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A distributed model predictive control scheme is developed for trackingpiecewise constant references where the terminal set is reconfigured online,whereas the terminal controller is computed offline. Unlike many standardexisting schemes, this scheme yields large feasible regions without performingoffline centralized computations. Although the resulting optimal controlproblem (OCP) is a semidefinite program (SDP), an SDP scalability method basedon diagonal dominance is used to approximate the derived SDP by a second-ordercone program. The OCPs of the proposed scheme and its approximation areamenable to distributed optimization. Both schemes are evaluated using a powernetwork example and compared to a scheme where the terminal controller isreconfigured online as well. It is found that fixing the terminal controllerresults in better performance, noticeable reduction in computational cost andsimilar feasible region compared to the case in which this controller isreconfigured online.

Online Computation of Terminal Ingredients in Distributed Model Predictive Control for Reference Tracking