Paper Info
Title
Robust Control of Constrained Linear Systems With Bounded Disturbances
Abstract
This technical note develops a novel robust control algorithm for linear systems subject to additive and bounded disturbances. The approach is based on the constraint tightening method. While this problem can be tackled using existing robust model predictive control techniques, the proposed method has an advantage in that it is computationally efficient and avoids the need to solve repeatedly an online optimization problem, while the optimization problem solved at initialization is a simple linear programming problem. The algorithm elaborated in this technical note guarantees convergence to a minimal disturbance invariant set, and the terminal predicted state constraint set is allowed to be larger than the minimal disturbance invariant set. As an illustration, the developed algorithm is applied to constrained roll control of a ship operating in a wave field. Simulation results show that the proposed approach reduces the ship roll motion while the input and dynamic stall constraints are satisfied.
Year
DOI
Venue
2012
10.1109/TAC.2012.2192362
Automatic Control, IEEE Transactions
Keywords
Field
DocType
linear programming,linear systems,predictive control,robust control,additive disturbances,bounded disturbances,constrained linear systems,constraint tightening method,linear programming problem,minimal disturbance invariant set,novel robust control algorithm,online optimization problem,robust model predictive control techniques,ship roll motion,terminal predicted state constraint set,Model predictive control (MPC)
Mathematical optimization,Linear system,Linear-quadratic-Gaussian control,Control theory,Model predictive control,Linear programming,Initialization,Robust control,Optimization problem,Mathematics,Bounded function
Journal
Volume
Issue
ISSN
57
10
0018-9286
Citations 
PageRank 
References 
9
0.56
13
Authors
3
Name
Order
Citations
PageRank
Reza Ghaemi17710.31
Jing Sun249188.35
Ilya V. Kolmanovsky316320.68