Research On Adaptive Non-singular Terminal Sliding Mode Trajectory Tracking Control Of Manipulator

In the wake of the development of modern manufacturing industry and the constant improvement of scientific and technological level.Robot engineering has also evolve rapidly.Manipulator is a comparatively linchpin part in the field of robot control.It can be used in industrial manufacturing,fire protection,medical treatment,national defense,aerospace technology and other fields.In order to ensure the safe,efficient and reliable operation of the robot system,manipulator control inevitably becomes an indispensable part of the robot design process.Due to uncertainty and interference(such as external complex environmental factors),the control of manipulator is very challenging.In practical application,when the robot system works in complex environment,it will seriously affect the control accuracy of the robot system and increase the unnecessary energy loss of the system due to external interference and internal friction of the system.Compared with the traditional sliding mode control,The terminal sliding mode lead into a nonlinear term based on the traditional sliding mode surface,which increases its convergence speed near the sliding mode surface,but also brings the singularity problem.In addition,terminal sliding mode control can not achieve accurate control without accurate manipulator dynamic model.Taking the manipulator with modeling error and external disturbance as the research object,the appropriate control method is selected to carry on study the trajectory tracking of the manipulator system The main study content of this paper are as follows:The structure of the manipulator system is briefly introduced,and the complexity and nonlinearity of the system are analyzed.Considering the influence of system parameters,model and interference,a simplified manipulator model is established by Lagrange modeling method,which is convenient for the subsequent trajectory tracking analysis and control of manipulator system.The sliding mode variable structure is introduced,and the devise process of its sliding mode surface is analyzed.For the manipulator system with external disturbance,a nonsingular terminal sliding mode controller is designed.The robust control term is added to the control rate design to eliminate the influence of external disturbance on system control and chattering,enhance the adaptability of the algorithm in practical application,Lyapunov stability theory is applyed to certificate the stability of the system.Simulink is used to simulate and compare the control system to further verify the control performance and optimization of the algorithm.The radial neural network algorithm is introduced and combined with the terminal sliding mode control method.Using the characteristics of RBF neural network,such as global approximation ability,simple structure,self-learning and fast convergence speed,a nonsingular fast terminal sliding mode adaptive trajectory tracking method based on RBF neural network is designed to deal with the uncertain parameters of the system,The robust control term is added to the controller to better estimate the error,which effectively overcomes the dependence of the ordinary control method on the accurate model of the manipulator.Eventually,the Lyapunov function is devised to certificate the stability of the system in theory.The simulation results show that the proposed control method can be a very good to the desired trajectory tracking and effectively restrain the chatteringFinally,the work of the full text is summarized,and the next work is prospected.