Permanent magnet synchronous motor control method
Patent Information
- Application Number
- PCT/CN2025/108962
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-03-28
- Filing Date
- 2025-07-17
- Publication Date
- 2026-10-01
Smart Images
Figure CN2025108962_01102026_PF_FP_ABST
Abstract
Description
A control method for a permanent magnet synchronous motor Technical Field
[0001] This invention relates to the field of synchronous motor control technology, and in particular to a control method for a permanent magnet synchronous motor. Background Technology
[0002] Improving system reliability, enhancing power factor, and reducing costs are increasingly important trends in home appliances such as refrigerators, air conditioners, and fans. Permanent magnet synchronous motors (PMSMs) are commonly used in these appliances due to their advantages, including high power density, large torque, small size, high efficiency, simple control, and high precision. However, the different forms of loads driven by PMSMs result in different load signal formats. When these loads are added to the PMSM control system, they cause speed fluctuations, which in turn cause vibrations in the motor control system, affecting the high-precision speed control of the PMSM. Summary of the Invention
[0003] This invention provides a control method for a permanent magnet synchronous motor, the purpose of which is to suppress speed fluctuations and improve the control accuracy of the permanent magnet synchronous motor speed.
[0004] To achieve the above objectives, the present invention provides a control method for a permanent magnet synchronous motor, comprising:
[0005] Step 1: Select the target permanent magnet synchronous motor. The dual closed-loop control system of the target permanent magnet synchronous motor includes an outer speed loop and an inner current loop.
[0006] Step 2: Design a fractional sliding surface and a fractional reaching law in the outer loop of rotational speed, and construct a fractional sliding controller based on the fractional sliding surface and the fractional reaching law.
[0007] Step 3: Use the dung beetle algorithm to tune the parameters of the fractional sliding mode controller to obtain the optimal control parameters of the fractional sliding mode controller. The fractional sliding mode controller generates the optimal q-axis current control command for the target permanent magnet synchronous motor based on the optimal control parameters.
[0008] Step 4: Design a fractional-order prediction model and a fractional-order cost function in the inner current loop, and construct a fractional-order model predictive current controller based on the fractional-order prediction model and the fractional-order cost function. The fractional-order model predictive current controller is used to generate the optimal stator voltage control command for the target permanent magnet synchronous motor.
[0009] Step 5: Control the speed and current of the target permanent magnet synchronous motor based on the optimal q-axis current control command and the optimal stator voltage control command, so that the actual speed and current of the target permanent magnet synchronous motor track the given speed and current.
[0010] Furthermore, the design of fractional-order sliding surfaces and fractional-order reaching laws in the outer ring of rotational speed includes:
[0011] For a given target signal, define position tracking error and velocity tracking error;
[0012] Based on position tracking error and velocity tracking error, a fast terminal sliding surface that converges within a preset time is constructed in the outer loop of rotational speed;
[0013] By constraining the parameters in the fast terminal sliding surface and introducing a fractional differential linear term, the fast terminal sliding surface converges, resulting in a fractional sliding surface.
[0014] The design introduces a fractional-order reaching law to obtain a fractional-order reaching law for enabling the dual-closed-loop control system to enter the sliding mode state.
[0015] Furthermore, the expression for a fractional-order sliding surface is:
[0016] in, This represents a fractional-order sliding surface, where e1 represents the position tracking error, e2 represents the velocity tracking error, and D... -α [·] denotes a fractional integral operator, α denotes the differential order, k1 and k2 are both positive real numbers, and p and q are both parameters of the fast terminal sliding surface.
[0017] Furthermore, the expression for the fractional-order reaching law is:
[0018] in, This represents the fractional-order reaching law, where η, λ, and μ are all undetermined coefficients, and D... α [·] indicates the fractional order toggle.
[0019] Furthermore, the expression for the fractional-order sliding mode controller is:
[0020] Where u represents the fractional-order sliding mode controller, and b(x) represents the non-homogeneous term in the permanent magnet synchronous motor object model. J represents the moment of inertia of the motor, x d Let f(x) represent the homogeneous term in the permanent magnet synchronous motor object model, given the target tracking signal. B represents the damping viscosity coefficient.
[0021] Furthermore, a fractional-order prediction model and a fractional-order cost function are designed in the inner current loop, including:
[0022] Based on the voltage balance equation of the target permanent magnet synchronous motor in the dq coordinate system, a fractional differential operator is introduced to construct a fractional voltage balance equation in the inner current loop.
[0023] A fractional-order prediction model for the fractional-order voltage balance equation is constructed using a fractional-order prediction and correction algorithm.
[0024] Select the dq-axis voltage vector and construct a numerical evaluation index expression for the dq-axis voltage vector;
[0025] Based on the numerical evaluation index expression, fractional calculus theory is introduced to design a fractional cost function.
[0026] Furthermore, the voltage balance equation of the target permanent magnet synchronous motor in the dq coordinate system is:
[0027] Where p represents the differential operator, u d U represents the d-axis voltage in the synchronous coordinate system. q i represents the q-axis voltage in the synchronous coordinate system. d i represents the d-axis current in the synchronous coordinate system. q L represents the q-axis current in the synchronous coordinate system, R represents the stator winding phase resistance, and L represents the q-axis current in the synchronous coordinate system. d L represents the d-axis inductance. q Represents the q-axis inductance, ω e ψ represents the mechanical angular velocity of a permanent magnet synchronous motor. f This indicates the magnetic flux linkage of a permanent magnet.
[0028] Furthermore, the fractional-order voltage balance equation is:
[0029] Among them, L s This indicates the stator inductance.
[0030] Furthermore, the fractional-order prediction model is as follows:
[0031] Where h represents the sampling period of the discretized target permanent magnet synchronous motor control system, Γ(·) represents the Gamma function, and α j,n+1 This represents the correction factor.
[0032] Furthermore, the expression for the fractional-order cost function is:
[0033] in, Denotes fractional cost, t ft0 represents the set termination time of the fractional-order prediction and correction algorithm, t0 represents the set start time of the fractional-order prediction and correction algorithm, and β represents the fractional order when converting the summation relationship in the numerical evaluation index into fractional-order integration. This indicates the q-axis current control command output by the outer loop control of the rotational speed. This represents the d-axis control command output by the outer loop control of the rotational speed, ω. k+1 denoted by weight factor, and k represents the sampling time.
[0034] The above-described solution of the present invention has the following beneficial effects:
[0035] This invention designs a fractional-order sliding surface and a fractional-order reaching law in the outer speed loop of a target permanent magnet synchronous motor (PMSM), and constructs a fractional-order sliding mode controller based on these parameters. The parameters of the fractional-order sliding mode controller are tuned using a dung beetle algorithm to obtain the optimal control parameters. The fractional-order sliding mode controller then generates the optimal q-axis current control command based on these optimal control parameters. Furthermore, a fractional-order prediction model and a fractional-order cost function are designed in the inner current loop of the target PMSM, and a fractional-order model predictive current controller is constructed based on these parameters. The model predictive current controller is used to generate the optimal stator voltage control command. Based on the optimal q-axis current control command and the optimal stator voltage control command, the speed and current of the target permanent magnet synchronous motor are controlled respectively, so that the actual speed and current of the target permanent magnet synchronous motor track the given speed and current. Compared with the prior art, this invention introduces a fractional-order operator into the traditional sliding mode controller and model predictive current controller, thereby improving the control accuracy of the permanent magnet synchronous motor speed by suppressing the speed fluctuation of the permanent magnet synchronous motor. This provides sufficient basis and reliability guarantee for the fault-tolerant control mechanism of high-performance permanent magnet synchronous motors.
[0036] Other beneficial effects of the present invention will be described in detail in the following detailed description section. Attached Figure Description
[0037] Figure 1 is a flowchart of an embodiment of the present invention;
[0038] Figure 2 is a flowchart of the dung beetle algorithm in an embodiment of the present invention;
[0039] Figure 3 shows the mechanical angular velocity ω. e and the q-axis current i in the synchronous coordinate system q The response waveform diagram. Detailed Implementation
[0040] To make the technical problems, solutions, and advantages of this invention clearer, a detailed description will be provided below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0041] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0042] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a locking connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0043] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
[0044] This invention addresses existing problems by providing a control method for a permanent magnet synchronous motor.
[0045] As shown in Figure 1, an embodiment of the present invention provides a control method for a permanent magnet synchronous motor, including:
[0046] Step 1: Select the target permanent magnet synchronous motor. The dual closed-loop control system of the target permanent magnet synchronous motor includes an outer speed loop and an inner current loop.
[0047] Step 2: Design a fractional sliding surface and a fractional reaching law in the outer loop of rotational speed, and construct a fractional sliding controller based on the fractional sliding surface and the fractional reaching law.
[0048] Step 3: Use the dung beetle algorithm to tune the parameters of the fractional sliding mode controller to obtain the optimal control parameters of the fractional sliding mode controller. The fractional sliding mode controller generates the optimal q-axis current control command for the target permanent magnet synchronous motor based on the optimal control parameters.
[0049] Step 4: Design a fractional-order prediction model and a fractional-order cost function in the inner current loop, and construct a fractional-order model predictive current controller based on the fractional-order prediction model and the fractional-order cost function. The fractional-order model predictive current controller is used to generate the optimal stator voltage control command for the target permanent magnet synchronous motor.
[0050] Step 5: Control the speed and current of the target permanent magnet synchronous motor based on the optimal q-axis current control command and the optimal stator voltage control command, so that the actual speed and current of the target permanent magnet synchronous motor track the given speed and current.
[0051] This invention takes a permanent magnet synchronous motor as the research object. The control system of the permanent magnet synchronous motor is a dual closed-loop control system, with the two closed loops being an outer speed loop and an inner current loop.
[0052] Specifically, a fractional-order sliding surface and a fractional-order reaching law are designed in the outer ring of the rotational speed, including:
[0053] For a given target signal, define position tracking error and velocity tracking error;
[0054] Based on position tracking error and velocity tracking error, a fast terminal sliding surface that converges within a preset time is constructed in the outer loop of rotational speed;
[0055] By constraining the parameters in the fast terminal sliding surface and introducing a fractional differential linear term, the fast terminal sliding surface converges, resulting in a fractional sliding surface.
[0056] The design introduces a fractional-order reaching law to obtain a fractional-order reaching law for enabling the dual-closed-loop control system to enter the sliding mode state.
[0057] In this embodiment of the invention, the position tracking error is defined as e1 and the velocity tracking error as e2, and the expression is as follows: e1 = x d -θ e
[0058] Where, x d Let θ represent the given target signal being tracked. e This indicates the mechanical angle of a permanent magnet synchronous motor. ω represents the rate of change of a given target signal. e This represents the mechanical angular velocity of a permanent magnet synchronous motor;
[0059] Based on position tracking error and velocity tracking error, a fast terminal sliding surface that converges in a finite time is constructed in the outer rotational speed loop, as follows:
[0060] Where s represents the fast terminal sliding surface, k represents the sliding surface gain, p and q are both parameters of the fast terminal sliding surface, p and q are both positive odd numbers, and p>q.
[0061] By constraining the range of parameters p and q and introducing fractional-order differential linear terms, the fast-terminal sliding surface can avoid singular phenomena and achieve fast convergence. Therefore, a fractional-order sliding surface is designed, and its expression is:
[0062] in, This represents a fractional-order sliding surface, where e1 represents the position tracking error, e2 represents the velocity tracking error, and D... -α [·] denotes a fractional integral operator, α denotes the differential order, k1 and k2 are both positive real numbers, and p and q are both parameters of the fast terminal sliding surface.
[0063] In this embodiment of the invention, when the tracking error of the dual-closed-loop control system is far from the equilibrium point, the exponential term in the fractional sliding surface enables the system tracking error to converge quickly; while when the tracking error of the dual-closed-loop empty flocking system is close to the equilibrium point, the linear term in the fractional sliding surface dominates the system tracking error to converge quickly. Therefore, introducing a fractional integral operator into the linear term can enable the fractional sliding surface to have a faster convergence speed when it is close to the equilibrium point.
[0064] In this embodiment of the invention, to ensure that the system enters the sliding mode state quickly and smoothly, a fractional operator is introduced into the reaching law, resulting in a fractional reaching law, the expression of which is:
[0065] in, Let D represent the fractional-order reaching law, where η, λ, and μ are all undetermined coefficients, satisfying η>0, λ>0, 0<μ≤1. α [·] indicates a fractional-order switching term. When the value of s is large, the fractional-order switching term accelerates the approach speed. When s is small, it can slow down the approach rate, thereby ensuring that the approach speed to the sliding surface is accelerated without increasing chattering.
[0066] Specifically, the expression for constructing a fractional-order sliding mode controller by combining a fractional-order sliding surface and a fractional-order reaching law is as follows:
[0067] Where u represents the fractional-order sliding mode controller, and b(x) represents the non-homogeneous term in the permanent magnet synchronous motor object model. J represents the moment of inertia of the motor, x d Let f(x) represent the homogeneous term in the permanent magnet synchronous motor object model, given the target tracking signal. B represents the damping viscosity coefficient.
[0068] Since the control performance of the fractional sliding mode controller is significantly affected by parameters k1, k2, η, λ, and μ, this embodiment of the invention uses the dung beetle algorithm to optimize and tune these parameters, seeking the optimal solution to achieve the best speed tracking performance of the dual closed-loop control system. The dung beetle algorithm includes rolling dung beetles, egg-hatching dung beetles, small dung beetles, and thieving dung beetles. Each set of parameters of the fractional sliding mode controller is considered an individual in the population. The specific optimization process is as follows:
[0069] First, set the maximum number of iterations and the population size;
[0070] Then, the rolling dung beetle, the incubating dung beetle, the baby dung beetle, and the thieving dung beetle in the dung beetle algorithm are randomly initialized;
[0071] Calculate the initial fitness values of the rolling dung beetle, the egg-hatching dung beetle, the small dung beetle, and the thieving dung beetle based on the objective function;
[0072] Determine if the current individual is a dung beetle. If so, update the dung beetle's position using its position update mechanism. The update mechanism expression is: x i (t+1)=x i (t)+αkx i (t-1)+b|x i (t)-X w |
[0073] Where, x i (t+1) represents the value of the i-th set of parameter vectors [k1,k2,η,λ,μ] randomly generated in the fractional sliding mode controller at the t-th iteration; k represents the deflection coefficient, k∈(0,0.2]; b represents the natural coefficient, b∈(0,1), X w α represents the worst position within the current population, and α is the exploration preference parameter of the search space;
[0074] Otherwise, determine whether the current individual is a dung beetle incubating eggs. If so, update the position of the dung beetle incubating eggs using the dung beetle incubating egg position update mechanism. The update mechanism expression is: B i (t+1)=X * +b1(B i (t)-Lb*)+b2(B i (t)-Ub*)
[0075] Among them, B i (t) represents the position of the i-th incubation egg in the t-th iteration, and b1 and b2 represent two independent random variables; X * Lb represents the optimal position within the current population. * Ub * Indicates the lower and upper limits of the spawning area;
[0076] Otherwise, determine if the current individual is a dung beetle. If so, update the dung beetle's position using the dung beetle's position update mechanism. The update mechanism expression is: x i (t+1)=x i (t)+C1(x i (t)-Lb b )+C2(B i (t)-Ub*)
[0077] Among them, Lb b Ub * C1 represents the lower and upper bounds of the range of values for the parameter vector [k1,k2,η,λ,μ] in a fractional sliding mode controller; C2 represents a random number following a normal distribution; C3 represents a random number belonging to a uniform distribution.
[0078] Otherwise, determine if the current individual is a dung beetle. If so, update the dung beetle's position using the dung beetle's position update mechanism. The update mechanism expression is: x i (t+1)=X b +Sg(|x1(t)-X*|+x1(t-X) b )
[0079] Where S and g represent a constant and a random variable that follows a normal distribution, respectively;
[0080] When the entire population has been traversed and the maximum number of iterations has been reached, the optimal control parameters of the fractional sliding mode controller are output.
[0081] Specifically, a fractional-order prediction model and a fractional-order cost function are designed in the inner current loop, including:
[0082] Based on the voltage balance equation of the target permanent magnet synchronous motor in the dq coordinate system, a fractional differential operator is introduced to construct a fractional voltage balance equation in the inner current loop.
[0083] A fractional-order prediction model for the fractional-order voltage balance equation is constructed using a fractional-order prediction and correction algorithm.
[0084] Select the dq-axis voltage vector and construct a numerical evaluation index expression for the dq-axis voltage vector;
[0085] Based on the numerical evaluation index expression, fractional calculus theory is introduced to design a fractional cost function.
[0086] Specifically, the voltage balance equation of the target permanent magnet synchronous motor in the dq coordinate system is:
[0087] Where p represents the differential operator, u dU represents the d-axis voltage in the synchronous coordinate system. q i represents the q-axis voltage in the synchronous coordinate system. d i represents the d-axis current in the synchronous coordinate system. q L represents the q-axis current in the synchronous coordinate system, R represents the stator winding phase resistance, and L represents the q-axis current in the synchronous coordinate system. d L represents the d-axis inductance. q Represents the q-axis inductance, ω e ψ represents the mechanical angular velocity of the motor. f This indicates the magnetic flux linkage of a permanent magnet.
[0088] Specifically, based on the voltage balance equation of the target permanent magnet synchronous motor in the dq coordinate system, a fractional differential operator is introduced to construct a fractional voltage balance equation in the inner current loop, as follows:
[0089] Among them, L s Indicates stator inductance;
[0090] Specifically, using a fractional prediction and correction algorithm, the fractional-order prediction model for the fractional-order voltage balance equation of the permanent magnet synchronous motor under the above continuous case is constructed as follows:
[0091] Where h represents the sampling period of the discretized target permanent magnet synchronous motor control system, Γ(·) represents the Gamma function, and α j,n+1 The correction factor is represented in the following form:
[0092] Where n represents the current step number of the prediction correction algorithm, q represents the fractional order, q = α, and j represents the index factor.
[0093] The dq-axis voltage vector selected in this embodiment of the invention is the optimal voltage vector. The optimal voltage vector is the dq-axis voltage vector that minimizes the deviation between the model-predicted current and the input control command current. The numerical evaluation index expression for the dq-axis voltage vector is constructed as follows:
[0094] Among them, J n Indicates numerical evaluation index, This represents the d-axis control command output by the outer loop control of the rotational speed. This represents the q-axis current control command output by the outer loop control of the rotational speed. If the dual closed-loop control system adopts a field-oriented control strategy, then...
[0095] Specifically, the expression for the fractional-order cost function is:
[0096] in, Denotes fractional cost, t f t0 represents the set termination time of the fractional-order prediction and correction algorithm, t0 represents the set start time of the fractional-order prediction and correction algorithm, and β represents the fractional order when converting the summation relationship in the numerical evaluation index into fractional-order integration. This indicates the q-axis current control command output by the outer loop control of the rotational speed. This represents the d-axis control command output by the outer loop control of the rotational speed, k represents the sampling time, and ω represents the speed. k+1 Let represent the weighting factor, and satisfy the following relationship:
[0097] Among them, L N Let represent an Nth-order Legendre polynomial.
[0098] In this embodiment of the invention, the numerical evaluation criteria for the model of the dual closed-loop control system for permanent magnet synchronous motor are as follows:
[0099] Where t represents the simulation time array recorded in the model, t f This represents the simulation termination time in the model; err(t) represents the input value of the speed controller, i.e., the deviation between the speed setpoint and the feedback.
[0100] To verify the effectiveness of the control method provided in this embodiment of the invention, a surface-mounted permanent magnet synchronous motor with parameters as shown in Table 1 below was selected as the controlled object:
[0101] Table 1
[0102] Given speed control command As a stepped wave input, under the provided control method, the mechanical angular velocity ω of the controlled object... e and the q-axis current i in the synchronous coordinate system q The response waveforms are shown in Figure 3(a) and (b). Experiments have shown that, given that the stepped wave input is a relatively slowly changing process, the actual speed feedback of the motor can achieve very high following accuracy when following the given speed control signal. At the same time, the ripple of the q-axis current and electromagnetic torque can always be controlled within a small amplitude range.
[0103] This invention designs a fractional-order sliding surface and a fractional-order reaching law in the outer speed loop of a target permanent magnet synchronous motor (PMSM), and constructs a fractional-order sliding mode controller based on these parameters. The parameters of the fractional-order sliding mode controller are tuned using a dung beetle algorithm to obtain the optimal control parameters. The fractional-order sliding mode controller then generates the optimal q-axis current control command based on these optimal control parameters. In the inner current loop of the target PMSM, a fractional-order prediction model and a fractional-order cost function are designed, and a fractional-order model predictive current controller is constructed based on these parameters. The model predictive current controller is used to generate the optimal stator voltage control command. Based on the optimal q-axis current control command and the optimal stator voltage control command, the speed and current of the target permanent magnet synchronous motor are controlled respectively, so that the actual speed and current of the target permanent magnet synchronous motor track the given speed and current. Compared with the prior art, the embodiments of the present invention introduce fractional-order operators into the traditional sliding mode controller and model predictive current controller, thereby improving the control accuracy of the permanent magnet synchronous motor speed by suppressing the speed fluctuation of the permanent magnet synchronous motor, and providing sufficient basis and reliability guarantee for the fault-tolerant control mechanism of high-performance permanent magnet synchronous motors.
[0104] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A control method for a permanent magnet synchronous motor, characterized in that, include: Step 1: Select the target permanent magnet synchronous motor. The dual closed-loop control system of the target permanent magnet synchronous motor includes an outer speed loop and an inner current loop. Step 2: Design a fractional-order sliding surface and a fractional-order reaching law in the outer speed loop, and construct a fractional-order sliding controller based on the fractional-order sliding surface and the fractional-order reaching law. The expression of the fractional-order sliding surface is: wherein This represents a fractional-order sliding surface, where e1 represents the position tracking error, e2 represents the velocity tracking error, and D... -α [·] denotes a fractional integral operator, α denotes the differential order, k1 and k2 are both positive real numbers, and p and q are both parameters of the fast terminal sliding surface. Step 3: The parameters of the fractional sliding mode controller are tuned using the dung beetle algorithm to obtain the optimal control parameters of the fractional sliding mode controller. The fractional sliding mode controller generates the optimal q-axis current control command for the target permanent magnet synchronous motor based on the optimal control parameters. Step 4: Design a fractional-order prediction model and a fractional-order cost function in the inner current loop, and construct a fractional-order model predictive current controller based on the fractional-order prediction model and the fractional-order cost function. The fractional-order model predictive current controller is used to generate the optimal stator voltage control command for the target permanent magnet synchronous motor. Designing a fractional-order prediction model and a fractional-order cost function in the inner current loop includes: Based on the voltage balance equation of the target permanent magnet synchronous motor in the dq coordinate system, a fractional differential operator is introduced to construct a fractional voltage balance equation in the inner current loop. A fractional-order prediction model for the fractional-order voltage balance equation is constructed using a fractional-order prediction and correction algorithm. Select the dq-axis voltage vector and construct a numerical evaluation index expression for the dq-axis voltage vector; Based on the numerical evaluation index expression, fractional calculus theory is introduced to design a fractional cost function; Step 5: Based on the optimal q-axis current control command and the optimal stator voltage control command, control the speed and current of the target permanent magnet synchronous motor respectively, so that the actual speed and current of the target permanent magnet synchronous motor track the given speed and current.
2. The control method for a permanent magnet synchronous motor according to claim 1, characterized in that, A fractional-order sliding surface and a fractional-order reaching law are designed in the outer rotational speed ring, including: For a given target signal, define position tracking error and velocity tracking error; Based on the position tracking error and the speed tracking error, a fast terminal sliding surface that converges within a preset time is constructed in the outer rotation speed loop; The parameters in the fast terminal sliding surface are constrained, and a fractional differential linear term is introduced to make the fast terminal sliding surface converge, thus obtaining a fractional sliding surface. The design introduces a fractional-order reaching law to obtain a fractional-order reaching law for enabling the dual-closed-loop control system to enter the sliding mode state.
3. The control method of a permanent magnet synchronous motor according to claim 2, characterized by, The expression for the fractional-order reaching law is: wherein Let represent the fractional-order reaching law, s represent the fast terminal sliding surface, and η, λ, and μ all represent undetermined coefficients. α [·] indicates the fractional order toggle.
4. The control method of a permanent magnet synchronous motor according to claim 3, characterized by, The expression of the fractional order sliding mode controller is: wherein u represents a fractional order sliding mode controller, b(x) represents a non-homogeneous term in a permanent magnet synchronous motor object model, J represents the motor rotational inertia, x d represents the given tracking target signal, f(x) represents the homogeneous term in the permanent magnet synchronous motor object model, B represents the damping viscosity coefficient.
5. The control method of a permanent magnet synchronous motor according to claim 4, characterized by, The voltage balance equation of the target permanent magnet synchronous motor in a d-q coordinate system is: Where p represents the differential operator, u d U represents the d-axis voltage in the synchronous coordinate system. q i represents the q-axis voltage in the synchronous coordinate system. d i represents the d-axis current in the synchronous coordinate system. q L represents the q-axis current in the synchronous coordinate system, R represents the stator winding phase resistance, and L represents the q-axis current in the synchronous coordinate system. d L represents the d-axis inductance. q Represents the q-axis inductance, ω e ψ represents the mechanical angular velocity of a permanent magnet synchronous motor. f This indicates the magnetic flux linkage of a permanent magnet.
6. The control method of a permanent magnet synchronous motor according to claim 5, characterized by, The fractional-order voltage balance equation is: Among them, L s This indicates the stator inductance.
7. The control method of a permanent magnet synchronous motor according to claim 6, characterized by, The fractional order prediction model is: Where h represents the sampling period of the discretized target permanent magnet synchronous motor control system, Γ(·) represents the Gamma function, and α j,n+1 This represents the correction factor.
8. The control method for a permanent magnet synchronous motor according to claim 7, characterized in that, The expression of the fractional cost function is: wherein denotes a fractional order cost, t f denotes a termination time of the fractional order prediction-correction algorithm, t0denotes a start time of the fractional order prediction-correction algorithm, and β denotes a fractional order for converting a summation relation in the numerical evaluation index into a fractional order integral operation, a q-axis current control command indicative of a speed outer loop control output, This represents the d-axis control command output by the outer loop control of the rotational speed, ω. k+1 denoted by weight factor, and k represents the sampling time.