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Neural Computing and Applications

Erschienen in:

01.12.2013 | Original Article

Observer-based fuzzy adaptive control of nonlinear systems with actuator faults and unmodeled dynamics

verfasst von: Yinyin Xu, Shaocheng Tong, Yongming Li

Erschienen in: Neural Computing and Applications | Sonderheft 1/2013

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Abstract

In this paper, an adaptive fuzzy output feedback fault-tolerant control scheme is developed for a class of nonlinear systems with actuator faults, unmodeled dynamics and without assuming the states being available for control design. Fuzzy logic systems are employed to approximate unknown nonlinear functions, and a fuzzy state observer is established to estimate the unmeasured states. By combining adaptive backstepping technique with changing supplying function technique and the nonlinear fault-tolerant control theory, a novel adaptive fuzzy fault-tolerant output feedback control approach is developed. It is proved that proposed control approach guarantees that all the variables of the closed-loop system are bounded. The simulation results are provided to illustrate the effectiveness of the proposed control approach. Compared with the existing results, the main contributions of this paper are as follows: (1) the proposed control method removes the restrictive assumption that all the states of the controlled system be measured directly; and (2) the proposed control method cannot only compensate for the actuator faults, but also solve the problem of the unmodeled dynamics.

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Titel: Observer-based fuzzy adaptive control of nonlinear systems with actuator faults and unmodeled dynamics
verfasst von: Yinyin Xu
Shaocheng Tong
Yongming Li
Publikationsdatum: 01.12.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe Sonderheft 1/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-013-1495-7

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