Dynamic response optimisation of active heave compensation systems for electrical winches
Year: 2025
Type: article
Abstract: Wind-wave-swell disturbances and system nonlinearities pose significant obstacles to active heave compensation (AHC) for electrical winches. This study proposes a synergistic AHC strategy, which combines extended Kalman filter (EKF) and adaptive model predictive control (AMPC), significantly alleviating the system response lag defect and realizing the dynamic nonlinear dead-zone compensation mechanism. The wave spectrum parameters are mapped by sea state grade, and the dynamic disturbance signal is generated by programmable logic controller (PLC) in real time to drive the ship to heave. EKF evaluates the system state and key parameters in real time to eliminate the output unresponsiveness caused by variable frequency drive (VFD) dead zone. The embedded EKF in AMPC framework realises the collaborative work of online parameter identification and rolling optimisation. Meanwhile, the dead zone of VFD is corrected by the winch driving force, which ensures that the system can achieve high-precision attitude control of the load under specified states (dynamic stability trajectories) and input constraints. The experimental results of full-scale electrical winch AHC platform demonstrate that the compensation effectiveness of EKF-AMPC is 7.613 %–11.898 % higher than that of conventional proportional integral derivative (PID) under 2- to 6-level sea states, confirming the effectiveness and practical feasibility of this strategy.
Source: Ocean Engineering
Authors: Ruhua Zhang, Wenhua Li, Shanying Lin, Gen Li, Ping Zhang, Shijie Xu
Institution: Dalian Maritime University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,150
Funders: Dalian Maritime University, Higher Education Discipline Innovation Project, National University's Basic Research Foundation of China, Liaoning Revitalization Talents Program, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities, Dalian Science and Technology Innovation Fund
OpenAlex ID: W4416388058
