Research On Path Following Control Of Underactuated Unmanned Surface Vessel

Recently,with the rapid development of the artificial intelligence,new energy,new material and other high technologies,unmanned surface vessel as a kind of intelligent platform is in the ascendant with the ability of autonomous navigation and decision-making.On the issues of climate and environment variation,human requirement,and nation security,unmanned surface vessel plays a crucial role in these respects.From the perspective of theoretical research and engineering application,the dissertation analyses the path following control in detail for many subjects in the fields of unmanned surface vessel control.Due to the complexity of the ocean environment,the dynamics' of the unmanned surface vessel is obviously uncertain,as well as the thrusters with the physical constraint.Giant challenges occur in the unmanned surface vessel from these uncertainties and nonlinear issues.According to above discussions,the dissertation presents the following works.First,robust adaptive path following control laws are proposed to solve the path following control problem of underactuated unmanned surface vessel with external time-varying disturbances and input saturation by utilizing the integral line-of-sight guidance,disturbance observer,auxiliary dynamical system and tracking differentiator.Integral line-of-sight guidance compensates the drift effects from the kinematic level caused by the environment disturbances including wind,wave,and ocean currents.Meanwhile,disturbance observers are introduced to provide accurate estimations of the unknown disturbances in the attitude of yaw and surge,and the auxiliary dynamical system is used to solve the problem of input saturation.Subsequently,the application of tracking differentiator can simplify the derivative of the intermediate function calculation and make the control laws simple and effective.Secondly,in view of the path following control problem of underactuated unmanned surface vessel with external disturbances and dynamical uncertainties,and considering the input saturation,robust adaptive path following control laws are designed by utilizing the improved integral line-of-sight guidance,and the adaptive radial basis function neural networks.By introducing a time-delay sideslip angle estimator and a finite-time current observer into the integral line-of-sight guidance,the ocean currents can be compensated and suppressed well,and an accurate sideslip angle can be provided under the condition of insufficient partial attitude measurement information.In addition,the adaptive radial basis function neural networks are used to obtain satisfied dynamic uncertainties approximation.Similarly,auxiliary dynamic systems are introduced to solve the problem of input saturation.Then,aiming at the path following problem with external disturbances and dynamic uncertainties,with the consideration of prescribed performance,robust adaptive path following control laws are proposed by applying the line-of-sight guidance,the composite adaptive integral sliding mode control and adaptive radial basis function neural networks.Based on the typical line-of-sight guidance and the prescribed performance function,the performance of the path following errors is guaranteed.The combined adaptive integral sliding mode and radial basis function neural network method can facilitate the dynamics systems design with satisfied disturbance rejection and dynamic uncertainties estimation performance,where the reconstructed sliding mode surfaces eliminate the approaching process and sliding mode chattering.Finally,the numerical simulations under the above designed control strategies are carried out with the aid of Matlab/Simulink.The simulation results show that these control strategies are suitable for the general parameterized predefined path and effectively overcome the time-varying disturbances,dynamic uncertainties,input saturation and other problems,so as to realize the goal of path following.