Existence and computation of infinite horizon model predictive control with active steady-state input constraints

This note addresses the existence and implementation of the infinite-horizon controller for the case of active steady-state input constraints. This case is important because, in many practical applications, controllers are required to operate at the boundary of the feasible region (for instance, in order to maximize global economic objectives). For this case, the usual finite horizon parameterizations with terminal cost cannot be applied, and optimal solutions are not generally available. We propose here an iterative algorithm that generates two finite-horizon approximations to the true infinite-horizon problem, where the solution to one of the approximations yields an upper bound on the true optimum, while the other approximation yields a lower bound. We show convergence of both bounding approximations to the optimal solution, as the horizon length in the approximations is increased. We outline a procedure, based on this result, to provide a solution to the infinite-horizon problem that is exact to within any user-specified tolerance. Finally, we present an example that includes a comparison between optimal and suboptimal controllers.