Fuzzy Based Model Predictive Control for Uncertain Nonlinear System

Abstract:

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In this paper, a model predictive control (MPC) scheme is investigated for uncertain nonlinear system with time delay and input constraint. First, the Takagi-Sugeno (T-S) fuzzy model is used to approximate the dynamics of nonlinear processes and the parallel distributed compensation (PDC) controllers which are parameter dependent and mirror the structure of the T-S plant model are proposed. Then a novel feedback PDC predictive controller obtained from the linear matrix inequality (LMI) solutions which can guarantee the stability of the closed-loop overall fuzzy system is put forward. Finally, a numerical example is provided to demonstrate the effectiveness and feasibility of the proposed method.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

2404-2410

DOI:

10.4028/www.scientific.net/AMR.383-390.2404

Citation:

L. Xu and F. Liu, "Fuzzy Based Model Predictive Control for Uncertain Nonlinear System", Advanced Materials Research, Vols. 383-390, pp. 2404-2410, 2012

Online since:

November 2011

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$35.00

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