Adaptive Control of Nonlinear Discrete-Time System by Least Square Support Vector Machine

Author

Xu, Jian-Qiang ; Wang, Jian-Jun ; Zhu, Jun ; Chen, Shu-Zhong

Author_Institution

Center of Mathematics and Physics Teaching, Shanghai Institute of Technology, Shanghai 200233, China; Department of Computer Science and Technology, East China Normal University, Shanghai 200062, China E-MAIL: jqxu@citiz.net

Volume

1

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

544

Lastpage

548

Abstract

In this paper we introduce the use of recurrent least square support vector machine algorithm for the adaptive control of a class of nonlinear discrete-time systems. The curse of dimensionality is avoided by using the finite time window. Advantage of the newly designed algorithm is that the computation of inverse matrix is avoided. Simulation results also verify the effectiveness of the algorithm.

Keywords

Nonlinear discrete-time system; adaptive control and least square support vector machine; Adaptive control; Algorithm design and analysis; Equations; Iterative algorithms; Least squares approximation; Least squares methods; Multi-layer neural network; Neural networks; Support vector machine classification; Support vector machines; Nonlinear discrete-time system; adaptive control and least square support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527004

Filename

1527004