2024 UKACC 14TH INTERNATIONAL CONFERENCE ON CONTROL, CONTROL
|
2024年
基金:
英国工程与自然科学研究理事会;
关键词:
dual control;
active learning;
wave energy converter;
auto-optimisation control;
MODEL-PREDICTIVE CONTROL;
D O I:
10.1109/CONTROL60310.2024.10531894
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
This paper introduces an innovative auto-optimisation control framework for wave energy converters (WECs) where the concept of dual control for exploration and exploitation (DCEE) is employed to effectively address this challenge in the realm of WECs. The control problem for WECs is characterised by its dynamic and unpredictable nature, demanding strong adaptivity and robustness based on wave predictions. A sophisticated automatic control framework is proposed that transforms the inherently periodic WEC control problem into an optimal operational parameter search problem. A DCEE approach is developed to optimally search the best operational condition through trading off between exploitation and exploration. More specifically, the DCEE approach contributes to the reduction of belief uncertainty in the identification of wave parameters, which is achieved by actively exploring the operating environment. It also facilitates the tracking of optimal operational conditions for power takeoff force. Simulation results validates the effectiveness of this novel framework featuring the DCEE approach.