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Fuzzy adaptive sliding mode control method and system based on differential evolution algorithm optimization

A differential evolution algorithm and fuzzy self-adaptive technology, applied to control systems, vector control systems, control generators, etc., can solve problems such as the complexity of the design process, and achieve the effect of improving robustness and reducing chattering

Active Publication Date: 2020-06-02
ZHEJIANG SCI-TECH UNIV
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Problems solved by technology

[0006] The embodiment of the present application provides a fuzzy self-adaptive sliding mode control method and system based on differential evolution algorithm optimization, which solves the problem of complicated design process of the existing method, constant value of sliding mode gain, and chattering when the system is disturbed by the outside world. For technical problems arising in varying degrees, the intelligent algorithm is used to study the optimized sliding mode algorithm, so that the sliding mode gain can be adaptively adjusted according to external changes, which can effectively improve the robustness, stability and rapidity of the permanent magnet synchronous motor controller , effectively reduce chattering phenomenon

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  • Fuzzy adaptive sliding mode control method and system based on differential evolution algorithm optimization
  • Fuzzy adaptive sliding mode control method and system based on differential evolution algorithm optimization
  • Fuzzy adaptive sliding mode control method and system based on differential evolution algorithm optimization

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Embodiment 1

[0076] figure 1 and figure 2 They are respectively the step flow chart and schematic diagram of the fuzzy adaptive sliding mode control method based on differential evolution algorithm optimization provided in Embodiment 1 of the present application, and the described fuzzy adaptive sliding mode control method based on differential evolution algorithm optimization includes the following steps :

[0077] Step S1, establishing the sliding mode speed controller model of the permanent magnet synchronous motor, and deriving the speed control law;

[0078] use i d = 0 rotor field oriented control method, i d Indicates the DC current of the permanent magnet synchronous motor. In order to ensure that the three-phase PMSM drive system has better dynamic quality, the exponential reaching law method is used to obtain the control law of the sliding mode speed controller of the permanent magnet synchronous motor as follows:

[0079]

[0080] In formula (1), D is the motor paramete...

Embodiment 2

[0117] Based on the method in Embodiment 1, this embodiment provides a fuzzy adaptive sliding mode control system optimized based on differential evolution algorithm.

[0118] Figure 9 It is a schematic structural diagram of the fuzzy adaptive sliding mode control system optimized based on the differential evolution algorithm provided in this embodiment. The fuzzy adaptive sliding mode control system optimized based on the differential evolution algorithm includes a PMSM module, a coordinate transformation module, and a differential evolution algorithm. Algorithm-optimized fuzzy sliding mode controller, torque current regulator, excitation current regulator, SVPWM module, three-phase inverter, sensor module, etc.

[0119] combine Figure 10 ,in,

[0120] Permanent magnet synchronous motor PMSM, used to output three-phase winding current i a i b i c ;

[0121] A coordinate transformation module, including a Clark transformation module, a Park transformation module and a ...

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Abstract

The invention discloses a fuzzy adaptive sliding mode control method and system based on differential evolution algorithm optimization. The method comprises the steps of firstly, building a permanentmagnet synchronous motor sliding mode speed controller model, and deriving a speed control law; calculating speed deviation and a sliding mode surface; digitally representing a fuzzy rule; fuzzing thesliding mode surface and the derivative thereof as input; looking up an initial fuzzy rule table; performing defuzzification on the to-be-optimized parameters to serve as output; and finally, calculating the output of the controller, carrying out optimization selection on the fuzzy rule by using a differential evolution algorithm until the optimal index is converged to the minimum value, and selecting an optimal fuzzy rule table. According to the invention, the fuzzy rule in the fuzzy sliding mode controller is optimized by using the differential evolution algorithm, optimal adjustment of gain parameters in the exponential reaching law in the sliding mode algorithm is automatically achieved, the permanent magnet synchronous motor sliding mode controller which is rapid in response, small in overshoot and good in robustness is designed, and the requirements of the field with high performance requirements for a permanent magnet synchronous motor speed regulation system are met.

Description

technical field [0001] The invention relates to a fuzzy self-adaptive sliding mode control method and system based on differential evolution algorithm optimization, belonging to the technical field of AC motor control. Background technique [0002] The permanent magnet synchronous motor is a nonlinear, strongly coupled multivariable system, which requires high control precision and strong system stability in practical applications. The traditional PI control method cannot meet the actual requirements, and the PI parameters are set blindly and cannot be adjusted adaptively according to external changes. In contrast, the sliding mode control algorithm can adjust the voltage output according to the current state of the motor (such as deviation and its derivatives, etc.), forcing the system to move according to the predetermined "sliding mode" state trajectory. [0003] The permanent magnet synchronous motor system itself has many unfavorable factors such as complexity and nonl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02P21/00H02P21/05H02P21/18
CPCH02P21/0007H02P21/0017H02P21/05H02P21/18
Inventor 郭亮郑超丁浩
Owner ZHEJIANG SCI-TECH UNIV
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