Robust stability constraints for fuzzy model predictive control
Mollov, S.
van den Boom, T.
Cuesta, F.
Ollero, A.
Babuska, R.
Syst. & Control Eng. Group, Delft Univ. of Technol.;
This paper appears in: Fuzzy Systems, IEEE Transactions on
Publication Date: Feb 2002
Volume: 10,
Issue: 1
On page(s): 50-64
ISSN: 1063-6706
References Cited: 30
CODEN: IEFSEV
INSPEC Accession Number: 7182682
Digital Object Identifier: 10.1109/91.983278
Current Version Published: 2002-08-07
Abstract
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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