Title :
Stability Analysis of Fuzzy Control for Nonlinear Systems
Author :
Chen, Po-Chen ; Yeh, Ken ; Chen, Cheng-Wu ; Lin, Shu-Hao
Author_Institution :
Dept. of Civil Eng., Nat. Central Univ., Jhongli, Taiwan
Abstract :
In this study, we propose a method of stability analysis for a GA-based reference ANNC capable of handling these types of problems for a nonlinear system. The initial values of the consequent parameter vector are decided via a genetic algorithm (GA) after which a modified adaptive law is derived based on Lyapunov stability theory to control the nonlinear system for tracking a user-defined reference model. The requirement of Kalman-Yacubovich lemma is fulfilling. A boundary-layer function is introduced into these updating laws to cover parameter and modeling errors, and to guarantee that the state errors converge into a specified error bound. After this, an adaptive neural network controller (ANNC) is derived to simultaneously stabilize and control the system.
Keywords :
Lyapunov methods; adaptive control; fuzzy control; genetic algorithms; neurocontrollers; nonlinear control systems; stability; GA-based reference ANNC; Kalman-Yacubovich lemma; Lyapunov stability theory; adaptive neural network controller; boundary-layer function; consequent parameter vector; error bound; fuzzy control; genetic algorithm; modeling error; modified adaptive law; nonlinear system; parameter error; stability analysis; state error; user-defined reference model; Adaptive control; Control system synthesis; Control systems; Fuzzy control; Genetic algorithms; Lyapunov method; Nonlinear control systems; Nonlinear systems; Programmable control; Stability analysis; Genetic algorithm; Neural network;
Conference_Titel :
Intelligent Information and Database Systems, 2009. ACIIDS 2009. First Asian Conference on
Conference_Location :
Dong Hoi
Print_ISBN :
978-0-7695-3580-7
DOI :
10.1109/ACIIDS.2009.83
