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https://doi.org/10.1007/s40815-016-0162-4
Title: | Membership-Function-Dependent Stability Analysis and Control Synthesis of Guaranteed Cost Fuzzy-Model-Based Control Systems | Authors: | Lam, H.K Xiao, B Yu, Y Yin, X Han, H Tsai, S.-H Chen, C.-S |
Keywords: | Control system analysis Control system synthesis Control systems Control theory Controllers Cost benefit analysis Cost functions Costs Linear matrix inequalities Matrix algebra Membership functions Nonlinear feedback Piecewise linear techniques System stability Dependent stability Fuzzy controllers Fuzzy model based control Guaranteed cost Linear quadratic cost function Lyapunov stability theory Minimization of costs Stability analysis Control system stability |
Issue Date: | 2016 | Citation: | Lam, H.K, Xiao, B, Yu, Y, Yin, X, Han, H, Tsai, S.-H, Chen, C.-S (2016). Membership-Function-Dependent Stability Analysis and Control Synthesis of Guaranteed Cost Fuzzy-Model-Based Control Systems. International Journal of Fuzzy Systems 18 (4) : 537-549. ScholarBank@NUS Repository. https://doi.org/10.1007/s40815-016-0162-4 | Rights: | Attribution 4.0 International | Abstract: | This paper focuses on the guaranteed cost stability analysis of fuzzy-model-based (FMB) control systems. Representing the nonlinear plant using a Takagi–Sugeno (T–S) fuzzy model, a fuzzy controller is employed to close the feedback loop. A weighted linear quadratic cost function is considered as the cost index to measure the performance of the closed-loop fuzzy system in terms of the system states, system outputs, and control signals. The stability of the FMB control system is investigated by the Lyapunov stability theory subject to the minimization of cost index for performance realization. A membership-function-dependent approach using the piecewise-linear membership functions is employed to include the information of membership functions into the stability analysis. Membership-function-dependent stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and feedback gains with the consideration of the system performance measured by the cost function. A simulation example is provided to illustrate the effectiveness and merits of the proposed approach. © 2016, The Author(s). | Source Title: | International Journal of Fuzzy Systems | URI: | https://scholarbank.nus.edu.sg/handle/10635/181351 | ISSN: | 15622479 | DOI: | 10.1007/s40815-016-0162-4 | Rights: | Attribution 4.0 International |
Appears in Collections: | Elements Staff Publications |
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