Title :
A fuzzy control scheme for nonlinear systems and its application to power systems
Author :
Tan, Xiaobo ; Zhang, Naiyao ; Tong, Luyuan ; Wang, Zhonghong
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
The Takagi-Sugeno model (T-S model) based fuzzy control scheme for nonlinear systems is presented in this paper. In the T-S fuzzy model, a nonlinear system is represented with a set of fuzzy rules which describe the local linear dynamics. Then the parallel distributed compensation (PDC) design is employed in the fuzzy controller design. Linear optimal control is used in the derivation of each control rule. The overall fuzzy controller is a fuzzy blending of each individual linear controller. Quadratic stability of the overall nonlinear control system can be checked and ensured with H∞ control theory. The fuzzy control scheme is applied to thyristor-controlled series compensator control in power system transients. Digital simulations with NOTOMAC software have demonstrated that the fuzzy control scheme is superior to other conventional control methods. The fuzzy controller effectively improves power systems transient stability and very quickly damp power swings
Keywords :
H∞ control; compensation; control system synthesis; fuzzy control; linear systems; nonlinear control systems; optimal control; power system control; power system transients; stability; H∞ control theory; NOTOMAC software; T-S fuzzy model; Takagi-Sugeno model; control rule; damping; digital simulation; fuzzy control; fuzzy controller design; fuzzy rules; linear controller; linear optimal control; local linear dynamics; nonlinear systems; parallel distributed compensation; power system transients; power systems; power systems transient stability; quadratic stability; thyristor-controlled series compensator control; Control systems; Fuzzy control; Fuzzy sets; Fuzzy systems; Nonlinear systems; Optimal control; Power system control; Power system stability; Power system transients; Takagi-Sugeno model;
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
DOI :
10.1109/ICIPS.1997.672782