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
fDate :
4/1/2010 12:00:00 AM
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);
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2010.2041994