Six-Axis Robot Manipulator's Dynamic Analysis And Its Sliding Mode Control

Six-axis robot is the most widely used in the industrial robots,applied to handle,weld,palletize and other working environment.It is favored with multi-degree of freedom of movement and flexibility.However,for multi-axis robots,its control problem is always been a difficult problem to solve,especially for the trajectory of the robot manipulator of the accuracy and speed.In the process of motion,the robot will be subject to external interference,the impact of the load and the uncertainty of their own modeling,these are all leading to the error of the trajectory.Therefore,in this paper,we analyzes the structure of the robot,and then mainly analyzes the control method of its trajectory.Firstly,we introduce the kinematics of the robot manipulator,and solve the attitude matrix of the six-axis robot.On this basis,the dynamics of the robot is modeled and the dynamic characteristics of the robot are analyzed.After that,a basic algorithm of trajectory control,sliding mode control(SMC)is introduced.And describing one of the biggest drawbacks is chattering,then introduced four methods to remove chattering.Comparing four methods with classical SMC,we prove the effectiveness of the four methods removing chattering.But at the same time,it can be seen that the chattering can not be completely removed,and can only be weakened to a certain extent.Then,due to the limitation of the sliding mode control method,we combined two kinds of intelligent control algorithms with the sliding mode variable structure to achieve a better control effect.The first is neural sliding mode control,the second is fuzzy sliding mode control.This paper presents a novel neural network sliding mode control and a new fuzzy sliding mode control algorithm respectively.Compared with the traditional neural network sliding mode control and fuzzy sliding mode control method,the convergence time of the proposed algorithm is shorter and the convergence effect is better,which are more applicable to the actual.Moreover,with the traditional algorithm focusing only on the theoretical results,the two methods are simulated by Matlab and Adams,and the real-time motion state of the robot can be seen through the simulation.The algorithm supports the algorithm adequately.The results of joint simulation also prove the accuracy of the algorithm.