Efficient scheduled stabilizing output feedback model predictive control for constrained nonlinear systems

In this paper, we present a computationally efficient scheduled output feedback model predictive control (MPC) algorithm for constrained nonlinear systems with large operating regions. We design 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 online switches between the set of local controllers and achieves nonlinear transitions with guaranteed stability. The algorithm is illustrated with a highly nonlinear continuously stirred tank reactor (CSTR) process.