DocumentCode
1401407
Title
Model Predictive Control Using Segregated Disturbance Feedback
Author
Wang, Chen ; Ong, Chong-Jin ; Sim, Melvyn
Author_Institution
Dept. of Mech. Eng., Nat. Univ. of Singapore & Singapore-MIT Alliance, Singapore, Singapore
Volume
55
Issue
4
fYear
2010
fDate
4/1/2010 12:00:00 AM
Firstpage
831
Lastpage
840
Abstract
This paper proposes a new control parametrization under the model predictive control (MPC) framework for constrained linear discrete-time systems with bounded disturbances. The proposed parametrization takes the form of a special piecewise affine disturbance feedback in an effort to reduce conservatism. It is a generalization of linear disturbance feedback parametrization, introduced in the recent literature. Numerical computations and stability properties of the resulting MPC problem using the proposed parametrization are discussed. When the disturbance set and the problem data satisfy mild assumptions, the associated finite-horizon optimization can be computed efficiently and exactly. The advantage of the proposed parametrization over linear disturbance feedback is illustrated via numerical examples.
Keywords
discrete time systems; feedback; linear systems; numerical analysis; optimisation; predictive control; constrained linear discrete-time systems; finite-horizon optimization; linear disturbance feedback parametrization; model predictive control; piecewise afflne disturbance feedback; Adaptive control; Control systems; Convergence; Cost function; Linear feedback control systems; Mechanical engineering; Numerical stability; Permission; Predictive control; Predictive models; State feedback; Model predictive control (MPC);
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2010.2041994
Filename
5404420
Link To Document