Title :
Efficient implementation of multivariable MPC with parametric uncertainties
Author :
Bouzouita, Badreddine ; Bouani, Faouzi ; Ksouri, Mekki
Author_Institution :
Nat. Eng. Sch. of Tunis, Tunis, Tunisia
Abstract :
A robust predictive controller for uncertain multivariable systems is developed in this work. The design problem is based on multivariable Controlled Auto Regressive Integrated Moving Average (CARIMA) model with parametric uncertainties. The use of an uncertain CARIMA model leads to a non convex optimization problem. Consequently, the computation time is so high that limit the on line implementation of the robust predictive controller. To reduce the computation time, we propose, in this work, the convexification of the optimization problem by using the generalized geometric programming. This method is addressed for non convex polynomial problem which is the case of most robust and nonlinear control system analysis and design problem. The efficiency of the proposed optimization algorithm, LMI and genetic algorithms optimizers are tested and compared on benchmark functions. The proposed controller is performed on three tanks system.
Keywords :
autoregressive moving average processes; computational complexity; concave programming; control system synthesis; genetic algorithms; geometric programming; linear matrix inequalities; multivariable control systems; nonlinear control systems; predictive control; robust control; uncertain systems; CARIMA model; LMI; computation time; controlled auto regressive integrated moving average model; generalized geometric programming; genetic algorithms; linear matrix inequalities; model predictive control; multivariable MPC; nonconvex optimization; nonconvex polynomial problem; nonlinear control system analysis; parametric uncertainties; robust predictive controller; uncertain multivariable systems; Equations; Genetic algorithms; Mathematical model; Optimization; Robustness; Uncertainty; Valves; Generalized geometric programming; Parametric uncertainties; Robust predictive control; min-max optimization problem;
Conference_Titel :
Control Conference (ECC), 2007 European
Conference_Location :
Kos
Print_ISBN :
978-3-9524173-8-6