The Adaptive Inverse Control of Nonlinear Ship Maneuvering Based on Improved Radial Basis Function Neural Network
There are several drawbacks of common adaptive control methods to nonlinear ship manoeuvring,such as high learning complexity in real time parameters adjustment and poor robustness etc.To(overcome) these disadvantages,a new adaptive inverse control(AIC) scheme based on improved radial basis function(RBF) network was presented,which has simpler structure and no local minimization problem compared with usual nonlinear adaptive model.The simulation results on a nonlinear ship model of "The R.O.V Zeefakkel" show that the AIC can greatly improve the dynamic behavior with a good robustness and disturbance rejection performances;it is suited to the control of smaller ships which have higher (requirement) to the manoeuvrability.