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Related Experiment Videos

Guaranteed cost controller design for discrete-time switching fuzzy systems.

Doo Jin Choi1, PooGyeon Park

  • 1Pohang University of Science and Technology, Pohang, Kyungbuk, 790-784, Korea. chdj@postech.ac.kr

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|September 17, 2004
PubMed
Summary

This study introduces discrete-time switching fuzzy systems and proposes two novel guaranteed cost state-feedback controllers. These controllers minimize state and input energy for improved performance in complex systems.

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Area of Science:

  • Control Systems Engineering
  • Fuzzy Logic Systems
  • Hybrid Systems

Background:

  • Discrete-time switching fuzzy systems combine characteristics of switched hybrid systems and Takagi-Sugeno (TS) fuzzy systems.
  • Existing methods may not fully utilize time-varying information in fuzzy weighting functions.

Purpose of the Study:

  • To develop novel guaranteed cost state-feedback controllers for discrete-time switching fuzzy systems.
  • To minimize an upper bound of state and input energy (LQ performance) under time-varying fuzzy weighting functions.
  • To enhance controller design by incorporating time-varying information more effectively.

Main Methods:

  • Introduction of a discrete-time switching fuzzy system with crisp switching-region and local fuzzy weighting functions.
  • Proposal of two guaranteed cost state-feedback controllers.

Related Experiment Videos

  • Utilization of a piecewise quadratic Lyapunov function (PQLF) for the first controller.
  • Development of a new piece-wise fuzzy weighting-dependent Lyapunov function (PFWLF) for the second controller, incorporating past information.

    • Main Results:

    • The proposed controllers guarantee a minimized upper bound of state and input energy (LQ performance).
    • The PQLF-based controller effectively uses time-varying switching-region weighting functions.
    • The PFWLF-based controller demonstrates superior performance by utilizing both current and past information of local fuzzy weighting functions and switching-region functions.
    • The PFWLF controller's design leverages a novel Lyapunov function structure.

    Conclusions:

    • The developed controllers offer effective solutions for controlling discrete-time switching fuzzy systems with time-varying parameters.
    • The PFWLF-based controller provides enhanced performance by utilizing richer time-varying information.
    • This research contributes to the advancement of robust control strategies for complex hybrid systems.