Title :
Output-feedback Model Predictive Control for LPV Systems with Input Saturation based on Quasi-Min-Max Algorithm
Author :
Kim, Tae-Hyoung ; Park, Jee-Hun ; Sugie, Toshiharu
Author_Institution :
Dept. of Syst. Sci., Kyoto Univ.
Abstract :
Model predictive control (MPC) is one of the most promising and significant control approaches because of its ability to handle control problems for constrained systems. In this paper, we propose a robust output-feedback MPC scheme for polytopic linear parameter varying (LPV) systems based on a quasi-min-max algorithm. We first show the off-line design procedure of a robust state observer for LPV systems using linear matrix inequality (LMI). Then, the on-line robust output-feedback MPC algorithm using the estimated state is developed based on LMI technique. At each time instant, the control input is computed by solving the proposed infinite horizon optimization problem involving LMI constraints. Finally, a numerical example is given to demonstrate its effectiveness
Keywords :
control nonlinearities; feedback; infinite horizon; linear matrix inequalities; linear systems; minimax techniques; observers; predictive control; robust control; constrained systems; infinite horizon optimization; linear matrix inequalities; linear matrix inequality; linear parameter varying systems; model predictive control; offline design; output-feedback; quasi-min-max algorithm; robust state observer; state estimation; Constraint optimization; Infinite horizon; Linear matrix inequalities; Open loop systems; Optimal control; Predictive control; Predictive models; Robustness; State estimation; Uncertainty;
Conference_Titel :
Decision and Control, 2006 45th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
1-4244-0171-2
DOI :
10.1109/CDC.2006.377038