Optimization over state feedback policies for robust control with constraints

This paper is concerned with the optimal control of linear discrete-time systems, which are subject to unknown but bounded state disturbances and mixed constraints on the state and input. It is shown that the class of admissible affine state feedback control policies with memory of prior states is equivalent to the class of admissible feedback policies that are affine functions of the past disturbance sequence. This result implies that a broad class of constrained finite horizon robust and optimal control problems, where the optimization is over affine state feedback policies, can be solved in a computationally efficient fashion using convex optimization methods without having to introduce any conservatism in the problem formulation. This equivalence result is used to design a robust receding horizon control (RHC) state feedback policy such that the closed-loop system is input-to-state stable (ISS) and the constraints are satisfied for all time and for all allowable disturbance sequen...

• Type: Journal
• Year: 2006
• Where: AUTOMATICA
• Authors: Paul J. Goulart, Eric C. Kerrigan, Jan M. Maciejowski
• Keywords: AUTOMATICA 2006, Optimal Control, Optimal Control Problem, State Feedback