A Novel Model Predictive Control Formulation for Wave Energy Converters Based on the Reactive Rollout Method
Zechuan Lin, Xuanrui Huang, Xi Xiao
Abstract
In the wave energy converter (WEC) optimal control problem, the well-developed model predictive control (MPC) faces the trade-off between energy extraction performance and online computation burden when choosing the length of optimization horizon. In this work, a novel MPC problem formulation is proposed, which includes a terminal value function and a terminal constraint set. The terminal value function is derived by further calculating the system trajectory beyond the optimization horizon based on a pre-chosen “rollout” policy, which incorporates more future information and improves energy extraction. The linear reactive control is chosen as the rollout policy, under which a policy improvement theorem of the WEC system is derived. The terminal constraint set is a simple control invariant set that ensures the recursive feasibility of MPC. Extensive simulations show that the proposed reactive rollout MPC can achieve close-to-optimal performance with a very short optimization horizon, reducing the online computation burden significantly.