Moving horizon control is a type of sampled-data feedback control in which the control over each sampling interval is determined by the solution of an open-loop optimal control problem. We develop a dual-sampling-rate moving horizon control scheme for a class of linear, continuous-time plants with strict input saturation constraints, in the presence of plant uncertainty and input disturbances. Our control scheme has two components: a slow-sampling moving horizon controller for a nominal plant, and a fast-sampling state-feedback controller whose function is to force the actual plant to emulate the nominal plant. The design of the moving horizon controller takes into account the non-negligible computation time required to compute the optimal control trajectory.
We prove local stability of the resulting feedback system and illustrate its performance with simulations. In these simulations, our dual-sampling-rate controller exhibits performance that is considerably superior to its single-sampling-rate moving horizon controller counterpart.