Data-Driven Model Predictive Control for Wave Energy Converters Using Gaussian Process

Yanhua Liu, Shuo Shi, Zhenbin Zhang, Zhenfeng Di, Oluleke Babayomi
2022 Symmetry  
The energy harvested by an ocean wave energy converter (WEC) can be enhanced by a well-designed wave-by-wave control strategy. One of such superior control methods is model predictive control (MPC), which is a nonlinear constrained optimization control strategy. A limitation of the classical MPC algorithm is its requirement of an accurate WEC dynamic model for real-time implementation. This article overcomes this challenge by proposing a data-driven MPC scheme for wave energy converters. The
more » ... a-based WEC model is developed by a Gaussian process (encompassing mean predictions and symmetric uncertainties) for a more accurate description of nonlinear and unmodeled system dynamics. A cross-entropy solver for data-driven MPC is employed for rapid, high-performance results, which samples trajectories from Gaussian distributions based on the concept of the symmetry principle. The proposed strategy is verified numerically by simulations which demonstrate its superior performance over a classical complex-conjugate controller.
doi:10.3390/sym14071284 fatcat:rkcw3hj6wnfhzc3o22ieqwtkem