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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 3/2015

01.04.2015 | Original Article

Soft variable structure controller design for constrained systems based on S-class functions

verfasst von: Yunlong Liu, Shanmao Gu, Yonggui Kao, Shuhong Tang

Erschienen in: Neural Computing and Applications | Ausgabe 3/2015

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Abstract

A soft variable structure control (SVSC) strategy based on S-class functions is addressed in this paper. Firstly, the definition of SVSC strategy is given, the structure of SVSC system under constrained control input is analyzed, and S-class functions with smoothness, strict monotonicity, and saturation are presented. Secondly, the sufficient condition on the stability of SVSC system is obtained by Lyapunov stability theory. A soft variable structure controller based on S-class functions is developed aiming at optimizing the smoothness problem of the SVSC systems based on variable saturations, and the chattering problem of sliding mode control (SMC) systems. Then, the concrete algorithm on SVSC strategy based on sigmoid functions is obtained. Finally, a simulation example is carried out to verify the feasibility and effectiveness of the SVSC strategy, and compared with SMC strategy, high regulation rate is achieved, settling time is shorted, and the system chattering can be reduced by the proposed strategy.
Vorheriger Artikel Solving time-varying quadratic programs based on finite-time Zhang neural networks and their application to robot tracking
Nächster Artikel A chaos embedded GSA-SVM hybrid system for classification

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Metadaten
Titel
Soft variable structure controller design for constrained systems based on S-class functions
verfasst von
Yunlong Liu
Shanmao Gu
Yonggui Kao
Shuhong Tang
Publikationsdatum
01.04.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 3/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1748-0

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