Muñoz de la Peña, David and Bemporad, Alberto and Alamo, Teodoro
*A decomposition algorithm for feedback min-max model predictive control.*
In:
Decision and Control and European Control Conference.
IEEE, 12th-15th Dec. 2005 , pp. 5126-5131.
ISBN 0-7803-9567-0
(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.

Item Type: | Book Section |
---|---|

Identification Number: | 10.1109/CDC.2005.1582975 |

Uncontrolled Keywords: | Optimization algorithms; Predictive control for linear systems; Uncertain systems |

Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |

Research Area: | Computer Science and Applications |

Depositing User: | Professor Alberto Bemporad |

Date Deposited: | 27 Jul 2011 08:47 |

Last Modified: | 05 Aug 2011 13:53 |

URI: | http://eprints.imtlucca.it/id/eprint/533 |

### Actions (login required)

Edit Item |