Title :
Robust model predictive control of constrained linear systems
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
fDate :
June 30 2004-July 2 2004
Abstract :
Linear matrix inequality (LMI) based optimization methods are applied to the problem of designing a model predictive controller for an uncertain constrained linear system. The control signal is specified in terms of both feedback and feedforward components, where the feedback is designed to maintain the state within a prescribed ellipse in the presence of unknown bounded disturbances and system perturbations. The feedforward component drives these ellipses to a desired reference state. The LMI characterization allows exact specification of ellipsoidal and hyperplane constraints on the inputs, states and outputs.
Keywords :
control system synthesis; feedback; feedforward; linear matrix inequalities; linear systems; optimisation; perturbation techniques; predictive control; robust control; uncertain systems; feedback component; feedforward component; linear matrix inequality; optimization methods; robust model predictive control design; system perturbations; uncertain constrained linear systems; unknown bounded disturbances;
Conference_Titel :
American Control Conference, 2004. Proceedings of the 2004
Conference_Location :
Boston, MA, USA
Print_ISBN :
0-7803-8335-4
