摘要：AbstractThis paper extends previous results on symmetry in strictly convex linear model predictive control to non-strictly convex and nonlinear model predictive control. We define symmetry for constrained systems, controllers, and model predictive control problems. We show that symmetric model predictive control problems produce symmetric controllers. We show that the previously established methods of memory reduction can be applied to non-strictly convex problems. We apply these memory reduction techniques to the battery balancing problem. Exploiting symmetry leads to an exponential memory reduction and simple, intuitive optimal controllers.
