Model Predictive Control for Constrained Discrete Time Systems: An Optimal Perturbation Analysis Approach

In the paper we consider a model predictive control (MPC) strategy based on approximating the MPC optimal control solution by a nominal solution (either pre-computed in advance on-line or computed off-line) and a perturbation solution, which is easily computable and corrects the nominal solution. Unlike similar approaches in prior literature (see e.g., (A.E. Bryson and Y. Ho, 1975), (F.L. Lewis, 1986)), our approach is capable of enforcing piecewise state and control constraints. We describe how the basic approach can be integrated within the framework of forecasting MPC (FMPC) and illustrate its effectiveness by means of an example.