Neural networks based nonlinear H∞control for linear switched reluctance motor

Huiyan Li; Yuliang Liu; Jiang Wang; Y. K. Wong; Wai Lok Chan

Neural networks based nonlinear H_∞control for linear switched reluctance motor

Huiyan Li, Yuliang Liu, Jiang Wang, Y. K. Wong, Wai Lok Chan

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

This paper is concerned with H∞control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H∞tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external disturbance and NNs approximation error to a prescribed level. Furthermore, theoretical results are applied to a position tracking control of linear switched reluctance motor. Simulation studies are included to demonstrate the effectiveness of the method.

Original language	English
Title of host publication	Proceedings of 2009 7th Asian Control Conference, ASCC 2009
Pages	796-801
Number of pages	6
Publication status	Published - 11 Dec 2009
Event	2009 7th Asian Control Conference, ASCC 2009 - Hong Kong, Hong Kong Duration: 27 Aug 2009 → 29 Aug 2009

Conference

Conference	2009 7th Asian Control Conference, ASCC 2009
Country/Territory	Hong Kong
City	Hong Kong
Period	27/08/09 → 29/08/09

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Vision and Pattern Recognition
Control and Systems Engineering

Cite this

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title = "Neural networks based nonlinear H∞control for linear switched reluctance motor",

abstract = "This paper is concerned with H∞control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H∞tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external disturbance and NNs approximation error to a prescribed level. Furthermore, theoretical results are applied to a position tracking control of linear switched reluctance motor. Simulation studies are included to demonstrate the effectiveness of the method.",

author = "Huiyan Li and Yuliang Liu and Jiang Wang and Wong, {Y. K.} and Chan, {Wai Lok}",

year = "2009",

month = dec,

day = "11",

language = "English",

isbn = "9788995605691",

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T1 - Neural networks based nonlinear H∞control for linear switched reluctance motor

AU - Li, Huiyan

AU - Liu, Yuliang

AU - Wang, Jiang

AU - Wong, Y. K.

AU - Chan, Wai Lok

PY - 2009/12/11

Y1 - 2009/12/11

N2 - This paper is concerned with H∞control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H∞tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external disturbance and NNs approximation error to a prescribed level. Furthermore, theoretical results are applied to a position tracking control of linear switched reluctance motor. Simulation studies are included to demonstrate the effectiveness of the method.

AB - This paper is concerned with H∞control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H∞tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external disturbance and NNs approximation error to a prescribed level. Furthermore, theoretical results are applied to a position tracking control of linear switched reluctance motor. Simulation studies are included to demonstrate the effectiveness of the method.

UR - http://www.scopus.com/inward/record.url?scp=71449088259&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 9788995605691

SP - 796

EP - 801

BT - Proceedings of 2009 7th Asian Control Conference, ASCC 2009

T2 - 2009 7th Asian Control Conference, ASCC 2009

Y2 - 27 August 2009 through 29 August 2009

ER -

Neural networks based nonlinear H_∞control for linear switched reluctance motor

Abstract

Conference

ASJC Scopus subject areas

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