LMI based design of constrained fuzzy predictive control

doi:10.1016/j.fss.2009.10.020

Fuzzy Sets and Systems

Volume 161, Issue 6, 16 March 2010, Pages 893-918

https://doi.org/10.1016/j.fss.2009.10.020 Get rights and content

Abstract

Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new ideas are proposed here. First, an added constraint on the applied control action is used to ensure the decrease of a quadratic Lyapunov function, and so guarantee Lyapunov exponential stability of the closed-loop system. Second, the feasibility of the finite-horizon optimization problem with the added constraints is ensured based on an off-line solution of a set of LMIs. The novel stability method is compared to the existing methods, such as the techniques based on the end-point constraints (terminal constraint set), and the robust stability techniques based on the small gain theory. The proposed method ensures Lyapunov exponential stability, does not need an auxiliary controller and can be used with any feasible controller parameters. Illustrative examples including the predictive control of a highly nonlinear chemical reactor (CSTR) are discussed.

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LMI based design of constrained fuzzy predictive control

Abstract

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Automatica

Automatica

Automatica

Automatica

Automatica

Int. J. Approx. Reason.

Int. J. Approx. Reason.

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IEEE Trans. Fuzzy systems

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Analysis and design for a class of complex control systems, part 1–2

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IEEE Trans. Fuzzy Systems

Fuzzy predictive control of a solar power plant

IEEE Trans. Fuzzy Syst.

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IEEE Trans. Fuzzy Syst.

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IEEE Trans. Fuzzy Syst.

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