Adaptive control using interval Type-2 fuzzy logic for uncertain nonlinear systems  

作　　者：周海波 应浩 段吉安 

机构地区：[1]School of Mechanical and Electrical Engineering,Central South University [2]State Key Laboratory of High Performance and Complex Manufacturing,Central South University [3]Department of Electrical and Computer Engineering,Wayne State University

出　　处：《Journal of Central South University》2011年第3期760-766,共7页中南大学学报（英文版）

基　　金：Project(51005253) supported by the National Natural Science Foundation of China;Project(2007AA04Z344) supported by the National High Technology Research and Development Program of China

摘　　要：A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.A new adaptive Type-2 (T2) fuzzy controller was developed and its potential performance advantage over adaptive Type-1 (T1) fuzzy control was also quantified in computer simulation.Base on the Lyapunov method,the adaptive laws with guaranteed system stability and convergence were developed.The controller updates its parameters online using the laws to control a system and tracks its output command trajectory.The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance.And the comparison simulation experiments subjected to white noise or step disturbance indicate that the T2 controller is better than the T1 controller by 0-18%,depending on the experiment condition and performance measure.

关 键 词：Type-2 fuzzy systems adaptive fuzzy control nonlinear systems stability 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]