Paper Info
Title
Indirect adaptive fuzzy-neural control with observer and supervisory control for unknown nonlinear systems
Abstract
In this paper, we develop an observer-based indirect adaptive fuzzy-neural controller with supervisory mode for a certain class of high order unknown nonlinear dynamical system. The free parameters of the adaptive fuzzy-neural controller with supervisory mode can be tuned on-line by an observer-based output feedback control law and adaptive law, based on the Lyapunov synthesis approach. The fuzzy controller is appended with a supervisory controller. If the fuzzy control system tends to unstable, the supervisory controller starts working to guarantee stability. From the energy point of view, this is a very economical design methodology. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded.
Year
DOI
Venue
2001
10.1109/FUZZ.2001.1009095
Fuzzy Systems, 2001. The 10th IEEE International Conference  
Keywords
Field
DocType
lyapunov methods,adaptive control,closed loop systems,control system synthesis,feedback,fuzzy control,fuzzy neural nets,neurocontrollers,nonlinear control systems,nonlinear dynamical systems,observers,stability,uncertain systems,lyapunov synthesis approach,adaptive law,closed-loop system,free parameters,global stability,high-order unknown nonlinear dynamical system,indirect adaptive fuzzy-neural control,observer,observer-based output feedback control law,supervisory control,uniformly bounded signals,design methodology,electrical engineering,nonlinear system
Lyapunov function,Control theory,Separation principle,Supervisory control,Control theory,Computer science,Fuzzy logic,Adaptive control,Fuzzy control system,Observer (quantum physics)
Conference
Volume
Citations 
PageRank 
2
0
0.34
References 
Authors
3
4
Name
Order
Citations
PageRank
C. Wang158247.29
Tsung-Chih Lin236126.73
Han-Leih Liu326513.06
Tsu-Tian Lee,4252.79