Suboptimality bounds for linear quadratic problems in hybrid linear systems

A method for computation of lower and upper bounds for the linear quadratic cost function associated to a class of hybrid linear systems is proposed. The optimization problem involves state space constraints and switches between the continuous and discrete dynamics at fixed time instances on the boundaries of the flow and jump sets. Our approach computes a quadratic suboptimal cost parameterized by initial and end state variables of all time intervals. Then, the unknown parameters are determined via solving constrained quadratic programming problems.