Robust output feedback model predictive control for constrained linear systems via interval observers

This work addresses the problem of robust output feedback model predictive control for discrete-time, constrained linear systems corrupted by (bounded) state and measurement disturbances. Using available information on measurements uncertainty bounds, objective is to stabilize such a system while robustly respecting imposed constraints control. To this end, interval observer predictor with guaranteed performance are incorporated into classic MPC scheme. new approach offers advantages as enlarged feasible regions optimal problem, low computational burden, ease design.