Neural Networks Based-Adaptive Control of Nonlinear Ship Manoeuvring System

The problem of an adaptive control method for a nonlinear ship manoeuvring system under the influence of input dead-zone is considered in this paper. The ship manoeuvring system in the form of an uncertain nonlinear system is considered. The unknown nonlinear functions are approximated by radial basis function neural networks (RBFNN). The suggested control technique has the benefit that it does not require any prior understanding of ship manoeuvring systems. With arbitrarily small positioning errors, our proposed control law is proven to be successful in managing the position and heading of ships to the desired targets. The Lyapunov function method is employed in the stability analysis of the proposed model. Finally, an example is provided to demonstrate the efficiency of the suggested methodology.