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A novel robust predictive control algorithm is presented for input-saturated uncertain discrete-time linear systems described by structured norm-bounded uncertainties. The solution is based on the minimization, at each time instant, of an LMI convex optimization problem obtained by a recursive use of the S-procedure. Stability and feasibility are proved and comparisons with robust multi-model (polytopic)...
This technical note deals with robust state estimation when parametric uncertainties nonlinearly affect a plant state-space model, based on a simultaneous minimization of nominal estimation errors and their sensitivities. An analytic solution is derived for the optimal estimator which can be recursively realized. This estimator has a form similar to the robust estimator of , and its computational...
This paper presents the design of iterative learning control based on Quadratic performance criterion (Q-ILC) for linear systems subject to additive uncertainty. Robust Q-ILC design can be cast as a min-max problem. We propose a novel approach which employs an upper bound of the worst-case error, then formulates a nonconvex quadratic minimization problem to get the update of iterative control inputs...
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