Output Feedback Model Predictive Control of Uncertain Norm-Bounded Linear Systems

A constrained output feedback model predictive control (MPC) scheme for uncertain Norm-Bounded discrete-time linear systems is presented. This scheme extends recent results achieved by the authors under full-state availability to the more interesting case of incomplete and noisy state information. The design procedure consists of an off-line step where a state feedback and an asymptotic observer (dynamic primal controller) are designed via bilinear matrix inequalities and used to robustly stabilize a suitably augmented state plant. The on-line moving horizon procedure adds N free control moves to the action of the primal controller which are computed by solving a linear matrix inequality optimization problem whose numerical complexity grows up only linearly with the control horizon N. The effectiveness of the proposed MPC strategy is illustrated by a numerical example