TY - GEN
T1 - Dual Control of Exploration and Exploitation for Wave Energy Converters
AU - Tang, Siyang
AU - Chen, Wen Hua
AU - Liu, Cunjia
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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 take-off force. Simulation results validates the effectiveness of this novel framework featuring the DCEE approach.
AB - 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 take-off force. Simulation results validates the effectiveness of this novel framework featuring the DCEE approach.
KW - active learning
KW - auto-optimisation control
KW - dual control
KW - wave energy converter
UR - http://www.scopus.com/inward/record.url?scp=85194847698&partnerID=8YFLogxK
U2 - 10.1109/CONTROL60310.2024.10531894
DO - 10.1109/CONTROL60310.2024.10531894
M3 - Conference article published in proceeding or book
AN - SCOPUS:85194847698
T3 - 2024 UKACC 14th International Conference on Control, CONTROL 2024
SP - 25
EP - 30
BT - 2024 UKACC 14th International Conference on Control, CONTROL 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th UKACC International Conference on Control, CONTROL 2024
Y2 - 10 April 2024 through 12 April 2024
ER -