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Machine Intelligence Research

Erschienen in:

01.08.2013

Observer-based Adaptive Fuzzy Control for a Class of Nonlinear Time-delay Systems

verfasst von: Hassan A. Yousef, Mohamed Hamdy

Erschienen in: Machine Intelligence Research | Ausgabe 4/2013

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Abstract

An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.

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Titel: Observer-based Adaptive Fuzzy Control for a Class of Nonlinear Time-delay Systems
verfasst von: Hassan A. Yousef
Mohamed Hamdy
Publikationsdatum: 01.08.2013
Verlag: Springer-Verlag
Erschienen in: Machine Intelligence Research / Ausgabe 4/2013
Print ISSN: 2731-538X
Elektronische ISSN: 2731-5398
DOI: https://doi.org/10.1007/s11633-013-0721-1

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