Creation of a Ride Control Algorithm Using a Neural Network

Ride control systems are often implemented to reduce vessel motions. However, modern ride control systems are prone to experiencing a phase lag between the wave-induced motions and the control system’s actuation. The phase lag limits the system’s ability to dampen vessel motions and reduces the system’s effectiveness. To investigate a possible improvement to modern systems, an artificial neural network-based controller, trained by potential flow simulations, was used to prescribe the optimum future actuation of a ride control system. By prescribing the optimum future actuation in anticipation of system delays, phase lag can be mitigated.