A computationally efficient scheduled model predictive control algorithm for control of a class of constrained nonlinear systems

We present an overview of our results on stabilizing scheduled output feedback Model Predictive Control (MPC) algorithm for constrained nonlinear systems based on our previous publications [19, 20]. Scheduled MPC provides an important alternative to conventional nonlinear MPC formulations and this paper addresses the issues involved in its implementation and analysis, within the context of the NMPC05 workshop. The basic formulation involves the design of a set of local output feedback predictive controllers with their estimated regions of stability covering the desired operating region, and implement them as a single scheduled output feedback MPC which on-line switches between the set of local controllers and achieves nonlinear transitions with guaranteed stability. This algorithm provides a general framework for scheduled output feedback MPC design.