Abstract
For industrial-grade manipulators, the study of trajectory tracking control issues provides an important guarantee for accurate and safe work. Therefore, the trajectory control input driving torque can meet the requirements of the robot arm to accurately track a given target trajectory, and the process of building a decision tree is a process of dividing the feature space. For a given training data set, a set of if-then is summarized the rule of. Based on this, this paper launches the research of multi-degree-of-freedom manipulator joint trajectory tracking control method based on decision tree. Based on the established kinematics and dynamics model of the manipulator, this paper uses a proportional-integral-derivative (PID) sliding mode controller based on the sliding mode surface of the manipulator to perform the trajectory tracking control of the end of the manipulator, and the simulation results of the improved sliding mode control are compared with the simulation results of the improved sliding mode control. The simulation results of the PID controller and the traditional sliding mode controller are compared. This paper finally verifies the effectiveness of the proposed new sliding mode controller based on the expanded state observer through the experimental platform. The speed and chattering problems of the trajectory tracking at the end of the manipulator are better than those of the controller on the experimental platform. Finally, this paper adopts the sliding mode variable structure control strategy combining the double-power reaching law and the improved terminal sliding mode surface to study the trajectory tracking control of the planar two-degree-of-freedom manipulator.
Highlights
At this stage, there is a big gap between my country and foreign countries in the theoretical discovery of industrial robot weapons and the implementation of robotic arm mechanics
In the research on the trajectory tracking control method of multi-degree-of-freedom manipulator arm based on decision tree, many scholars have studied it and achieved good results
Research and analysis of multi-degree-of-freedom manipulator joint trajectory tracking control method based on decision tree
Summary
- A fuzzy adaptive extended Kalman filter exploiting the Student’s t distribution for mobile robot tracking Xin Lai, Guorui Zhu and Jonathon Chambers. - Design and control of a multi-DOF micromanipulator dedicated to multiscale micromanipulation Yi-Ling Yang, Yan-Ding Wei, Jun-Qiang Lou et al
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