BMI-based stability and performance design for fuzzy-model-based control systems subject to parameter uncertainties

Hak Keung Lam; Lakmal D. Seneviratne

doi:10.1109/TSMCB.2006.885308

BMI-based stability and performance design for fuzzy-model-based control systems subject to parameter uncertainties

Hak Keung Lam, Lakmal D. Seneviratne

Mechanical & Nuclear Engineering

King's College London

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

19 Scopus citations

Abstract

This paper presents the stability and performance design of a fuzzy-model-based control system subject to parameter uncertainties. A nonlinear controller with a favorable characteristic to relax the stability conditions is proposed to drive the system states of the nonlinear plant to follow those of a stable reference model. Stability and performance conditions in terms of bilinear matrix inequalities (BMIs) will be derived based on a Lyapunov-based approach. A combined genetic algorithm and convex programming technique process will be developed to solve the solution to the BMIs. An application example will be given to illustrate the merits of the proposed approach.

Original language	British English
Pages (from-to)	502-514
Number of pages	13
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume	37
Issue number	3
DOIs	https://doi.org/10.1109/TSMCB.2006.885308
State	Published - Jun 2007

Keywords

Bilinear matrix inequality
Fuzzy control
Nonlinear systems
Stability

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10.1109/TSMCB.2006.885308

Cite this

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abstract = "This paper presents the stability and performance design of a fuzzy-model-based control system subject to parameter uncertainties. A nonlinear controller with a favorable characteristic to relax the stability conditions is proposed to drive the system states of the nonlinear plant to follow those of a stable reference model. Stability and performance conditions in terms of bilinear matrix inequalities (BMIs) will be derived based on a Lyapunov-based approach. A combined genetic algorithm and convex programming technique process will be developed to solve the solution to the BMIs. An application example will be given to illustrate the merits of the proposed approach.",

keywords = "Bilinear matrix inequality, Fuzzy control, Nonlinear systems, Stability",

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note = "Funding Information: Manuscript received November 18, 2005; revised February 17, 2006. This work was supported by the Division of Engineering, King{\textquoteright}s College London. This paper was recommended by Associate Editor W. Pedrycz. The authors are with the Division of Engineering, King{\textquoteright}s College London, WC2R 2LS London, U.K. (e-mail: [email protected]). Digital Object Identifier 10.1109/TSMCB.2006.885308",

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AB - This paper presents the stability and performance design of a fuzzy-model-based control system subject to parameter uncertainties. A nonlinear controller with a favorable characteristic to relax the stability conditions is proposed to drive the system states of the nonlinear plant to follow those of a stable reference model. Stability and performance conditions in terms of bilinear matrix inequalities (BMIs) will be derived based on a Lyapunov-based approach. A combined genetic algorithm and convex programming technique process will be developed to solve the solution to the BMIs. An application example will be given to illustrate the merits of the proposed approach.

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BMI-based stability and performance design for fuzzy-model-based control systems subject to parameter uncertainties

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Keywords

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