| The Unmanned surface vessel,as a kind of small marine motion equipment,is becoming gradually more modular and intelligent with the rapid development of various high technologies(such as new energy,artificial intelligence,5G communication,etc.).The core technologies applied in the unmanned surface vehicle are constantly iterating and updating,which provides a reliable guarantee for it to complete different tasks in various complex and extreme environments.Due to the complexity of the ocean environment,how to accurately control the unmanned surface vessel in the complex and changeable marine environment is the premise of accomplishing other complex tasks.Among all the branches of the motion control field of unmanned surface vessels,the path following control problem will be researched in this paper.The main contents are as follows:First,to solve the path following control problem of underactuated unmanned surface vessels with the presence of unknown external time-varying disturbances,a path following controller was designed by combining line-of-sight guidance law with the dynamic control law.In the guidance system,the integral term of the adaptive integral line-of-sight guidance law was utilized to compensate for the influence of external disturbances on the position tracking errors from the kinematics level.In the dynamic control system,an adaptive path following control law was designed by applying the backstepping method.The reduced-order extended state observer was introduced to estimate unknown external time-varying disturbances,and the tracking differentiator was applied to simplify the derivative calculation of the control law.The effectiveness of the proposed control strategy was verified by stability analysis and simulation experiments.Secondly,an adaptive path following control strategy based on improved adaptive integral line-of-sight guidance law was proposed for dealing with the path following control problem of underactuated unmanned surface vessels exposed to unknown time-varying ocean currents.In the guidance system,the reduced-order ESO was introduced in the IAILOS guidance law to estimate the unknown time-varying ocean current velocities and compensate for the effects of unknown time-varying ocean currents from the kinematics level.In the dynamic control system,the problem of unknown time-varying disturbances and dynamic uncertainties were settled by utilizing the good approximation characteristics of the RBF neural network.Meanwhile,the robustness of the integral sliding mode controller was improved.Stability analysis and simulation experiments were carried out to demonstrate the effectiveness and superiority of the proposed path following strategy based on the IAILOS guidance law.Finally,considering the situation that the unknown time-varying sideslip angle could not satisfy the slow time-varying and approximately small angle,an adaptive path following control strategy based on the ELOS guidance law and improved RBF neural network was proposed for achieving accurately path following control task.In the guidance system,the reduced-order ESO in the ELOS guidance law was introduced to accurately estimate the unknown timevarying sideslip angle and obtain a more accurate ideal heading angle.In the dynamic control system,a predictor was introduced to improve the traditional RBF neural network.The robustness and transient performance of the controller were enhanced by the RBF neural based on the estimation errors of the predictor.Stability analysis and simulation experiments were provided to validate the effectiveness and superiority of the proposed path following strategy based on the ELOS guidance law. |
