Abstract:
This paper proposes a feedback model predictive control (MPC) strategy for linear time invariant discrete-time systems subject to predictable, persistent and bounded dist...Show MoreMetadata
Abstract:
This paper proposes a feedback model predictive control (MPC) strategy for linear time invariant discrete-time systems subject to predictable, persistent and bounded disturbances, and constraints on inputs and states. It is shown that with a sufficiently long prediction horizon, an infinite prediction horizon MPC with an indefinite index function and preview information of bounded disturbances can be approximated by a numerically tractable finite prediction horizon linear state feedback MPC. The proposed control strategy is essentially a non-causal economic MPC and can find its applications in a wide area, where the preview information of disturbance is available and conventional tracking control and regulation control strategies are not suitable, e.g. the energy maximization problem for sea wave energy converters. A numerical simulation is given to demonstrate the efficacy of the proposed control approach.
Published in: 2018 IEEE Conference on Decision and Control (CDC)
Date of Conference: 17-19 December 2018
Date Added to IEEE Xplore: 20 January 2019
ISBN Information: