Permanent magnet synchronous motor driving system control method, device and system

Abstract

The invention discloses a permanent magnet synchronous motor driving system control method, device and system, and belongs to the field of motor control. According to the technical scheme, the method comprises the steps that firstly, an observer is adopted to estimate and compensate disturbance low-frequency components, and the disturbance upper bound acting on a system is effectively reduced; and secondly, a fuzzy system is constructed by using the change rate of the speed error and the estimated value of the disturbance high-frequency component, and an adjustable switching gain is generated by combining the estimated value of the disturbance high-frequency component, so that a large-amplitude action instantaneously caused by a sudden-change disturbance effect is suppressed in time, and meanwhile, small-amplitude buffeting dynamic operation of the system after disturbance disappears is considered. Compared with a traditional anti-interference controller, the control method has higher robustness and higher dynamic response speed.

Description

Technical Field

[0001] The present invention relates to a system control and anti-interference method for adjusting the switching gain of a sliding mode controller by using multi-source information, and belongs to the field of motor control. Background Art

[0002] Permanent magnet synchronous motors have the advantages of high efficiency, high power density, high torque inertia ratio, low noise, and easy maintenance, and are widely used in fields such as robots, automobiles, machine tools, and aerospace. However, when operating under different working conditions, permanent magnet synchronous motors are affected by various internal disturbances (parameter changes and unmodeled dynamics) and external disturbances (load torque changes). Especially when subjected to sudden disturbance actions, the high-performance servo control of permanent magnet synchronous motors faces major challenges.

[0003] When subjected to external disturbances, torque fluctuations will occur in the permanent magnet synchronous motor drive system, resulting in reduced control accuracy of position and speed. In the research on anti-interference control of permanent magnet synchronous motors, non-linear control methods such as fuzzy control, robust control, sliding mode control, predictive control, and intelligent control have emerged. Sliding mode control has received extensive attention from academia and industry due to its strong robustness. The control quantity output by the traditional sliding mode controller contains a switching term, and the discontinuous control signal will cause chattering problems. If a large switching gain is selected to completely suppress the disturbance, the chattering phenomenon becomes more serious. Therefore, how to balance the system's anti-disturbance ability and reduce the chattering amplitude is an urgent problem to be solved when the sliding mode control method is applied to the permanent magnet synchronous motor drive system. Many scholars have done a lot of exploratory work in this field and given some innovative solutions. The existing research methods can be mainly classified into three categories:

[0004] 1) The first category is to suppress the disturbance by using a large switching gain, that is, the control action is always greater than or equal to the disturbance term. This method also includes two schemes: one is to fix the large switching gain, and the other is to dynamically vary the switching gain. In order to achieve complete suppression of the disturbance, generally the upper bound of the disturbance is used as the switching gain of the sliding mode controller, but it is often difficult to obtain the prior upper bound of the disturbance. Some scholars have proposed a new type of integral sliding mode surface and used an adaptive algorithm to estimate the upper bound of the disturbance of the permanent magnet synchronous motor drive system, solving the problem of setting the switching gain of the sliding mode controller. In order to suppress randomly varying disturbances, the fixed switching gain can be changed to a variable switching gain, and a recursive fuzzy neural network is used to estimate the upper bound of the real-time disturbance to realize the online adjustment of the switching gain of the sliding mode controller. However, when the system is subjected to large disturbances, this type of method requires a large switching gain to suppress the disturbance, and the drastic change of the switching gain will cause strong chattering.

[0005] 2) To reduce chattering, the second type of method introduces an observer to estimate the disturbance and perform feedforward compensation, reducing the upper bound of the disturbance that the sliding mode controller needs to suppress. In this case, the switching gain of the sliding mode controller only needs to be greater than the upper bound of the disturbance estimation error, thus significantly reducing the magnitude of the constant switching gain. Some scholars have proposed a non - linear disturbance observer to estimate the mismatched disturbance. After feedforward compensating the disturbance estimation value, effective suppression of the disturbance can be achieved under a smaller switching gain, and the chattering effect is alleviated. Treating internal and external disturbances equally and assuming that their derivatives with respect to time are bounded, an extended state observer can be used to estimate the lumped disturbance and perform feedforward compensation, which can also reduce the set value of the switching gain of the sliding mode controller. This type of method has a certain effect in suppressing disturbances and reducing chattering. However, when the system is subjected to sudden disturbances, due to the bandwidth limitation of the observer and the constraint of the system iteration calculation speed, there will always be a large disturbance estimation error in the disturbance observation, and the disturbance cannot be compensated in a timely and effective manner. The small fixed switching gain of the sliding mode controller set for the system is not sufficient to suppress the disturbance effect, resulting in poor dynamic performance of the system.

[0006] 3) To further reduce chattering and be able to quickly suppress interference, on the basis of feedforward compensation of the disturbance estimation value, the sliding mode controller is adjusted to have a variable switching gain that takes into account the time - variability of the disturbance. To reduce chattering in the steady - state condition, an adaptive variable switching gain of the sliding mode controller can be constructed using the speed error, and combined with a load torque observer to compensate for the disturbance, improving the system response speed and suppressing the chattering phenomenon. A fuzzy sliding - mode speed control method with a load torque observer estimates and feedforward compensates for the load disturbance, uses the speed error as the input of the fuzzy system, and the output of the fuzzy system as the switching gain of the sliding mode controller, improving the chattering suppression effect. In addition to generating the switching gain using the speed error, the size of the variable switching gain can also be determined according to the external disturbance information. The disturbance is divided into high - frequency components and low - frequency components. The low - frequency disturbance is directly estimated and compensated, and the high - frequency disturbance estimation value is directly used as the switching gain of the sliding mode controller, which can achieve the effect of dynamically adjusting the switching gain with the high - frequency disturbance, thus weakening the chattering phenomenon to a certain extent. However, the variable switching gain of this type of method strictly depends on the speed and accuracy of high - frequency disturbance estimation. Especially under the action of sudden disturbances, because the high - frequency disturbance cannot be reflected in the switching gain in a timely manner or there is a numerical mismatch, it is difficult to suppress the disturbance in a timely manner. Summary of the Invention

[0007] The technical problem to be solved by the present invention is: to provide a system control and anti-interference method for adjusting the switching gain of a sliding mode controller using multi-source information. An observer is used to estimate and compensate the low-frequency component of the disturbance, effectively reducing the upper bound of the disturbance acting on the system; a fuzzy system is constructed using the change rates of both the speed error and the estimated value of the high-frequency component of the disturbance, and then, combined with the estimated value of the high-frequency component of the disturbance, an adjustable switching gain is generated to ensure that the large-amplitude actions caused instantaneously by the sudden disturbance are promptly suppressed, while taking into account the small-amplitude chattering dynamic operation of the system after the disturbance disappears. The control method of the present invention has stronger robustness and faster dynamic response speed compared with the traditional anti-interference control methods.

[0008] The present invention adopts the following technical solutions to solve the above technical problems:

[0009] The present invention first proposes a control method for a permanent magnet synchronous motor drive system, including the steps of:

[0010] S1. Divide the lumped disturbance acting on the permanent magnet synchronous motor into high-frequency and low-frequency components, establish a first-order dynamic model of the permanent magnet synchronous motor, and build a second-order extended state observer to obtain the estimated value of the high-frequency component in the lumped disturbance;

[0011] S2. Use a low-frequency disturbance compensator to obtain the estimated value of the low-frequency component in the lumped disturbance; for the changes in the estimated value of the high-frequency component of the disturbance and the speed error, design a fuzzy system to output an additional gain, which is used to compensate for the estimation error existing in the extended state observer at the initial moment of the disturbance action;

[0012] S3. Design a system controller according to the estimated value of the high-frequency component of the disturbance, the estimated value of the low-frequency component of the disturbance, and the additional gain output by the fuzzy system, directly feed forward and compensate the estimated value of the low-frequency component of the disturbance, and use the estimated value of the high-frequency component of the disturbance and the output of the fuzzy system together as the adjustable switching gain of the sliding mode controller. Specifically, when the system is subjected to a sudden disturbance, the estimated value of the high-frequency component of the disturbance and the output of the fuzzy system rapidly increase to suppress the disturbance; when the disturbance is a slow time-varying disturbance, the estimated value of the high-frequency component of the disturbance and the output of the fuzzy system decrease to near zero, thereby reducing the chattering of the system in the steady state.

[0013] As a preferred solution of the method of the present invention, the system controller is designed as:

[0014]

[0015] where, u(t) is the output signal of the system controller, and this signal is the magnitude of the q-axis reference current, s(t) is the sliding mode variable, s(t)=ω(t)-ω * (t), ω(t) is the mechanical angular velocity of the motor, ω * (t) is the angular velocity reference value, x1(t)=ω(t), is the estimated value of the high-frequency disturbance, is the estimated value of the low-frequency disturbance, d f (t) is the additional gain output by the fuzzy system, k1 is an adjustable correction coefficient, a is the system parameter, sat(·) is the saturation function, and the function sat(·) is:

[0016]

[0017] where c1, c2 ∈ R.

[0018] On the other hand, the present invention also provides a control device for a permanent magnet synchronous motor drive system, including:

[0019] A low-frequency disturbance compensator for obtaining an estimated value of the low-frequency component in the lumped disturbance;

[0020] A second-order extended state observer for obtaining an estimated value of the high-frequency component in the lumped disturbance;

[0021] An adjustable switching gain module, which designs an additional gain for the fuzzy system output according to the changes in the estimated high-frequency component of the disturbance and the speed error; forms the adjustable switching gain of the sliding mode controller by combining the estimated high-frequency component of the disturbance and the additional switching gain output by the fuzzy system;

[0022] A system controller for directly feed-forward compensating the estimated low-frequency disturbance; when the system is subjected to a sudden disturbance, controlling the estimated high-frequency component of the disturbance and the fuzzy system output to rapidly increase to suppress the disturbance; when the disturbance is a slow time-varying disturbance, controlling the estimated high-frequency component of the disturbance and the fuzzy system output to decrease to near zero, thereby reducing the steady-state chattering of the system.

[0023] Taking the controller output signal as the given value of the q-axis current loop and combining with the current loop controller to achieve the speed control of the permanent magnet synchronous motor.

[0024] The present invention also provides an electronic system, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method steps of the present invention.

[0025] Finally, the present invention also provides a computer-readable storage medium storing computer instructions, and the computer instructions are used to cause the computer to execute the steps of the method of the present invention.

[0026] Compared with the prior art, the present invention adopts the above technical solutions and has the following technical effects:

[0027] 1. The present invention provides a new control method for a permanent magnet synchronous motor drive system. By simultaneously utilizing key features such as the internal state information of the motor, external environment information, and their rates of change, the switching gain of the sliding mode controller is constructed, achieving timely and rapid suppression of sudden external disturbances.

[0028] 2. The control method provided by the present invention designs an adjustable switching gain of the sliding mode controller using the estimated value of the high-frequency component of the disturbance and the output of the fuzzy system. The system has less chattering in the steady state and reduces the influence of the disturbance estimation error on the system to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is the structural block diagram of the control method proposed by the present invention.

[0030] Figure 2 are the membership functions of the input and output of the fuzzy system.

[0031] Figure 3 are the speed simulation curves of different control methods.

[0032] Figure 4 are the estimated values of the high- and low-frequency components of the disturbance and the output d f (t) waveforms. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention, and cannot be construed as a limitation of the present invention.

[0034] The present invention proposes a system control and anti-interference method for adjusting the switching gain of a sliding mode controller using multi-source information. For the first-order dynamic model of a permanent magnet synchronous motor (PMSM), the lumped disturbance acting on the motor is divided into high-frequency and low-frequency components. The first-order dynamic model of the permanent magnet synchronous motor is rewritten, and a second-order extended state observer (ESO) is designed to estimate the high-frequency component in the lumped disturbance.

[0035] For the estimated value of the low-frequency component of the disturbance, a low-frequency disturbance compensator (LPDF) is designed to estimate the low-frequency component in the lumped disturbance.

[0036] For the estimated value of the high-frequency component of the disturbance and the change of the speed error, a fuzzy system output additional gain is designed, and this additional gain is used to compensate for the large estimation error existing in the extended state observer at the initial moment of the disturbance action.

[0037] Design a system controller for the additional gains of the estimated value of the disturbance high-frequency component, the estimated value of the disturbance low-frequency component, and the output of the fuzzy system. The estimated value of the disturbance low-frequency component is directly fed forward for compensation, effectively reducing the upper bound of the disturbance acting on the system. The estimated value of the disturbance high-frequency component and the output of the fuzzy system are jointly used as the adjustable switching gain of the sliding mode controller, ensuring that the large-amplitude actions caused by the sudden disturbance are promptly suppressed, and at the same time taking into account the small-amplitude chattering dynamic operation of the system after the disturbance disappears.

[0038] The following is a specific embodiment of the present invention, which is as follows:

[0039] First, the interference is divided into two categories: low-frequency and high-frequency. The estimated value of the disturbance low-frequency component is directly compensated for the low-frequency interference, while the estimated value of the disturbance high-frequency component is used as a variable switching gain to suppress the high-frequency interference. In addition, the output of the fuzzy system is used as an additional switching gain, and the switching gain of the sliding mode controller changes faster, enabling the system to quickly suppress the sudden interference. The control block diagram of the system is as Figure 1 shown. The first-order dynamic model of the permanent magnet synchronous motor in the system is:

[0040]

[0041] Among them, B is the viscous friction coefficient, J is the moment of inertia of the motor drive system, ω(t) is the mechanical angular velocity of the motor, and T L (t) is the load torque.

[0042] The lumped disturbance d(t) is divided into:

[0043]

[0044] Rewrite the first-order dynamic model as:

[0045]

[0046] Among them,

[0047] The system sliding mode surface is designed as:

[0048] s(t) = ω(t) - ω * (t)

[0049] Among them, s(t) is the sliding mode variable, and ω * (t) is the angular velocity reference value.

[0050] According to the first-order dynamic model of the permanent magnet synchronous motor, the system controller is designed as:

[0051]

[0052] Among them, u(t) is the output signal of the system controller, and this signal is the magnitude of the q-axis reference current. x1(t) = ω(t), is the estimated value of the high-frequency disturbance, is the estimated value of the low-frequency disturbance, d f (t) is the additional gain output by the fuzzy system. k1 is an adjustable correction coefficient, and sat(·) is a saturation function. The function sat(·) is:

[0053]

[0054] Build an extended state observer according to the rewritten first-order dynamic model to estimate the high-frequency component of the disturbance

[0055]

[0056] Among them, [x1(t) x2(t)] = [ω(t) d h (t)], and are the estimated values of x1(t) and x2(t). β1 and β2 are the observer parameters.

[0057] Estimate the low-frequency component of the lumped disturbance The designed low-frequency disturbance compensator for

[0058]

[0059] Among them, k ω and δ are adjustable correction coefficients.

[0060] Let When it can be obtained that:

[0061]

[0062] Among them, when is used as the input, or is used as the output, the above expressions are in the forms of a low-pass filter and a high-pass filter respectively in the frequency domain:

[0063]

[0064] The designed extended state observer ensures that is uniformly bounded, will converge to the total disturbance d(t). Thus, is the estimated value of the low-frequency component in the lumped disturbance, is the estimated value of the high-frequency component in the lumped disturbance.

[0065] The input of the fuzzy system is n sampling periods Ts The absolute value change of the internal speed error and the high-frequency interference estimation value, and its expression is:

[0066]

[0067] where Δe(t) is the speed change, Δd(t) is the high-frequency disturbance estimation change, and e(t) is the speed error.

[0068] The fuzzy input Δe(t) is divided into 2 intervals: SM (small), BI (big). The fuzzy input Δd(t) is divided into 4 intervals: ZO (near zero), VM (very small), SM (small), BI (big). The fuzzy output d f (t) is divided into 4 intervals: ZO (near zero), VM (very small), SM (small), BI (big). The fuzzy rule base is shown in Table 1:

[0069] Table 1 Fuzzy rule base

[0070]

[0071] The motor operation process from startup, being subjected to sudden disturbances to steady state can be divided into three cases:

[0072] (1) Δe(t) ≤ 0, Δd(t) ≤ 0 and Δe(t) ≤ 0, Δd(t) > 0

[0073] During the motor startup process, the absolute value of the motor speed error Δe(t) is less than or equal to zero. And there are internal disturbances during the startup process of the motor, and the estimated disturbances will fluctuate, resulting in Δd(t) > 0 or Δd(t) < 0. In order not to make incorrect compensation, when Δe(t) ≤ 0, under the control of the fuzzy rules, the fuzzy output d f (t) remains zero. When the permanent magnet synchronous motor is subjected to a sudden disturbance, the situation of Δe(t) ≤ 0, Δd(t) ≤ 0 will also occur during the process of the motor speed changing from the maximum or minimum value to the reference speed. At this time, it is considered that the disturbance has been fully compensated, and the fuzzy output d f (t) remains zero.

[0074] (2) Δe(t) > 0, Δd(t) > 0

[0075] At this time, the system is subjected to a sudden disturbance, and the output of the fuzzy system is positively correlated with the change amount of the disturbance high-frequency component estimation value, realizing the suppression of sudden disturbances with different amplitudes by the system.

[0076] (3) Δe(t) > 0, Δd(t) ≤ 0

[0077] At this time, the disturbance estimated by the extended state observer has converged to the vicinity of the actual disturbance value, so the output of the fuzzy system is zero.

[0078] The fuzzy input and fuzzy output membership functions are as follows Figure 2 As shown. In fuzzy control, the centroid method is used for defuzzification to obtain the fuzzy output d f (t) as follows:

[0079]

[0080] where df(t) is the output of the fuzzy system, and z i is the magnitude of the output of the i-th fuzzy rule, and μ i (z i ) is the membership degree corresponding to the i-th fuzzy rule.

[0081] Therefore, the design steps of the sliding mode control method proposed by the present invention are as follows:

[0082] Step 1: Select the sliding mode controller parameter k1. Increasing k1 is beneficial to improving the response speed of the motor speed. Due to the constraints of the control system bandwidth and the motor current, there is an upper limit for k1.

[0083] Step 2: Select the extended state observers β1 and β2. The selection of β1 and β2 should ensure the convergence of the observers. Due to the limitation of the system bandwidth, there are upper limits for β1 and β2.

[0084] Step 3: Select the low-frequency disturbance compensator parameters k ω and δ. k ω is the cut-off frequency for distinguishing the high-frequency disturbance estimate value and the low-frequency disturbance estimate value. The high-frequency disturbance estimate value is estimated by the extended state observer. Therefore, the selection of k ω should be within the bandwidth range of the extended state observer. The function of the parameter δ is to limit the derivative of the disturbance compensation value and the selected δ can ensure that the system is as much as possible under the action of the disturbance

[0085] Step 4: Select the fuzzy rules. The formulation of the fuzzy rules should satisfy the relationship between the fuzzy input variables and the fuzzy output variables under different working conditions.

[0086] Step 5: The digital signal processor collects the three-phase current signals through the analog-to-digital converter and the motor rotor position and speed signals through the encoder, and outputs the control quantity u(t) according to the fuzzy sliding mode controller expression.

[0087] Step 6: Use the obtained speed loop controller output u(t) as the given value of the q-axis current loop, and combine the current loop controller to achieve the speed control of the permanent magnet synchronous motor.

[0088] To further illustrate the effectiveness of the proposed control strategy, simulation analysis is carried out in Matlab / Simulink. The parameters of the permanent magnet synchronous motor are set as shown in Table 2. The proposed FDCSMC+ESO method is compared with SMC+ESO and DCSMC+ESO. Among them, the expression of the SMC+ESO controller is:

[0089]

[0090] The expression of the DCSMC+ESO controller is:

[0091]

[0092] The expression of the controller of the FDCSMC+ESO method proposed in the present invention is:

[0093]

[0094] The parameters of the three controllers are shown in Table 3. The bus voltage is set to 200V, and the reference speed of the permanent magnet synchronous motor is set to 2000 r / min. The simulation condition is that the permanent magnet synchronous motor starts without load and a rated load torque is applied at 6 s, and the rated load torque is removed at 12 s. Figure 3 、 Figure 4 And Table 4 shows the results of this simulation test.

[0095] Table 2 Parameters of the permanent magnet synchronous motor

[0096] Parameter Value Parameter Value Rated voltage (V) 200 Permanent magnet flux linkage (Wb) 0.12025 Rated current (A) 5.3 <![CDATA[Moment of inertia (kg.m 2 )]]> 0.0132 Rated power (kW) 1 Friction coefficient (N.m.s / rad) 0.005 Rated torque (N.m) 4.78 d-axis inductance (mH) 2.95 Number of pole pairs 5 q-axis inductance (mH) 2.95

[0097] Table 3 Simulation control parameters of different control methods

[0098] Method Value SMC + ESO <![CDATA[k1 = 0.022, k2 = 0.03, ω0 = 100]]> DCSMC + ESO <![CDATA[k1 = 0.022, ω0 = 100, δ = 1000, κ = 0.3]]> FDCSMC + ESO <![CDATA[k1 = 0.022, ω0 = 100, δ = 1000, κ = 0.3]]>

[0099] Table 4 Performance indexes of simulation test with loading for different methods

[0100]

[0101] As Figure 3 shown, all three control methods can achieve speed control without overshoot. The different load characteristics of the actual loading and unloading processes are considered in the simulation. Therefore, there are certain differences in the speed change Δn and the recovery time t r of each method during the loading and unloading processes. By comparing the dynamic performance indexes of the three methods in Table 4, it can be known that the proposed FDCSMC+ESO control strategy has stronger anti-interference ability than DCSMC+ESO and SMC+ESO. When the motor is subjected to sudden disturbances, it has a faster recovery time and a smaller speed change. The estimated value of the high-frequency component of the disturbance under FDCSMC+ESO control The estimated value of the low-frequency component of the disturbance and the output d of the fuzzy system f (t) waveform is as Figure 4 shown. When the PMSM is subjected to a sudden disturbance, the estimated value of the disturbance high-frequency component and the output of the fuzzy system increase rapidly, realizing the rapid suppression of the sudden disturbance. The output of the fuzzy system is related to the estimation error of the high-frequency interference. Therefore, the output of the fuzzy system has differences during the loading and unloading processes.

[0102] Embodiment 2:

[0103] This embodiment provides a control device for a permanent magnet synchronous motor drive system, including:

[0104] A low-frequency disturbance compensator for obtaining an estimated value of the low-frequency component in the lumped disturbance;

[0105] A second-order extended state observer for obtaining an estimated value of the high-frequency component in the lumped disturbance;

[0106] An adjustable switching gain module, which designs an additional gain for the output of the fuzzy system according to the changes in the estimated value of the disturbance high-frequency component and the speed error; forms the adjustable switching gain of the sliding mode controller by combining the estimated value of the disturbance high-frequency component and the additional switching gain of the output of the fuzzy system;

[0107] A system controller for directly feed-forward compensating the estimated low-frequency disturbance estimate; when the system is subjected to a sudden disturbance, controlling the estimated value of the disturbance high-frequency component and the output of the fuzzy system to increase rapidly to suppress the disturbance; when the disturbance is a slow time-varying disturbance, controlling the estimated value of the disturbance high-frequency component and the output of the fuzzy system to decrease to near zero, thereby reducing the steady-state chattering of the system. Using the controller output signal as the given value of the q-axis current loop and combining with the current loop controller to achieve the speed control of the permanent magnet synchronous motor.

[0108] The specific implementation content of each of the above units corresponds one by one to the steps of the method proposed in Embodiment 1 of the present invention, and will not be elaborated here.

[0109] Embodiment 3:

[0110] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method of the present invention are implemented, and will not be elaborated here.

[0111] Embodiment 4:

[0112] This embodiment further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor.

[0113] It should be noted that the processing flows of Embodiment 2 to Embodiment 4 correspond to the specific steps of the method provided by the embodiments of the present invention, and have the corresponding functional modules and beneficial effects of the method. For technical details not described in detail in this embodiment, reference can be made to the method provided by the embodiments of the present invention.

[0114] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0115] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0116] In the description of this specification, the descriptions with reference to the terms "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0117] The above description is only a preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

[0118] The basic principles, main features and advantages of the present invention have been shown and described above. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and all these changes and improvements fall within the scope of the present invention claimed.

Claims

1. A control method for a permanent magnet synchronous motor drive system, characterized in that, Including the steps: S1. Divide the lumped disturbance acting on the permanent magnet synchronous motor into high-frequency components and low-frequency components, establish a first-order dynamic model of the permanent magnet synchronous motor, and build a second-order extended state observer to obtain the estimated value of the high-frequency components in the lumped disturbance; S2. Use a low-frequency disturbance compensator to obtain the estimated value of the low-frequency components in the lumped disturbance; design a fuzzy system to output an additional gain according to the changes in the estimated value of the high-frequency disturbance components and the speed error, and this additional gain is used to compensate for the estimation error existing in the extended state observer at the initial moment of the disturbance action; S3. Design a system controller according to the estimated value of the high-frequency disturbance components, the estimated value of the low-frequency disturbance components, and the additional gain output by the fuzzy system. Feed forward compensate the estimated value of the low-frequency disturbance components directly, and use the estimated value of the high-frequency disturbance components and the output of the fuzzy system as the adjustable switching gain of the sliding mode controller. Specifically: when the system is subjected to a sudden disturbance, the estimated value of the high-frequency disturbance components and the output of the fuzzy system increase rapidly to suppress the disturbance; when the disturbance is a slow time-varying disturbance, the estimated value of the high-frequency disturbance components and the output of the fuzzy system decrease to near zero, thereby reducing the chattering of the system in the steady state.

2. The method according to claim 1, wherein The expression of the system controller described in S3 is: wherein, u(t) is the output signal of the controller, and this signal is the magnitude of the q-axis reference current; s(t) is the sliding mode variable, s(t)=ω(t)-ω * (t), ω(t) is the mechanical speed of the motor, and ω * (t) is the speed reference value, x1(t)=ω(t), is the estimated value of the high-frequency component of the disturbance, is the estimated value of the low-frequency component of the disturbance, d f (t) is the additional gain output by the fuzzy system, k1 is an adjustable correction coefficient, a is a system parameter, and sat(·) is a saturation function. The function sat(·) is: where \(c1,c2\in R\).

3. The method according to claim 2, characterized in that, The lumped disturbance \(d(t)\) is divided into two parts: The first-order dynamic model of the permanent magnet synchronous motor is established as: Among them, b is a system parameter, and an extended state observer is constructed according to the first-order dynamic model to estimate the high-frequency component of the disturbance: where, [x1(t) x2(t)] = [ω(t) d h (t)], and are the estimated values of x1(t) and x2(t), and β1 and β2 are the observer parameters.

4. The method according to claim 3, wherein The low-frequency disturbance compensator used to estimate the low-frequency components of the disturbance is designed as: Among them, is the estimated value of the lumped disturbance low-frequency component, and k ω and δ are adjustable correction coefficients.

5. The method according to claim 4, wherein The said k ω is the cut-off frequency for distinguishing the high-frequency components and low-frequency components of the disturbance, and k ω should be selected within the bandwidth of the extended state observer.

6. The method according to claim 1, wherein The additional gain output by the fuzzy system is: where d f (t) is the output of the fuzzy system, and z i is the magnitude of the output of the i-th fuzzy rule, and μ i (z i ) is the membership degree corresponding to the i-th fuzzy rule.

7. A control device for a permanent magnet synchronous motor drive system, characterized in that, Including: A low-frequency disturbance compensator for obtaining the estimated value of the low-frequency components in the lumped disturbance; A second-order extended state observer for obtaining the estimated value of the high-frequency components in the lumped disturbance; An adjustable switching gain module that designs a fuzzy system to output an additional gain according to the changes in the estimated value of the high-frequency disturbance components and the speed error; forms the adjustable switching gain of the sliding mode controller by combining the estimated value of the high-frequency disturbance components and the additional switching gain output by the fuzzy system; A system controller for directly feed forward compensating the estimated value of the low-frequency disturbance estimation; when the system is subjected to a sudden disturbance, controlling the estimated value of the high-frequency disturbance components and the output of the fuzzy system to increase rapidly to suppress the disturbance; when the disturbance is a slow time-varying disturbance, controlling the estimated value of the high-frequency disturbance components and the output of the fuzzy system to decrease to near zero, thereby reducing the chattering of the system in the steady state.

8. The control device of a permanent magnet synchronous motor drive system according to claim 7, characterized in that, The system controller is: where \(u(t)\) is the output signal of the controller, which is the magnitude of the q-axis reference current, \(s(t)\) is the sliding mode variable, \(s(t)=\omega(t)-\omega\) * (t), \(\omega(t)\) is the mechanical speed of the motor, \(\omega\) * (t) is the speed reference value, \(x_1(t)=\omega(t)\), is the estimated value of the high-frequency component of the disturbance, is the estimated value of the low-frequency component of the disturbance, \(d\) f (t) is the additional gain output by the fuzzy system, \(k_1\) is an adjustable correction coefficient, \(a\) is a system parameter, \(sat(\cdot)\) is the saturation function, and the function \(sat(\cdot)\) is: where \(c1,c2\in R\); Use the controller output signal as the given value of the q-axis current loop, and combine with the current loop controller to realize the speed control of the permanent magnet synchronous motor.

9. An electronic system, comprising: At least one processor; And a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and is characterized in that the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-6.

10. A computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

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