Abstract
AbstractWe present a computationally efficient scheduled model predictive control (MPC) algorithm for constrained nonlinear systems with large operating regions. We design a set of local predictive controllers with estimates of their regions of stability covering the desired operating region, and implement them as a single scheduled MPC which on‐line switches between the set of local controllers and achieves nonlinear transitions with guaranteed stability. This algorithm is computationally efficient and provides a general framework for the scheduled MPC design. The algorithm is illustrated with two examples. Copyright © 2003 John Wiley & Sons, Ltd.
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