Constrained receding horizon predictive control for systems with disturbances

A receding horizon predictive control method for systems with input constraints and disturbances is proposed.A polyhedral feasible set of states which is invariant withrespect to a given state feedback control law is derived inthe presence of bounded disturbances. The proposed predicted control algorithm deploys a strategy in which the currentstate is steered into the polyhedral invariant feasible setwithin a finite number N of feasible control moves, despitethe presence of disturbances. The future control moves overthe horizon N are represented as the sum of the state feedback control and a perturbation; the perturbation term provides the degrees of freedom with which to enlarge the stabilizable set of initial states. The control algorithm is formulated in linear matrix inequalities so that it can be solved using semidefinite programming.