Optimal learning tracking control for nonlinear systems

J. S.H. Tsai, G. R. Chen, C. Y. Lin, S. M. Guo, T. J. Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, an improved-type learning control mechanism is proposed to design an optimal tracker for a nonlinear system. Even without the detailed information on the system, the proposed mechanism also yields the optimal learning tracker. In order to achieve the output tracking design, the optimal linearized models of the nonlinear system at operating states are obtained by the optimal linearization approach, so that the well-designed learning mechanism for linear systems can be extended to the nonlinear case. How the eigenspectrums of linearized models significantly affect the effectiveness of the optimal learning control mechanism has been investigated in this paper, and the pole placement method is used to improve the drawback of learning control. Illustrative examples are presented to demonstrate the effectiveness of the proposed methodology.

Original languageEnglish
Title of host publicationWMSCI 2008 - The 12th World Multi-Conference on Systemics, Cybernetics and Informatics, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008 - Proc.
Pages99-104
Number of pages6
Publication statusPublished - 2008
Event12th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2008, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008 - Orlando, FL, United States
Duration: 2008 Jun 292008 Jul 2

Publication series

NameWMSCI 2008 - The 12th World Multi-Conference on Systemics, Cybernetics and Informatics, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008 - Proc.
Volume4

Other

Other12th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2008, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008
Country/TerritoryUnited States
CityOrlando, FL
Period08-06-2908-07-02

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

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