Title :
A Decomposition Algorithm for Feedback Min–Max Model Predictive Control
Author :
de La Peña, D. Muñoz ; Alamo, T. ; Bemporad, A. ; Camacho, E.F.
Author_Institution :
Departamento de Ingenieria de Sistemas y Automatica, Seville Univ.
Abstract :
An algorithm for solving feedback min-max model predictive control for discrete-time uncertain linear systems with constraints is presented in this note. The algorithm 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
Keywords :
discrete time systems; feedback; linear systems; predictive control; uncertain systems; decomposition algorithm; discrete time uncertain linear system; feedback min-max model predictive control; finite time system; Adaptive control; Automatic control; Control systems; Feedback; Nonlinear control systems; Predictive control; Predictive models; Process control; Programmable control; Robotics and automation; Optimization algorithms; predictive control for linear systems; uncertain systems;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2006.883062
