Trajectory Tracking Control Of Tracked Marine Dredging Robot

To solve the key problems of tracked dredging robot trajectory tracking control under the uncertainty of external disturbances and the dynamic uncertainty of mathematical model during the construction,combined with the dredging operation scheme of caisson in specific projects,this research topic is selected as “trajectory tracking control of tracked marine dredging robot”,the theoretical exploration based on the requirements of dredging engineering practice has been carried out systematically in this thesis,which provides theoretical and technical support for intelligent control system of tracked dredging robot to improve the efficiency of trajectory tracking and reduce safety risks.Considering the actual construction characteristics of tracked dredging robot,a type of kinematics model whose center of mass does not coincide with the geometric center is constructed by using coordinate transformation method.At the same time,considering the influence of the dynamic characteristics of the tracked dredging robot on the actual control,the lagrangian method is used to construct the dynamic model,thereby the tracked dredging robot's global motion mathematical model is obtained.To solve the problem of unknown bounded time-varying disturbances,the adaptive technology is used to estimate the unknown disturbances,and at the same time,considering the simplicity of the control law structure,an adaptive self-regulation PID(Proportional,Integral and Derivative)trajectory tracking control law is proposed,this control law not only has the the simple structure of PID control law,but also can estimate the external disturbances in real-time,and realize the self-regulation of gain coefficient.To further solve the problems of dynamic uncertainties of the mathematical model and the unknown bounded time-varying disturbances,the radial basis function(RBF)neural network(NN)is used to reconstruct the dynamic and unknown disturbances of uncertain models,a trajectory tracking control law based on adaptive RBF neural network is proposed by using deep-rooted information based the robust neural network adaptive approach.At the same time,to solve the computational load problem of adaptive NN trajectory tracking control,the minimum learning parameter(MLP)is used for engineering realization easily.The stability analyses of the control laws proposed in this thesis are carried out by using Lyapunov stability theory,and numerical simulation programming is used to verify the effectiveness of the control laws.This research has important practical significance for promoting the intelligent development of underwater engineering robots.