Title :
Reduced order model predictive control - an approach based on system decomposition -
Author :
Hara, Naoyuki ; Kojima, Akira
Author_Institution :
Tokyo Metropolitan Univ., Tokyo
Abstract :
This paper considers a reduced order model predictive control (MPC) method for constrained discrete-time linear systems. By employing a system decomposition technique for discrete-time linear systems, a reduced order MPC law is derived. The MPC law is improved in terms of control performance and feasibility of the associated optimization problem.
Keywords :
discrete time systems; linear systems; optimisation; predictive control; reduced order systems; associated optimization problem; constrained discrete-time linear systems; reduced order model predictive control; system decomposition; system decomposition technique; Computational complexity; Control systems; Design methodology; Linear systems; Optimal control; Predictive control; Predictive models; Quadratic programming; Reduced order systems; Riccati equations; constraint; eigenvalue problem; model predictive control; model reduction;
Conference_Titel :
SICE, 2007 Annual Conference
Conference_Location :
Takamatsu
Print_ISBN :
978-4-907764-27-2
Electronic_ISBN :
978-4-907764-27-2
DOI :
10.1109/SICE.2007.4421358
