Smaller Chattering Sliding Mode Control For Trajectory Tracking Of Joint Robot

With the rapid development of robotics,people have higher requirements for precise control of their trajectories.Because sliding mode control has strong robustness and no need for precise modeling,it has become the preferred method for robot control.However,the chattering problem in sliding mode control has been plaguing people.This thesis studies the chattering problem in the sliding mode for trajectory tracking of joint robot manipulators.First,the typical sliding mode control for trajectory tracking of joint robot manipulators has been studied.On this basis,the position,velocity and acceleration upper bound of the desired trajectory in the typical sliding mode control law are replaced by their actual values,and thus a new upper bound for system uncertainties is constructed.A small chattering sliding mode control is then proposed.This control can reduce the chattering phenomenon of the robotic system effectively,but it increases the time when the system reaches the steady state.Second,using the method of the approach law,combining with a new approaching law function,a fast and small chattering sliding mode control approach is proposed.This control can improve the dynamic performance of the system and at the same time reducing the chattering phenomenon.Finally,using the genetic algorithm,a new fitness function is proposed to adjust the control parameters for the fast and small chattering continuous sliding mode control,and the performances of the controlled robotic systems are further improved.In this thesis,stabilities of the closed-loop systems with the above controls are proved theoretically by Lyapunov's direct method,and the conditions for ensuring global asymptotic tracking stability are obtained.Simulations on a two-DOF joint robot system with Matlab verify the effectiveness and improved performances of the proposed approaches.