Simulation and Stability Analysis of SRM Speed Control System Based on Fuzzy Self-Tuning PID
A dynamic simulation model for SRM (switched reluctance motor) speed control system based on fuzzy self-tuning PID is established in the environment of MATLAB/Simulink. Comparing with the result of the SRM speed control system based on conventional PID, t
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Simulation and Stability Analysis of SRM Speed Control System Based on Fuzzy Self-Tuning PID Jialiang Gan and Zhimin Li
Abstract A dynamic simulation model for SRM (switched reluctance motor) speed control system based on fuzzy self-tuning PID is established in the environment of MATLAB/Simulink. Comparing with the result of the SRM speed control system based on conventional PID, the performance of SRM speed control system by fuzzy self-tuning PID control algorithm is obviously better. Stability analysis for the SRM speed control system is carried out by using a new stability criterion for nonlinear time-invariant systems.
Keywords Switched reluctance motor Fuzzy self-tuning PID control control system Simulation Stability analysis
Speed
79.1 Introduction Switched Reluctance Drive (SRD) is a new speed control system, which avoids both the commutation spark of the DC motor while reversing and complex structure of AC motor with high cost. The SRD with the advantages of speed control of both the DC motor and the AC motor has high output and high energy efficiency. Although its electromagnetic principle and structure are quite simple, the SRD can’t get an ideal control result with the conventional PID control algorithm because it is a timing-variable, nonlinear, multivariate system. Fuzzy control is a typical intelligent control, which has a strong adaptability to nonlinear
J. Gan (&) Z. Li School of Computer and Information Science, HuBei Engineering University, Xiaogan 432100, China e-mail: [email protected]
W. Lu et al. (eds.), Proceedings of the 2012 International Conference on Information Technology and Software Engineering, Lecture Notes in Electrical Engineering 211, DOI: 10.1007/978-3-642-34522-7_79, Ó Springer-Verlag Berlin Heidelberg 2013
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parameters that changes in the speed control application. In order to improve the performance of switched reluctance motor speed control, the fuzzy algorithm and the PID algorithm are combined to make the fuzzy self-tuning PID control algorithm that has the advantages of both.
79.2 The Mathematical Model of Switched Reluctance Motor System There are three popular methods to solve the basic equation of the SRM: linearization, quasi linearization and nonlinear linearization. The linearization method simplifies the parameters of the SRM and emphasizes the basic physical characteristics of the SRM [1]. Although the precision of linearization is relatively lower, the relationship between the basic characteristics of the SRM and parameters can be understood with analysis of the approximate analytic expression. The variables of the analytical formula of SRM are solved by the linearization in this paper with the following equations [2]. (1) Circuit equation dwk dt
ð79:1Þ
wk ¼ Lk ðhk ; ik Þik
ð79:2Þ
Uk ¼ R k ik þ (2) Flux equations
(3) Mechanical equation Te ¼ J
d2 h dh þ D þ TL dt dt
ð79:3Þ
Which the angular velocity of the rotor: dh ¼x dt
ð79:4Þ
(4) Equation of mechanical and electrical contact 0
Te ¼
oWm ðh; i1 ; i2 ;
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