Controller with the PID Parameters Optimization by PSO for a 6-DOF Robotic Arm

Kun Jui Wu*, Mei Yung Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper uses the Denavit-Hartenberg (D-H) convention to derive the motion model, including the kinematics and dynamics, of the 6-DOF robotic arm. In order to overcome the highly nonlinear issue of the motion model, we linearize the nonlinear system by T-S fuzzy modeling. Based on the linearized model, we can control the robotic arm through a parallel distributed PID controller. According to the requirements of the continuous trajectory, the length limits of each arm, and the angle limits of the joint rotation, the design of motion form needs to fit the motion model of the robot arm. The parameters of the PID controller are found by the particle swarm optimization (PSO). According to the system transfer function, the controller with the optimized parameters can resist the uncertainty of the system, and make the robot arm move more efficiency and smoothly. The system is simulated in Matlab with Simulink, and its analysis scope includes fixed-point and trajectory tracking. Compared with the traditional PID controller, the results show that the proposed controller has less stability errors, overshoots and vibrations.

Original languageEnglish
Title of host publication2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350305791
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023 - Penghu, Taiwan
Duration: 2023 Oct 262023 Oct 29

Publication series

Name2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023

Conference

Conference2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023
Country/TerritoryTaiwan
CityPenghu
Period2023/10/262023/10/29

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence
  • Control and Optimization
  • Logic

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