In this paper,we propose a novel noncausal control framework to address the energy maximization problem of wave energy converters(WECs)subject to constraints.The energy maximization problem of WECs is a constrained op...In this paper,we propose a novel noncausal control framework to address the energy maximization problem of wave energy converters(WECs)subject to constraints.The energy maximization problem of WECs is a constrained optimal control problem.The proposed control framework converts this problem into a reference trajectory tracking problem through the Fourier pseudo-spectral method(FPSM)and utilizes the online tracking adaptive dynamic programming(OTADP)algorithm to realize real-time trajectory tracking for practical use in the ocean environment.Using the wave prediction technique,the optimal trajectory is generated online through a receding horizon(RH)implementation.A critic neural network(NN)is applied to approximate the optimal cost value function and calculate the error-tracking control by solving the associated Hamilton-Jacobi-Bellman(HJB)equation.The proposed WEC control framework improves computational efficiency and makes the online control feasible in practice.Simulation results show the effects of the receding horizon implementation of FPSM with different window lengths and window functions,while verifying the performances of tracking control and energy absorption of WECs in two different sea conditions.展开更多
基金supported by the Key R&D Program of Shandong Province,China(No.2021ZLGX04)the Taishan Industrial Experts Programme(No.tsls20231203)。
文摘In this paper,we propose a novel noncausal control framework to address the energy maximization problem of wave energy converters(WECs)subject to constraints.The energy maximization problem of WECs is a constrained optimal control problem.The proposed control framework converts this problem into a reference trajectory tracking problem through the Fourier pseudo-spectral method(FPSM)and utilizes the online tracking adaptive dynamic programming(OTADP)algorithm to realize real-time trajectory tracking for practical use in the ocean environment.Using the wave prediction technique,the optimal trajectory is generated online through a receding horizon(RH)implementation.A critic neural network(NN)is applied to approximate the optimal cost value function and calculate the error-tracking control by solving the associated Hamilton-Jacobi-Bellman(HJB)equation.The proposed WEC control framework improves computational efficiency and makes the online control feasible in practice.Simulation results show the effects of the receding horizon implementation of FPSM with different window lengths and window functions,while verifying the performances of tracking control and energy absorption of WECs in two different sea conditions.
