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Worst-case formulations of model predictive control for systems with bounded parameters. (English) Zbl 0878.93025
Several formulations of the worst-case predictive control algorithms under a set membership uncertainty and quadratic performance criterion are presented. The focus of the paper is the development of closed-loop predictive control formulations, which are based on the minimization of the worst-case quadratic cost for systems with bounded parameters. The parametric uncertainties are assumed to be time-invariant or time-varying. It is shown that the closed-loop formulation leads to a dynamic control program, which must be solved numerically. Simulation examples to compare the performance of proposed alternative suboptimal algorithms are presented.

MSC:
93B51 Design techniques (robust design, computer-aided design, etc.)
49N10 Linear-quadratic optimal control problems
93C55 Discrete-time control/observation systems
Software:
QDES
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