Optimal Proportional Integral Derivative Controller for Two-Wheeled Self- Balanced Mobile Robots Based on Particle Swarm Algorithm

Authors

  • Hasanain H. Mohsin Department of Electrical Engineering Techniques, BETC, Southern Technical University, Basrah, Iraq
  • Ammar A. Aldair Electrical Engineering Department, College of Engineering ,University of Basrah, Basrah, Iraq
  • Walid A. Al-Hussaibi Department of Electrical Engineering Techniques, BETC, Southern Technical University, Basrah, Iraq

DOI:

https://doi.org/10.31663/tqujes.12.2.452(2022)

Keywords:

TWSBR, PID, PSO, Simscape Multibody modeling, robustness controller test

Abstract

The two-wheeled self-balanced robot (TWSBR) is an important type of mobile robot for a wide range of tasks, in which stability represents a major research and technical challenge. The goal of this study is to propose an optimum control method for increasing the stability of TWSBR under perturbation effects. A proportional integral derivative (PID) controller is designed based on the particle swarm optimization (PSO) method to optimize the robot controller parameters. SimScape Multibody environment is used in this paper to examine the performance of the suggested controller without the need for the mathematical model of the considered TWSBR system. This simulation platform is used to model and visualize the robot's movements while utilizing the optimized controller. The accuracy and robustness of the designed controller are tested by changing the load placed on the mechanical structure layers during robot motion. The obtained results demonstrate the effectiveness of the suggested controller design for robot balancing during disturbance situations.

Downloads

Published

2022-12-01

How to Cite

Optimal Proportional Integral Derivative Controller for Two-Wheeled Self- Balanced Mobile Robots Based on Particle Swarm Algorithm. (2022). University of Thi-Qar Journal for Engineering Sciences, 12(2), 63-69. https://doi.org/10.31663/tqujes.12.2.452(2022)

Similar Articles

21-30 of 85

You may also start an advanced similarity search for this article.