Title :
Linear matrix inequality based model predictive controller
Author :
Granado, E. ; Colmenares, W. ; Bernussou, J. ; García, G.
Abstract :
A model predictive controller based on linear matrix inequalities (LMIs) is presented. As in standard model predictive control (MPC) algorithms, at each (sampling) time, a convex optimisation problem is solved to compute the control law. The optimisation involves constraints written as LMIs, including those normally associated with MPC problems, such as input and output limits. Even though a state-space representation is used, only the measurable output and the extreme values of the unmeasurable states are used to determine the controller, hence, it is an output feedback control design method. Stability of the closed-loop system is demonstrated. Based on this MPC, a Lyapunov matrix is built and the controller computation is set in a more standard MPC framework. The design techniques are illustrated with numerical examples
Keywords :
Lyapunov matrix equations <lin. matrix inequality model predictive controller>; closed loop systems <lin. matrix inequality model predictive controller>; convex programming <lin. matrix inequality model predictive controller>; feedback <lin. matrix inequality model predictive controller>; linear matrix inequalities <inequality model predictive controller>; predictive control <lin. matrix inequality model predictive controller>; stability <lin. matrix inequality model predictive controller>; state-space methods <lin. matrix inequality model predictive controller>; LMI; Lyapunov matrix; MPC; closed-loop system; convex optimisation; extreme values; input limits; linear matrix inequality; measurable output; model predictive controller; output feedback control design method; output limits; stability; state-space representation; unmeasurable states;
Journal_Title :
Control Theory and Applications, IEE Proceedings -
DOI :
10.1049/ip-cta:20030703
