Research on Path Following Control of Unmanned Surface Vehicle Based on Model Predictive Control with Improved Artificial Bee Colony Algorithm

To solve the problems of rudder angle response lag, rudder amplitude and rudder speed constraints in the path following of unmanned surface vehicle, a model predictive control algorithm is proposed. According to the control characteristics of unmanned surface vehicle, a nonlinear dynamic model of surface is established. To solve the model uncertainty and the interference of wind, wave and current in the marine environment, using the model prediction algorithm of on-line optimization, a constrained model prediction controller (MPC) based on improved artificial bee colony (ABC) optimization is proposed, and the stability of the model prediction controller is demonstrated. Finally, the simulation results show that the path following controller designed by ABC-MPC can track the reference path with high accuracy under the time-varying interference of wind, wave and current, and the change of rudder angle is small and smooth, which effectively reduces the cumulative influence of uncertainty.