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This paper considers robust model predictive control for systems with polytopic uncertainty and bounded disturbance, where the system state is unmeasurable, and the model at the current sampling time is an exact combination of the vertices of the polytope. A parameter-dependent dynamic output feedback is used for this problem. At each sampling time, the optimization problems can be solved via LMI...
A constrained robust model predictive control algorithm for linear systems with polytopic uncertainty is presented in this paper. At each sample time the algorithm aims at minimizing an infinite horizon worst-case quadratic cost function. Compared with existed techniques, the proposed algorithm uses a sequence of slack inequalities to construct a tighter upper bound of robust cost function. A control...
This paper considers a synthesis approach to dynamic output feedback robust model predictive control for systems with polytopic uncertainty and bounded disturbance/-noise. We consider the special case where the current model of the polytope is exactly known. The primary contribution is the formulation of the overall control problem into a single optimization problem solvable via LMI techniques. By...
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