An algorithm for solving feedback min-max model predictive control for discrete time uncertain linear systems with constraints is presented in the paper. The algorithm solves the corresponding multi-stage min-max linear optimization problem. It is based on applying recursively a decomposition technique to solve the min-max problem via a sequence of low complexity linear programs. It is proved that the algorithm converges to the optimal solution in finite time. Simulation results are provided to compare the proposed algorithm with other approaches. © 2005 IEEE.
A decomposition algorithm for feedback min-max model predictive control / MUNOZ DE LA PENA, D.; Alamo, T.; Bemporad, A.. - 2005:(2005), pp. 5126-5131. ( 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 Sevilla, Spain 12th-15th Dec. 2005) [10.1109/CDC.2005.1582975].
A decomposition algorithm for feedback min-max model predictive control
A. BEMPORAD
2005
Abstract
An algorithm for solving feedback min-max model predictive control for discrete time uncertain linear systems with constraints is presented in the paper. The algorithm solves the corresponding multi-stage min-max linear optimization problem. It is based on applying recursively a decomposition technique to solve the min-max problem via a sequence of low complexity linear programs. It is proved that the algorithm converges to the optimal solution in finite time. Simulation results are provided to compare the proposed algorithm with other approaches. © 2005 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
