A generic linear non-causal optimal control framework integrated with wave excitation force prediction for multi-mode wave energy converters with application to M4. (April 2020)

• Record Type: Journal Article
• Authors: Liao, Zhijing; Stansby, Peter; Li, Guang
• Is Part Of: Applied ocean research. Volume 97(2020)
• Publication Date: 2020-04
• Subjects: Wave excitation force estimation -- Kalman filter -- Autoregressive model -- Optimal control -- Non-causal control; Ocean engineering -- Periodicals; 620.416205
• DOI: 10.1016/j.apor.2020.102056
• Languages: English
• ISSNs: 0141-1187

Abstract

Abstract: The multi-float multi-mode wave energy converter (M-WEC) M4 has essentially linear hydrodynamics characteristics in operational and even extreme waves. This is in contrast to point-absorber and most raft-type devices where nonlinear effects and associated losses are significant. The control problem now involves a large number of degrees of freedom. Energy maximizing control of wave energy converters (WECs) is a non-causal control problem. This paper aims to propose a complete self-contained non-causal optimal control framework by combining a linear non-causal optimal control (LNOC) algorithm with an autoregressive (AR) model as the wave excitation force predictor and a Kalman Filter with random walk wave model (KFRW) as the wave excitation force estimator. The efficacy of the proposed framework together with its enabling components is demonstrated numerically using irregular waves. The proposed framework has low computational load, which enables its real-time implementation on standard computational hardware. Furthermore, the wave force prediction does not require deployment and maintenance of expensive hardware, which helps to reduce the unit cost of the generated electricity.