Research On Constraint Control Methods For Dynamic Positioning Vessel Trajectory Tracking

Dynamic positioning vessels can effectively perform complex operational tasks at sea with high requirements for maneuverability and safety,such as submarine pipeline laying,marine mine-laying and mine clearance,and tracking and recovering underwater vehicle operations etc.All these require dynamic positioning vessels to move precisely along the pre-defined trajectory to ensure the safety and economy of operation.However,in the practical engineering,the various constraints of dynamic positioning vessel’s environment and its own characteristics are usually the main factors that limit its high performance.Therefore,it is of great significance to study the constraint control method for trajectory tracking of dynamic positioning vessels.This paper focuses on how we should introduce unknown external disturbances,model uncertainties,system state constraints,system velocity state unknown constraints,actuator input saturation and input change rate saturation constraints and actuator energy consumption constraints into the design of dynamic positioning vessel trajectory tracking controller to make it closer to the real vessel characteristics,so as to improve the tracking accuracy,operation safety and economy of dynamic positioning vessels,which includes the following aspects:(1)Based on the mathematical model of the six-degree-of-freedom motion of the dynamic positioning vessels,the mathematical model of the three-degree-of-freedom motion of the dynamic positioning vessels to be used for the design of the trajectory tracking constraint controller in the subsequent chapters of the dissertation was given.The main technical derivations and definitions for the control algorithm and stability analysis were also given to lay the foundation for the subsequent design of the trajectory tracking constraint controller for the power positioning vessels.(2)In order to improve the trajectory tracking accuracy and system control performance of dynamic positioning vessels,a trajectory tracking constraint control method of dynamic positioning vessels based on barrier Lyapunov function was proposed considering the input saturation constraint of actuator and system output constraints.Firstly,the output constraint controller was designed by using barrier Lyapunov function combined with backstepping control method;secondly,the input saturation constraint of actuator was considered based on the output constraints of the system,and the control law was designed by using the hyperbolic tangent function to approximate the input saturation nonlinearity,designing the adaptive law to estimate the unknown upper bound of the compound disturbance of the system,and combining the nussbaum technique with the median value theorem;finally,the stability proof of the closed-loop control system based on the Lyapunov stability theory was completed based on the barrier Lyapunov function,and it is verified through simulation that the designed control method can realize the trajectory tracking control of the dynamic positioning vessels under the external environmental disturbances,input saturation constraints and output constraints,which improved the system trajectory tracking accuracy and ensured the robustness of the system against the compound disturbances.(3)In order to improve the trajectory tracking accuracy and system control performance of the dynamic positioning vessels,a prescribed performance constraint control method for trajectory tracking of dynamic positioning vessels based on disturbance estimator was proposed considering the input saturation constraints and system state constraints.Firstly,the input saturation nonlinearities was approximated by hyperbolic tangent function;secondly,to further design the actual control law,auxiliary variables are introduced to augment the control system model;then,a finite-time prescribed performance function was designed,and the prescribed performance and dynamic surface techniques were used in the backstepping design framework to make the system tracking error satisfy the predetermined transient and steady-state performance in finite time while the system state does not violate the constraints.On this basis,a fractional order disturbance estimator was designed to estimate the external unknown disturbances,combined with nussbaum technique to deal with the time-varying control gain of auxiliary variables,and then the controller was designed under the framework of backstepping design;finally,according to Lyapunov stability theory,the stability proof of closed-loop control system based on fractional disturbance estimator was completed,and it was verified through simulation that the designed control method could realize the trajectory tracking control of dynamic positioning vessels under the external environment disturbances,input saturation constraints and state constraints,which improved the performance of the control system and the robustness of the control system against external disturbances.(4)In order to solve the problems of time-varying asymmetric state constraints,unknown velocity state constraints and actuator input saturation constraints when a dynamic positioning vessel performed trajectory tracking task in a fixed channel,a neural network-based control method of prescribed performance constraints for dynamic positioning vessel trajectory tracking was proposed.Firstly,in view of the unknown velocity state of the system,the radial basis function neural network state observer was used to estimate the velocity state information of the dynamic positioning vessels;secondly,the speed performance function was designed,and the error coordinate transformation was carried out in combination with the system tracking error,and further in the backstepping design framework,the time-varying asymmetric barrier Lyapunov function was used to combine the prescribed performance and dynamic surface technique to ensure that the system state met the time-varying asymmetric constraints,while enabling the system tracking error to converge to the specified set at the specified convergence speed in finite time to meet the preset transient performance and steady-state performance;then,an auxiliary dynamic system was constructed to handle the actuator input saturation constraint,and a neural network is used to approximate online the unknown nonlinear uncertainty term consisting of the system model parameters and external disturbances,and then the controller is designed in the backstepping design framework;finally,the stability proof of the closed-loop control system based on the radial-based neural network was completed based on the Lyapunov stability theory,and it is verified through simulation that the designed control method can enable the dynamic positioning vessels to achieve the trajectory tracking control function under the external environmental disturbances,model uncertainties and multiple constraints,and at the same time improve the control system performance and ensure the robustness of the system against external disturbances and model uncertainties.(5)In order to solve the problem of excessive energy consumption in high-precision trajectory tracking tasks of dynamic positioning vessels,considering the energy consumption constraint of actuator,input saturation constraint and input change rate saturation constraint,an event triggered prescribed performance constraint control method for trajectory tracking of dynamic positioning vessels was proposed.Firstly,the event trigger error condition was designed;secondly,under the backstepping design framework,the controller was designed by using the speed performance function,combined with prescribed performance,command filtering technique and radial basis function neural network.On the one hand,the input saturation constraints and the input rate of change saturation constraints were solved,and on the other hand,the compensation tracking error of the system converged to a predetermined set at a specified convergence rate,satisfied the predetermined transient and steady-state performance,thus ensured that the system satisfied the state constraints.The unknown nonlinear functions in the virtual control law and the real control law were approximated online by neural network.The controller was able to make the actuator execute on demand by event trigger condition,and effectively deal with the energy consumption constraint of the actuator;finally,according to Lyapunov stability theory,the stability proof of closed-loop control system based on adaptive event trigger and the analysis of the minimum event trigger time interval were completed,and it was verified through simulation that the designed control method could enable the dynamic positioning vessels to achieve the time-triggered trajectory tracking control function under the external environment disturbances and model uncertainties and constraints,and at the same time improve the control performance of the system and ensure the robustness of the system against external disturbances and model uncertainties.