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Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

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Abstract

An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is presented. In this approach, the minimization problem of the “worst-case” objective function is converted into the linear objective minimization problem involving linear matrix inequalities (LMIs) constraints. The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability and a new upper bound on robust performance index are given for these kinds of uncertain fuzzy systems with state time-delay. Simulation results of CSTR process show that the proposed robust predictive control approach is effective and feasible.

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Authors and Affiliations

  1. National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou, 310027, China

    Su Cheng-li & Wang Shu-qing

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  1. Su Cheng-li
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  2. Wang Shu-qing
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Project (No. 60421002) supported by the National Natural Science Foundation of China

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Su, Cl., Wang, Sq. Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model. J. Zhejiang Univ. - Sci. A 7, 1723–1732 (2006). https://doi.org/10.1631/jzus.2006.A1723

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  • DOI: https://doi.org/10.1631/jzus.2006.A1723

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