Ship motion predictive PID control based on variable structure radial basis function network
基于变结构径向基函数网络的船舶运动预测PID控制

To deal with the long time-delay and time-varying dynamics of the ship motion in sea, we present a predictive PID controller based on variable structure radial basis function (RBF) network. This network performs sequential learning through a sliding data window reflecting system dynamic changes, and adjusts online the hidden layer nodes and their weighting values in the connection to output layers. We thus obtain an adaptive variable structure RBF network. This variable structure RBF network is employed as a multi-step online predictor for a predictive PID controller. Parameters of the controller are online tuned based on the sensitivity information obtained from the variable RBF network predictor. The proposed predictive PID controller is applied to ship course tracking control. Simulation results demonstrate satisfactory adaptation and robustness of the controllers.