Restricted-complexity characterization of control-invariant domains with application to lateral vehicle dynamics control

This paper proposes two algorithms to find a restricted-complexity robust control invariant (RCI) set along with a state-feedback gain. These algorithms are applicable to a linear system with additive disturbances subject to found polytopic state and input constraints. The RCI set is a polytope with restricted complexity, symmetric around the origin. Using a state transformation, novel LMI conditions are derived for the system constraints and invariance condition. Moreover, a new approach is proposed to iteratively increase the volume of the computed RCI set. The effectiveness of the proposed algorithm is illustrated by using lateral vehicle dynamics control example.