Novel SMC motor control method

Abstract

The invention relates to a novel SMC motor control method. The method comprises the following steps: defining that motor control adopts a nonlinear control algorithm; approaching to a sliding mode surface within limited convergence time based on a sliding mode state variable; approaching the sliding mode surface in an exponential approaching mode by adopting an exponential approaching rate; defining a sliding mode surface function; a smooth switching function is adopted as a sliding mode state quantity switching mode; constructing a sliding mode controller based on the sliding mode surface, the index approaching rate and the smooth switching function, and introducing a fuzzy intelligent control mode to construct a fuzzy controller; the fuzzy controller adopts two-dimensional fuzzy control, and fuzzy input quantity is state variable approaching speed variable quantity and change rate. According to the novel SMC motor control method provided by the invention, the sliding mode controller is constructed based on the sliding mode surface, the index approaching rate and the smooth switching function, and the vibration of the motor is reduced, so that the fault rate of the heat dissipation motor is reduced, the availability of a unit is improved, and the lost generating capacity of the unit is reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of motor control, and particularly relates to a novel SMC motor control method. BACKGROUND

[0002] The common cooling mode of a unit box transformer is air cooling, and the normal operation of a motor is directly related to the cooling efficiency of the box transformer. However, motor vibration is the main cause of motor failure. The commonly used vibration reduction measures are mechanical vibration reduction methods, such as increasing supports and the like. The principle of this vibration reduction method is to increase the stable force point of the motor to reduce vibration. However, the mechanical vibration reduction method can cause rusting of the support or loosening of the bolt, resulting in a change in the position of the support, reducing the vibration reduction effect, causing maintenance difficulties, and increasing maintenance costs. SUMMARY

[0003] The technical problem of the application is to provide a novel SMC motor control method, which introduces a fuzzy controller of two-dimensional fuzzy control and improves the motor control performance by using an improved control algorithm to reduce the vibration of the motor and ensure the continuous and stable operation of the motor.

[0004] The application aims to solve the above problems and provides a novel SMC motor control method, which comprises the following steps. Defining a nonlinear control algorithm for motor control; Based on the fact that the sliding mode state variable approaches the sliding surface in a limited convergence time; Exponential approach rate is used to approach the sliding surface by an exponential approach method; Defining a sliding surface function; Using a smooth switching function as the switching method of the sliding mode state variable; Based on the sliding surface, the exponential approach rate and the smooth switching function, a sliding mode controller is constructed, and a fuzzy controller is built by introducing a fuzzy intelligent control method; the fuzzy controller uses two-dimensional fuzzy control, and the fuzzy input quantity is the change amount and the change rate of the state variable approach speed.

[0005] Further, the nonlinear control algorithm has a calculation formula as follows: , ; In the formula, 、 respectively represent variables ， are the state variable and the controller variable of the system, represents time, n and m respectively represent real numbers.

[0006] Based on the sliding mode state variables approaching the sliding surface in a finite time, the constraints included are: 1) The motor control method has sliding mode; 2) Satisfy Lyapunov stability, that is, the state quantity satisfies the reachability condition ; 3) Sliding mode motion stability of motor control method.

[0007] Preferably, the formula for calculating the exponential convergence rate is: ; Where, , They represent the approach velocity increment of the moving point, represents the sliding mode approach rate, represents the sign function, and s represents the sliding surface function.

[0008] Finite convergence time , the state quantity of the motor tends to be stable in a limited time, and the time from the outside of the sliding surface to the sliding surface is t r , the calculation formula is: ; Furthermore, the calculation formula of the fast terminal sliding surface is: ; Where, represents the sliding surface function, Indicates error, represents the error change rate, where And it is a positive odd number.

[0009] The calculation formula of the fast terminal sliding mode controller is:

[0010] Where, Represents a controller function, represents the switching function increment, represents the smooth switching function, It is an adjustable parameter.

[0011] Preferably, the fuzzy controller introduces fuzzy control into a sliding mode algorithm to reduce the vibration of the motor and weaken the chattering phenomenon of the system.

[0012] Furthermore, constructing the fuzzy controller includes the following sub-steps: 1) Construct a single-variable two-dimensional fuzzy controller; 2) Define the fuzzy sets of error, error change and control quantity; 3) Define the membership function of input and output; 4) Establish fuzzy control rules and fuzzy control table; 5) According to the fuzzy reasoning calculation final control amount, get fuzzy set; 6) According to the process of fuzzy set to precise value inverse fuzzy.

[0013] Preferably, inverse fuzzy, including using Mamdani fuzzy algorithm and barycenter inverse fuzzy, the barycenter of the area surrounded by membership function curve and abscissa is the final output value of fuzzy reasoning.

[0014] Compared with the prior art, the beneficial effects of the present application include: 1) The novel SMC motor control method proposed in the present application, based on sliding surface, exponential approach rate and smooth switching function, constructs a sliding mode controller, reduces the vibration of the motor, thereby reducing the failure rate of the heat dissipation motor, improving the utilization rate of the unit, and reducing the loss of power generation of the unit.

[0015] 2) The novel SMC motor control method proposed in the present application realizes intelligent control effect of the motor through the design of fuzzy controller, introduces fuzzy control into sliding mode algorithm to realize sliding mode parameter self-tuning, and realizes intelligent control of motor speed to weaken the chattering phenomenon of the system.

[0016] 3) The novel SMC motor control method proposed in the present application does not need to install supporting bracket to reduce the vibration of the motor, reduces the maintenance cost, and reduces the volume and weight of the motor. BRIEF DESCRIPTION OF DRAWINGS

[0017] The present application will be further described below in combination with the drawings and examples.

[0018] Figure 1 The smooth switching function image of the novel SMC motor control method of the embodiment of the present application; Figure 2 The input membership function of the novel SMC motor control method of the embodiment of the present application; Figure 3 The input membership function of the novel SMC motor control method of the embodiment of the present application; Figure 4 The output membership function of the novel SMC motor control method of the embodiment of the present application; Figure 5 The SMC control speed waveform diagram of the embodiment of the present application; Figure 6 The FTISMC control speed waveform of the embodiment of the present application; Figure 7 The novel SMC motor control system framework diagram of the embodiment of the present application. ​​​DETAILED DESCRIPTION

[0019] To make the objectives, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings in the embodiments of the present invention.

[0020] Example 1 A novel SMC motor control method includes the following steps: Define the motor control using nonlinear control algorithm; Nonlinear control algorithm, the calculation formula is: , ; Where: 、 Represent variables respectively ， are the state variables and controller variables of the system, Indicates time, n and m Represent real numbers respectively.

[0021] Based on the sliding mode state variables approaching the sliding surface within a finite convergence time; Based on the sliding mode state variables approaching the sliding surface in a finite time, the constraints included are: 1) The motor control method has sliding mode; 2) Satisfy Lyapunov stability, that is, the state quantity satisfies the reachability condition ; 3) Sliding mode motion stability of motor control method.

[0022] The exponential approach rate is used to approach the sliding surface through the exponential approach method; The formula for calculating the exponential convergence rate is: ; Where, represents the sliding mode approach rate, represents the increment of the symbolic function, represents the symbolic function, represents the approach velocity increment, and s represents the sliding surface function.

[0023] Define the sliding surface function; A smooth switching function is used as the switching method of the sliding mode state quantity; like Figure 1 As shown in the figure, the smooth switching function sigmoid() is used as the state quantity switching mode. The slope of the curve is closely related to the value of parameter a. The larger the value of parameter a is, the steeper the sigmoid() switching function curve is. With the increase of the gain, the sigmoid switching function zero-crossing function curve is more jitter, and the control effect is worse.

[0024] For surface-mounted permanent magnet synchronous motor as the research object, the control mode is adopted The mathematical model of the motor is: ; Among them, for surface-mounted PMSM, are the inductance and current components of two-phase synchronous rotating coordinate system, is the amplitude of permanent magnet flux linkage, is the moment of inertia, is the number of motor pole pairs, is the load torque. is the q-axis stator voltage in the coordinate system.

[0025] The system state variables of PMSM are defined as: ; Among them, represents the system state variable, represents the rotor speed, represents the actual rotor speed of the motor. ; Let and be defined as: , ; The function calculation formula of sliding mode control is: ; Among them is the sliding mode design parameter, then the derivative can be obtained: ; When a=1 is set, substitute the above formula to obtain: The calculation formula of the control function is: ; Based on the sliding surface, the exponential approach rate, the smooth switching function is used to build the sliding mode controller, and the fuzzy intelligent control method is introduced to build the fuzzy controller; The fuzzy controller uses two-dimensional fuzzy control, and the fuzzy input is the state variable approach speed change and change rate.

[0026] The calculation formula of the sliding surface function is: ; Among them, represents , State variable , Parameter, i and n represent the calculation unit.

[0027] Limited convergence time , the state of the motor tends to be stable in a limited time, and the time of the sliding mode surface tends to the sliding mode surface is t r , the calculation formula is: ; The calculation formula of the fast terminal sliding mode surface is: ; The calculation formula of the fast terminal sliding mode controller is: ; The stability of the system is described by Lyapunov function, and the calculation formula is: ; In the formula, , the controller function is , the switching function increment is , the smooth switching function is , and the adjustable parameter is

[0028] According to Lyapunov function verification, it is obtained When the controller converges to 0 in a limited time, the control system converges.

[0029] The fuzzy controller introduces fuzzy control into the sliding mode algorithm, which is used to reduce the vibration of the motor and weaken the chattering phenomenon of the system.

[0030] The construction of fuzzy controller includes the following sub-steps: 1) Construct a single variable two-dimensional fuzzy controller; 2) Define the fuzzy sets of error, error change and control amount; 3) Define the membership function of input and output; 4) Establish fuzzy control rules and fuzzy control table; 5) Calculate the final control amount according to fuzzy reasoning, get fuzzy set; 6) According to the process of converting fuzzy set to precise value, defuzzification.

[0031] Defuzzification includes using Mamdani fuzzy algorithm and centroid defuzzification, which takes the centroid of the area surrounded by membership function curve and abscissa as the final output value of fuzzy reasoning.

[0032] The input and output of fuzzy controller are negative high NB, negative middle NM, negative low NS, zero ZO, positive low PS, positive middle PM and positive high PB, and the system input The input is [-4e-3, 4e-3], input is [-1e-3, 1e-3], and the system output is the sliding mode gain k corresponding to [1100, 1350].

[0033] As shown in Table 1, the designed fuzzy rule table is: Table 1

[0034] like Figure 2 、 Figure 3 and Figure 4 As shown in the figure, the seven fuzzy subsets of fuzzy control design are designed as seven fuzzy outputs at the same time. The system adopts Mamdani fuzzy algorithm and center of gravity defuzzification.

[0035] Fuzzy control consists of three parts: fuzzification, fuzzy reasoning, and defuzzification. In the fuzzy reasoning part, fuzzy rules and corresponding membership functions are designed. The system error and rate of change are input, and the relevant empirical control quantity is output after fuzzy reasoning.

[0036] (1) Fuzzification Fuzzification is to convert clear input into fuzzy language, so as to enter the next stage of fuzzy reasoning. The membership function includes several commonly used functions such as Gaussian, triangle, trapezoid, etc.

[0037] (2) Fuzzy reasoning The fuzzy rules and reasoning part connects the system input and outputs the corresponding empirical control quantities through fuzzy reasoning.

[0038] (3) Defuzzification This part converts the output of the fuzzy reasoning part into a numerical value that can be recognized by the system, including the center of gravity method, maximum membership method, etc.

[0039] Fuzzy control generally adopts one-dimensional or two-dimensional control. Control with three or more dimensions is more complicated and is generally not commonly used. Of course, the higher the dimension, the higher the accuracy of the change it can reflect. The input of the system in this paper is the change amount and change rate, so two-dimensional fuzzy control is adopted.

[0040] The present invention sets the rotation speed to 1000 r / min and performs simulation through Matlab, and its SMC and FTISMC control system simulation waveforms.

[0041] like Figure 5 As shown, the SMC control algorithm is used to improve the motor control performance, and its output speed fluctuation is small. The present invention adopts a fast terminal sliding mode control system, which further improves its control effect, reduces the vibration of the motor and reduces the overshoot.

[0042] like Figure 6As shown, the FTISMC control algorithm is used to realize the operation mode with no overshoot and small speed fluctuation, has good control performance, reduces the rotation of the motor, and further reduces the failure rate of the motor.

[0043] Compared with the SMC control mode, the FTISMC control mode can realize no overshoot control, has smaller speed fluctuation, and has better control effect.

[0044] Embodiment 2 As Figure 7 shown, the embodiment discloses a novel SMC motor control system, including the following steps: S1, collect the three-phase current values of the motor running state, and convert the three-phase stationary coordinate system into the two-phase stationary coordinate system through the Clark transformation; S2, convert into the two-phase rotating coordinate system through the Park transformation, and control the motor close to the direct current motor; S3, control through the current inner loop and the speed outer loop mode by using the obtained d-axis current id and q-axis current iq, and design the speed controller; S4, detect the motor speed through the encoder, and control according to the speed controller to obtain the q-axis reference current iqref; S5, control the rotation of the motor through the current inner loop control and the SVPWM control three-phase inverter; It is particularly pointed out that the above examples are only part of the preferred examples of the present application, the present application has been described in detail with reference to the above embodiments, and those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced, and any modification or replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A novel SMC motor control method, characterized in that: The following steps are involved: Define the motor control using nonlinear control algorithm; Based on the sliding mode state variables approaching the sliding surface within a finite convergence time; The exponential approach rate is used to approach the sliding surface through the exponential approach method; Define the sliding surface function; A smooth switching function is used as the switching method of the sliding mode state quantity; A sliding mode controller is constructed based on the sliding surface, exponential approach rate and smooth switching function, and a fuzzy intelligent control method is introduced to build a fuzzy controller; the fuzzy controller adopts two-dimensional fuzzy control, and the fuzzy input is the change amount and rate of approach speed of the state variable.

2. A novel SMC motor control method according to claim 1, characterized in that: The nonlinear control algorithm is calculated as follows: ， ； Its sliding surface function is: ； Where, 、 Represent variables respectively ， are the state variables and controller variables of the system, Indicates time, n and m represent real numbers respectively.

3. The novel SMC motor control method according to claim 1, characterized in that: The constraints involved in the approach of the sliding mode state variable to the sliding mode surface within a finite time are as follows: 1) The motor control method has sliding mode; 2) Satisfy Lyapunov stability, that is, the state quantity satisfies the reachability condition ; 3) Sliding mode motion stability of motor control method.

4. The novel SMC motor control method according to claim 1, characterized in that: The calculation formula of the exponential convergence rate is: ； Where, represents the sliding mode approach rate, represents the increment of the symbolic function, represents the symbolic function, represents the approach velocity increment, and s represents the sliding surface function.

5. The novel SMC motor control method according to claim 1, characterized in that: The finite convergence time is the time in which the state quantity of the motor tends to be stable. The time from the outside of the sliding surface to the sliding surface is t r , the calculation formula is: ； Where, And it is a positive odd number.

6. A novel SMC motor control method according to claim 1, characterized in that: The calculation formula of the fast terminal sliding surface is: ； Where, represents the sliding surface function, Indicates error, Indicates the rate of change of error.

7. A novel SMC motor control method according to claim 1, characterized in that: The calculation formula of the fast terminal sliding mode controller is: ； ； Where, Represents a controller function, represents the switching function increment, represents the smooth switching function, It is an adjustable parameter.

8. The novel SMC motor control method according to claim 1, characterized in that: The fuzzy controller introduces fuzzy control into the sliding mode algorithm to reduce the vibration of the motor and weaken the chattering phenomenon of the system.

9. A novel SMC motor control method according to claim 8, characterized in that: The construction of the fuzzy controller includes the following sub-steps: 1) Construct a single-variable two-dimensional fuzzy controller; 2) Define the fuzzy sets of error, error change and control quantity; 3) Define the membership function of input and output; 4) Establish fuzzy control rules and fuzzy control tables; 5) Calculate the final control quantity based on fuzzy reasoning and obtain the fuzzy set; 6) Defuzzification based on the process of converting fuzzy sets into exact values.

10. A novel SMC motor control method according to claim 9, characterized in that: The defuzzification includes adopting Mamdani fuzzy algorithm and centroid defuzzification, and taking the centroid of the area enclosed by the membership function curve and the horizontal coordinate as the final output value of the fuzzy reasoning.

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