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Erschienen in: Neural Computing and Applications 4/2018

09.12.2016 | Original Article

Observer-based hybrid adaptive fuzzy control for affine and nonaffine uncertain nonlinear systems

verfasst von: Hesam Fallah Ghavidel, Ali Akbarzadeh Kalat

Erschienen in: Neural Computing and Applications | Ausgabe 4/2018

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Abstract

This paper presents a novel observer-based hybrid adaptive fuzzy controller for affine and nonaffine nonlinear systems with external disturbance. The suggested design is so easy and does not need a mathematical model for system under control and also it is very simple, efficient and robust. Based on the adaptive method and the system states observer, an observer-based adaptive fuzzy method is proposed to control an uncertain nonlinear system. Also, a supervisory controller term is employed to attenuate the residual error to a desired level and compensate the both uncertainties and observer errors. Although proposed control method needs the uncertainties to be bounded, it does not need this bound to be identified. Stability of the proposed method is shown based on Lyapunov theory and also the strictly positive real condition if all the implicated signals are uniformly bounded. Finally, in our simulation studies, to demonstrate the usefulness and efficiency of the suggested technique, an uncertain nonlinear system is employed.

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Metadaten
Titel
Observer-based hybrid adaptive fuzzy control for affine and nonaffine uncertain nonlinear systems
verfasst von
Hesam Fallah Ghavidel
Ali Akbarzadeh Kalat
Publikationsdatum
09.12.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 4/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2732-7

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