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Equivalent sliding mode controller for ball and plate system based on RBF optimized by PSO

Xu, Yunyun and Dong, Xiucheng and Shi, Peng (2012) Equivalent sliding mode controller for ball and plate system based on RBF optimized by PSO. ICIC Express Letters, 6 (2). pp. 517-522. ISSN 1881-803X

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Abstract

This paper presented an equivalent sliding mode control based on a radial basis function (RBF) neural network optimized by partical swarm optimization (PSO) for the trucking control of the ball and plate system. Thus the advantage that RBF neural network could approach any function was played, and the robustness of sliding mode control (SMC) was retained. Simulation results show that the method has strong robustness and tracking error is smaller.

Item Type: Article
Uncontrolled Keywords: ResPubID25080, ResPubID25783, ball and plate system, control system, under-actuated system, sliding mode control, trajectory tracking, nonlinear system, neural network, robust design, learning speed
Subjects: FOR Classification > 0801 Artificial Intelligence and Image Processing
FOR Classification > 0802 Computation Theory and Mathematics
FOR Classification > 0913 Mechanical Engineering
SEO Classification > 970101 Expanding Knowledge in the Mathematical Sciences
Faculty/School/Research Centre/Department > School of Engineering and Science
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Depositing User: VUIR
Date Deposited: 20 Mar 2013 02:58
Last Modified: 22 Jul 2014 06:19
URI: http://vuir.vu.edu.au/id/eprint/10460
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Citations in Scopus: 3 - View on Scopus

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