Output feedback tracking control of MIMO systems using a fuzzy disturbance observer and its application to the speed control of a PM synchronous motor

Euntai Kim, Sungryul Lee

Research output: Contribution to journalArticlepeer-review

87 Citations (Scopus)

Abstract

One of the most important objectives in the design of control systems is to achieve the good tracking performance in the presence of the internal parameter uncertainty and external disturbance. In this paper, a new multiple-input-multiple-output (MIMO) fuzzy disturbance observer (FDO) based on output measurement is developed to achieve the goal. A filtered signal is introduced to resolve the algebraic loop encountered in the conventional FDO. The contribution of the disturbance observation error ζ to updating the parameters of the fuzzy system is analyzed in the sense of L2 and L. Then, the MIMO FDO is modified and the high gain observer (HGO) is employed to implement the output tracking control system. It is shown in a rigorous manner that the disturbance observation error, the tracking error and the state observation error converge to a compact set of which size can be kept arbitrarily small. Finally, the suggested method is applied to the speed control of a permanent magnet synchronous motor (PMSM) in the presence of the internal parameter uncertainty and external disturbance. The effectiveness and the feasibility of the suggested method are demonstrated by computer simulation.

Original languageEnglish
Pages (from-to)725-741
Number of pages17
JournalIEEE Transactions on Fuzzy Systems
Volume13
Issue number6
DOIs
Publication statusPublished - 2005 Dec

Bibliographical note

Funding Information:
Manuscript received October 5, 2002; revised May 5, 2003, January 31, 2004, and February 22, 2005. This paper was performed for the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Commerce, Industry, and Energy of Korea. The authors are with the School of Electrical and Electronic Engineering, Yonsei University Seoul 120-749, Korea (e-mail: etkim@yonsei.ac.kr). Digital Object Identifier 10.1109/TFUZZ.2005.859306

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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