltage at the current moment output by the cost function to make the prediction and control of the motor current more accurate.

[0124] like Figure 4 As shown in the figure, it is a schematic diagram of the spatial distribution of the voltage vector. When the optimal output voltage vector is the zero vector, whether the output is u0 (000) or u7 (111) depends on the switch state at the previous moment. Frequent switching of the inverter switch state will greatly reduce the service life of electronic devices. Therefore, the zero vector is selected based on the principle of the minimum number of inverter switch state switching. For example, assuming that the previous inverter switch state is (110), then the optimal zero vector output at the current moment is u7 (111).

[0125] S300: Establish a second model of the permanent magnet synchronous motor in the α-β stationary coordinate system, and construct a second sliding mode observer based on the second model; use the continuous saturation function as the switching function, use the power reaching law to design the second sliding mode observer, and introduce fuzzy control into the power reaching law to achieve adaptive adjustment of the current, so as to obtain a third sliding mode observer.

[0126] As an example, the second model may be:

[0127]

[0128] The back EMF corresponding to the second model is:

[0129]

[0130] Among them, u α and u βare the stator voltages of the α-axis and β-axis respectively; i d 、i q are the stator currents of the d-axis and q-axis respectively; R s is the stator resistance; L s is the stator inductance; ω e is the electrical angular velocity; ψ f is the permanent magnet flux; θ e is the electrical angle of the rotor.

[0131] It should be noted that constructing the second sliding mode observer based on the second model includes: rewriting the stator voltage equation into a second state equation of the stator current, and obtaining the second sliding mode observer based on the second state equation.

[0132] More specifically, the second state equation can be:

[0133]

[0134] As an embodiment, the second sliding mode observer may be:

[0135]

[0136] The second sliding surface is:

[0137]

[0138] The second sliding mode control law is:

[0139]

[0140] in, i α 、i β The estimated value of α 、i β are the stator currents of the α-axis and β-axis respectively; R s is the stator resistance; L s is the stator inductance; u α and u β are the stator voltages of the α-axis and β-axis respectively; v α 、v β E α 、E β The estimated value, E α 、E β are the back electromotive force of the α-axis and the β-axis corresponding to the second model respectively; are the estimated errors of the stator currents of the α-axis and β-axis, k3 represents the gain of the second sliding mode control law.

[0141] More specifically, the estimated error of the stator current may be obtained by subtracting the second sliding mode observer from the second state equation.

[0142] As an embodiment, the estimated error equation of the stator current is:

[0143]

[0144] in, are the estimated errors of the stator currents of the α-axis and β-axis, i α 、i β The estimated value of α 、i β are the stator currents of the α-axis and β-axis respectively; R s is the stator resistance; L s is the stator inductance; E α 、E β are the back electromotive force of the α-axis and β-axis corresponding to the second model respectively; v α 、v β E α 、E β The estimated value of .

[0145] When the state variable of the second sliding mode observer reaches the second sliding mode surface, it will make high-frequency, small-amplitude reciprocating motion along the preset second sliding mode surface until the motion reaches the equilibrium state of the permanent magnet synchronous motor system. When the equilibrium state of the permanent magnet synchronous motor system is reached, Then, the back electromotive force corresponding to the second sliding mode observer can be obtained according to the equivalent control principle of sliding mode control.

[0146] Specifically, the back electromotive force corresponding to the second sliding mode observer is:

[0147]

[0148] Among them, v α 、v β E α 、E β Estimated value of α 、E β are the back electromotive force of the α-axis and β-axis corresponding to the second model respectively; k3 represents the gain of the second sliding mode control law; are the estimated errors of the stator currents of the α-axis and β-axis respectively.

[0149] In order to improve the observation performance of the second sliding mode observer, the present invention uses a continuous saturation function instead of a sign function as a switching function, and uses a power reaching law to improve the second sliding mode observer, so that the permanent magnet synchronous motor system state has a desired reaching characteristic.

[0150] The continuous saturation function can be:

[0151]

[0152] Wherein, Δ is the thickness of the boundary layer. Continuous control is adopted within the boundary layer, and switching control is adopted outside the boundary layer.

[0153] The power reaching law is:

[0154]

[0155] Wherein, k4 is the gain of the power reaching law, k4>0; s is the distance between the system moving point and the second sliding surface; is the power reaching law; 0 <m<1。

[0156] In order to effectively suppress chattering and improve the observation performance of the second sliding mode observer, the present invention further establishes fuzzy rules and utilizes fuzzy control to adaptively adjust the output variables in the power reaching law.

[0157] The boundary layer thickness s and the power reaching law As the input variable of fuzzy control, m is taken as the output variable of fuzzy control.

[0158] When the moving point of the permanent magnet synchronous motor system is far away from the second sliding surface, that is, when s is large, the value of m should be increased to increase the approach speed. On the contrary, when the moving point of the permanent magnet synchronous motor system is close to the second sliding surface, that is, when s is small, the value of m should be reduced to suppress chattering. In order to make the fuzzy rule have a certain degree of advance, when When increases, the value of m should be increased. When it decreases, the value of m should be reduced.

[0159] As an example, Figure 5 As shown, for the input variables s and The fuzzy rules used are: {NB, NM, NS, ZO, PS, PM, PB} for fuzzification. The fuzzy rules used for the output variable m are: {ZO, PS, PM, PB}. Among them: N = Negative, B = Big, M = Middle, S = Small, ZO = Zero, P = Positive. Thus, we get Figure 6 The membership function of the input variables shown in Figure 7 The membership function of the output variable shown in Figure 8The mapping relationship between input variables and output variables is shown.

[0160] The sharper the shape of the membership function curve, the higher the sensitivity of the control, the more radical the control strategy, and it is suitable for systems with insignificant parameter changes; the flatter the membership function curve changes, the lower the sensitivity of the control, the more conservative the control adjustment, and it is suitable for systems with large parameter changes. The membership function of the parameters of the present invention can be: normal function, triangular function, trapezoidal function, etc.

[0161] However, since the variation range of parameters in the second sliding mode observer proposed in the present invention is relatively obvious, for the consideration of control sensitivity and stability, the membership functions of all parameters in the present invention are preferably normal functions.

[0162] In addition, the fuzzy reasoning methods used in the present invention include Mamdani method and TS method. Based on the consideration of calculation accuracy and calculation amount, Mamdani method is preferably used as the fuzzy reasoning method.

[0163] It should be noted that when the Mamdani method is used as the fuzzy inference method, its output is a fuzzy subset. Therefore, defuzzification processing is required to obtain the output variables used to control the controlled object.

[0164] The defuzzification methods include maximum membership method, median method, centroid method, etc. The present invention preferably uses the centroid method to defuzzify the output variables.

[0165] The expression of the centroid method is: u0 is the exact output before scaling; n is the number of elements in the output fuzzy set; x i is the i-th element in the fuzzy set; μ i For x i The corresponding membership degree.

[0166] It should be noted that the expression of the third sliding mode observer obtained by improving the second sliding mode observer is the same as that of the second sliding mode observer.

[0167] like Fig. 9 As shown, the third sliding mode observer is:

[0168]

[0169] The third sliding surface is:

[0170]

[0171] As an embodiment of the present invention, the third sliding mode control law of the third sliding mode observer is:

[0172]

[0173] Where k4 is the gain of the power reaching law, k4>0; s α and β is the second sliding surface; m is the output variable of fuzzy control.

[0174] The back electromotive force corresponding to the third sliding mode observer is:

[0175]

[0176] Among them, ν α , ν β E α 、E β The estimated value, E α 、E β are the back electromotive force of the α-axis and β-axis corresponding to the second model respectively; k4 is the gain of the power approaching law, k4>0; s α and β is the second sliding surface; m is the output variable of fuzzy control.

[0177] It should be noted that the stability of the third sliding mode observer is analyzed using Lyapunov's theorem.

[0178] As an embodiment, the stability condition of the third sliding mode observer is:

[0179]

[0180] Among them, E α 、E β are the back electromotive force of the α-axis and β-axis corresponding to the third model respectively; are the estimated errors of the stator current of the α-axis and β-axis respectively; m is the output variable of the fuzzy control.

[0181] The third sliding mode observer is stable only when its stability condition is met.

[0182] It should be noted that the stability analysis process of the third sliding mode observer is the same as the stability analysis process of the first sliding mode observer, and specifically includes:

[0183] First, the Lyapunov function is differentiated to obtain the derivative equation

[0184] Then based on the derivative equation we can get:

[0185]

[0186] Because when , the third sliding mode observer is stable, so the stability of the third observer must satisfy:

[0187]

[0188] Finally, the stability of the third observer satisfies The stability condition of the third sliding mode observer can be obtained.

[0189] Since using a low-pass filter to filter the back electromotive force signal corresponding to the third sliding mode observation will cause phase delay, the present invention performs angle compensation when using the arc tangent function to obtain the rotor position.

[0190] As an embodiment, the calculation formula for the rotation speed and the rotor position based on the third sliding mode observer is:

[0191]

[0192] in, is the speed of the permanent magnet synchronous motor; is the rotor position of the permanent magnet synchronous motor; are the estimated values ​​of the back electromotive force of the α-axis and β-axis corresponding to the second sliding mode observer respectively; ω c is the cutoff frequency of the low-pass filter.

[0193] S400: Obtaining the motor speed based on the third sliding mode observer and providing feedback to achieve sensorless control of the motor.

[0194] For example, Figure 2 As shown, the output value of the third sliding mode observer is the motor speed n, then according to the motor speed reference value n * , then the motor speed n and the motor speed reference value n * The difference is input into the speed regulator to obtain the reference value of the q-axis stator current Get the reference value of the d-axis stator current Finally, according to the reference values ​​of the q-axis and d-axis stator currents And the cost function is updated according to the predicted value of the stator current at time k+2 output by the current prediction model to realize the current prediction control of the motor.

[0195] In a second aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any one of the above methods. The technical features of the computer device are consistent with the technical features of the above method, and are not described one by one here.

[0196] In a third aspect, the present invention provides a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of any of the above methods when the computer program / instruction is executed by a processor. The technical features of the computer-readable storage medium are consistent with the technical features of the above method, and are not described one by one here.

[0197] In summary, the present invention effectively suppresses the jitter phenomenon of the sliding mode observer, reduces the harmonic content in the estimated back electromotive force corresponding to the third sliding mode observer, and improves the observation accuracy of the motor speed and rotor position, so that the stable operation of the permanent magnet synchronous motor can still be guaranteed under the conditions of parameter mismatch and external load disturbance.

[0198] It should be noted that, for the above-mentioned various embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0199] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0200] In the several embodiments provided in this application, it should be understood that the disclosed method or system can be implemented in other ways. For example, the above-described embodiments are only schematic, and the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0201] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0202] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0203] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application 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 memory and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0204] A person skilled in the art can understand that all or part of the various circuits in the above-mentioned embodiments can be completed by entering a program to instruct related hardware. The program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0205] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of the implementation scheme of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

[0206] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0207] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A motor current predictive control method based on a sliding mode observer, characterized in that: The method comprises: A first model of the permanent magnet synchronous motor in the dq rotating coordinate system is established based on the super-local model, and the first model is discretized and compensated in sequence to obtain a current prediction model; wherein a first sliding mode observer is used to observe the d-axis disturbance value and the q-axis disturbance value in the first model; Constructing a cost function, substituting the output values ​​of the current prediction model into the cost function one by one, and selecting the inverter switch combination that minimizes the cost function as the output to control the on and off of the inverter power switch; Establishing a second model of the permanent magnet synchronous motor in the α-β stationary coordinate system, and constructing a second sliding mode observer based on the second model; taking a continuous saturation function as a switching function, designing the second sliding mode observer using a power reaching law, and introducing fuzzy control into the power reaching law to achieve adaptive adjustment of current, thereby obtaining a third sliding mode observer; The motor speed is obtained based on the third sliding mode observer and is fed back to realize sensorless control of the motor.

2. The motor current prediction control method based on sliding mode observer according to claim 1, characterized in that: The cost function is constructed according to the sum of the absolute value of the difference between the predicted value and the reference value of the d-axis stator current and the absolute value of the difference between the predicted value and the reference value of the q-axis stator current.

3. The motor current prediction control method based on sliding mode observer according to claim 2, characterized in that: The cost function J is: in, is the reference value of the d-axis stator current; is the reference value of the q-axis stator current; i d (k+2), i q (k+2) are the predicted values ​​of the stator current of the d-axis and q-axis at time k+2 respectively.

4. The motor current prediction control method based on sliding mode observer according to claim 1, characterized in that: The first sliding mode observer is: in, is the estimated value of the d-axis disturbance; is the estimated value of the q-axis disturbance; L s is the stator inductance; u d 、u q are the stator voltages of the d-axis and q-axis respectively; m d 、m q are the first sliding mode control laws for the d-axis and q-axis respectively; The first sliding surface is a nonlinear sliding surface: The first sliding mode control law is: in, is the error state equation; c and β are both constants, c>0, β>0; are the estimated values ​​of the stator currents of the d-axis and q-axis, respectively, i d 、i q are the stator currents of the d-axis and q-axis respectively; μ is the terminal sliding mode factor, τ and k1 are the gains of the first sliding mode control law; ζ d and q The initial value of is 0; and They are d and q The derivative of .

5. The motor current prediction control method based on sliding mode observer according to claim 1, characterized in that: The second sliding mode observer is: The second sliding surface is: The second sliding mode control law is: in, i α 、i β The estimated value of α 、i β are the stator currents of the α-axis and β-axis respectively; R s is the stator resistance; L s is the stator inductance; u α and u β are the stator voltages of the α-axis and β-axis respectively; v α 、v β E α 、E β The estimated value, E α 、E β are the back electromotive force of the α-axis and the β-axis corresponding to the second model respectively; are the estimated errors of the stator currents of the α-axis and β-axis, k3 represents the gain of the second sliding mode control law.

6. The motor current prediction control method based on sliding mode observer according to claim 5, characterized in that: The power reaching law is: Wherein, k4 is the gain of the power reaching law, k4>0; s is the distance between the system moving point and the second sliding surface; is the power reaching law; 0 <m<1。 7. The motor current prediction control method based on sliding mode observer according to claim 6, characterized in that: The third sliding mode control law of the third sliding mode observer is: Where k4 is the gain of the power reaching law, k4>0; s α and β is the second sliding surface; m is the output variable of fuzzy control.

8. The motor current prediction control method based on sliding mode observer according to claim 6, characterized in that: The calculation formula for the speed and rotor position based on the third sliding mode observer is: in, is the speed of the permanent magnet synchronous motor; is the rotor position of the permanent magnet synchronous motor; are the estimated values ​​of the back electromotive force of the α-axis and β-axis corresponding to the second sliding mode observer respectively; ω c is the cutoff frequency of the low-pass filter.

9. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

Images