DocumentCode :
3098931
Title :
Application of Fuzzy Control in Switched Reluctance Motor Speed Regulating System
Author :
Liu, Weiguo ; Song, Shoujun
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xian
fYear :
2006
fDate :
Nov. 28 2006-Dec. 1 2006
Firstpage :
72
Lastpage :
72
Abstract :
The applications of switched reluctance motors have being increased day by day, but it is a multivariable and strong-coupling highly nonlinear system, there are lots of difficulties to build its model. In this paper, combining with the quasi-linear model brought forward by Miller, the small-signal dynamic model of the switched reluctance motor is built based on matlab/simulink environment. This model is very suitable for research of control strategies. In industrial automation fields, conventional PID control is acting a very important role, but its robustness is very weak. In this paper, on the basis of conventional PID controller, fuzzy control technique is introduced. Two improved PID controller are proposed: Fuzzy_PID compound control and fuzzy parameters self-tuning PID control. The former combines the advantages of PID and fuzzy control, while the latter uses fuzzy technique to adjust the parameters of PID controller dynamically. The simulation results show that the two control strategies can not only improve the dynamic and static performances of the system effectively, but also enhance robustness of the system.
Keywords :
fuzzy control; machine control; nonlinear control systems; reluctance motors; robust control; self-adjusting systems; velocity control; Matlab/Simulink environment; control strategy; conventional PID control; fuzzy control; fuzzy parameters self-tuning PID control; industrial automation fields; nonlinear system; quasilinear model; robustness; switched reluctance motor speed regulating system; switched reluctance motors; Automatic control; Diversity reception; Electrical equipment industry; Fuzzy control; Mathematical model; Nonlinear dynamical systems; Nonlinear systems; Reluctance motors; Robust control; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7695-2731-0
Type :
conf
DOI :
10.1109/CIMCA.2006.48
Filename :
4052713
Link To Document :
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