Studies on RBF neural-network controller with application to ship control

We propose a radial basis function (RBF) neural network controller for ship control. The main feature of the controller is to combine a fuzzy controller with neural networks. We transform a set of fuzzy inference rules into an RBF neural-network controller, utilizing the nonlinear mapping and learning ability of the neural networks. We present the design method of the controller based on the RBF neural networks and fuzzy rules, and discuss the characteristics of the controller. We use MATLAB as a simulation language. Simulation tests are conducted with different parameters, and the results are given in the paper. We introduce a ship control test bed. The controller is installed on the ship control test bed, and sea trials are conducted in the open sea. The sea trial results are also shown in the paper.