Real Time Multi-step Prediction for Shipborne Helicopter Platform Motion

A shipborne helicopter platform, which can compensate wave motion, is useful for a helicopter to land and take off safely. In order to solve the time delay problem of hydraulic cylinder, the prediction for the generalized heave motion (the coupling result of roll, pitch and heave) of the platform is needed. An Automation Regressive (AR) model is proposed to do the short time prediction for its low complexity of computation. A recursive least square (RLS) algorithm is commonly used to estimate the parameters of AR model. However, the parameter estimation based on RLS algorithm is easy to drift and be unstable when the system has random noise. To improve the problem, a damped recursive least square (DRLS) algorithm based on AR model is deduced and introduced to estimate the parameters. Using the collected real time data, the simulations suggest that the DRLS algorithm is able to increase the stability of parameter estimation and the AR prediction model can generate real time multi-step prediction for generalized heave displacements of a shipborne helicopter platform.