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Robust stability constraints for fuzzy model predictive control

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5 Author(s)
S. Mollov ; Syst. & Control Eng. Group, Delft Univ. of Technol., Netherlands ; T. van den Boom ; F. Cuesta ; A. Ollero
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This paper addresses the synthesis of a predictive controller for a nonlinear process based on a fuzzy model of the Takagi-Sugeno (T-S) type, resulting in a stable closed-loop control system. Conditions are given that guarantee closed-loop robust asymptotic stability for open-loop bounded-input-bounded-output (BIBO) stable processes with an additive l1-norm bounded model uncertainty. The idea is closely related to (small-gain-based) l1-control theory, but due to the time-varying approach, the resulting robust stability constraints are less conservative. Therefore the fuzzy model is viewed as a linear time-varying system rather than a nonlinear one. The goal is to obtain constraints on the control signal and its increment that guarantee robust stability. Robust global asymptotic stability and offset-free reference tracking are guaranteed for asymptotically constant reference trajectories and disturbances

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IEEE Transactions on Fuzzy Systems  (Volume:10 ,  Issue: 1 )