Paper Info
Title
Observer-based indirect adaptive supervisory control for unknown time delay system
Abstract
This paper proposes an indirect adaptive fuzzy neural network controller with state observer and supervisory controller for a class of uncertain nonlinear dynamic time-delay systems. The approximate function of unknown time delay system is inferred by the adaptive time delay fuzzy logic system. The supervisory controller, which can be combined with fuzzy neural network controller, will work when error dynamics is great than a constant which is determined by designer. Therefore, if the system is unstable, the supervisory controller will force the state to be stable. The free parameters of the indirect adaptive fuzzy controller can be tuned on-line by observer based output feedback control law and adaptive laws by means of Lyapunov stability criterion. The resulting of simulation example shows that the performance of nonlinear time-delay chaotic system is fully tracking the reference trajectory. Meanwhile simulation results show that the adaptive control effort of the proposed control scheme is much less due to the assist of the supervisory controller.
Year
DOI
Venue
2014
10.1109/FUZZ-IEEE.2014.6891631
FUZZ-IEEE
Keywords
DocType
ISSN
observers,indirect adaptive fuzzy neural network controller,observer-based indirect adaptive supervisory control,neurocontrollers,error dynamics,lyapunov stability criterion,adaptive time delay fuzzy logic system,adaptive control,control system synthesis,observer and supervisory control,nonlinear time delay systems,delays,feedback,state observer,fuzzy neural network controller,fuzzy control,unknown time delay system,observer based output feedback control law,stability,fuzzy neural networks (fnn),lyapunov methods,vectors
Conference
1544-5615
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Ting-Ching Chu100.34
Tsung-Chih Lin236126.73
Valentina Emilia Balas319537.08