Less Conservative Robust Control of Constrained Linear Systems with Bounded Disturbances

This paper develops a novel robust control method for linear systems subject to additive and bounded disturbances. The approach is based on constraint tightening method. The proposed method is computationally efficient in the sense that it does not require solving any online optimization problem, in contrast to several other robust Model Predictive Control approaches proposed in the literature. The algorithm elaborated in this paper guarantees convergence to a minimal disturbance invariant set and the terminal predicted state constraint set is allowed to be larger than the minimal disturbance invariant set.