Paper Info
Title
Run-time efficient observer-based fuzzy-neural controller for nonaffine multivariable systems with dynamical uncertainties
Abstract
In this paper, a novel hierarchical structure with run-time efficiency is developed to solve the rule explosion problem of fuzzy-neural network control for a class of uncertain nonaffine multivariable systems. The parameters of the hybrid adaptive controller are on-line tuned by the derived update laws under the constraint that only system outputs are available for measurement. Compared with the previous approaches, the proposed design process is more flexible and requires less computation time. According to the stability analysis, the overall control scheme guarantees that the closed-loop systems can obtain successful system control, effective state observer, and desired tracking performance. Finally, illustrative examples are provided to show the effectiveness of the proposed approach.
Year
DOI
Venue
2016
10.1016/j.fss.2015.12.008
Fuzzy Sets and Systems
Keywords
Field
DocType
Run-time efficiency,Trajectory-tracking control,Fuzzy-neural controller,Nonaffine multivariable systems
State observer,Control theory,Multivariable calculus,Control theory,Fuzzy neural,Control system,Design process,Observer (quantum physics),Mathematics,Computation
Journal
Volume
Issue
ISSN
302
C
0165-0114
Citations 
PageRank 
References 
0
0.34
27
Authors
3
Name
Order
Citations
PageRank
Yi-Hsing Chien1898.33
Wei-Yen Wang299587.40
Chen-Chien Hsu310213.52