Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems

Yih Guang Leu; Tsu Tian Lee; Wei Yen Wang

doi:10.1109/3477.790441

Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems

Yih Guang Leu, Tsu Tian Lee, Wei Yen Wang

Research output: Contribution to journal › Article › peer-review

340 Citations (Scopus)

Abstract

In this paper, an observer-based adaptive fuzzy-neural controller for a class of unknown nonlinear dynamical systems is developed. The observer-based output feedback control law and update law to tune on-line the weighting factors of the adaptive fuzzy-neural controller are derived. The total states of the nonlinear system are not assumed to be available for measurement. Also, the unknown nonlinearities of the nonlinear dynamical systems are not restricted to the system output only. The overall adaptive scheme guarantees that all signals involved are bounded. Simulation results demonstrate the applicability of the proposed method in order to achieve desired performance.

Original language	English
Pages (from-to)	583-591
Number of pages	9
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume	29
Issue number	5
DOIs	https://doi.org/10.1109/3477.790441
Publication status	Published - 1999
Externally published	Yes

ASJC Scopus subject areas

Control and Systems Engineering
Software
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/3477.790441

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title = "Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems",

abstract = "In this paper, an observer-based adaptive fuzzy-neural controller for a class of unknown nonlinear dynamical systems is developed. The observer-based output feedback control law and update law to tune on-line the weighting factors of the adaptive fuzzy-neural controller are derived. The total states of the nonlinear system are not assumed to be available for measurement. Also, the unknown nonlinearities of the nonlinear dynamical systems are not restricted to the system output only. The overall adaptive scheme guarantees that all signals involved are bounded. Simulation results demonstrate the applicability of the proposed method in order to achieve desired performance.",

author = "Leu, {Yih Guang} and Lee, {Tsu Tian} and Wang, {Wei Yen}",

note = "Funding Information: Manuscript received December 12, 1998; revised April 24, 1999. This work was supported by the National Science Council under Grant NSC 87-2213-E-011-080.This paper was recommended by Associate Editor C. P. Neuman. Y.-G. Leu and T.-T. Lee are with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R.O.C. (e-mail: leu@event.ee.ntust.edu.tw; ttlee@mouse.ee.ntust.edu.tw). W.-Y. Wang is with the Department of Business Mathematics, Soochow University, Taipei 100, Taiwan, R.O.C. (e-mail: wayne@bmath.scu.edu.tw). Publisher Item Identifier S 1083-4419(99)07943-1.",

year = "1999",

doi = "10.1109/3477.790441",

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AU - Leu, Yih Guang

AU - Lee, Tsu Tian

AU - Wang, Wei Yen

N1 - Funding Information: Manuscript received December 12, 1998; revised April 24, 1999. This work was supported by the National Science Council under Grant NSC 87-2213-E-011-080.This paper was recommended by Associate Editor C. P. Neuman. Y.-G. Leu and T.-T. Lee are with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R.O.C. (e-mail: leu@event.ee.ntust.edu.tw; ttlee@mouse.ee.ntust.edu.tw). W.-Y. Wang is with the Department of Business Mathematics, Soochow University, Taipei 100, Taiwan, R.O.C. (e-mail: wayne@bmath.scu.edu.tw). Publisher Item Identifier S 1083-4419(99)07943-1.

PY - 1999

Y1 - 1999

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AB - In this paper, an observer-based adaptive fuzzy-neural controller for a class of unknown nonlinear dynamical systems is developed. The observer-based output feedback control law and update law to tune on-line the weighting factors of the adaptive fuzzy-neural controller are derived. The total states of the nonlinear system are not assumed to be available for measurement. Also, the unknown nonlinearities of the nonlinear dynamical systems are not restricted to the system output only. The overall adaptive scheme guarantees that all signals involved are bounded. Simulation results demonstrate the applicability of the proposed method in order to achieve desired performance.

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Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems

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