Design PID Neural Network Controller for Trajectory Tracking of Differential Drive Mobile Robot Based on PSO

Authors

• Mohamed Mohamed, Department of Control and Systems Engineering, University of Technology - IraqFollow
• Mohammed Hamza, Department of Control and Systems Engineering, University of Technology - IraqFollow

Keywords

Two Wheel Mobile Robot, PID Neural Network Controller, Particle swarm optimization

Document Type

Research Paper

Abstract

This paper introduces a nonlinear (Proportional-Integral-Derivative Neural Network) (PID NN) controller for a differential wheeled mobile robot trajectory tracking problem. This neural controller is built based on the principles of neural network (NN) and the equation of conventional structure of PID controller and is applied on kinematic model of the mobile robot. The particle swarm optimization algorithm (PSO) is utilized to find the best values of three PID NN parameters and connection weights that minimize the error between the reference path and the actual path. The results illustrate that the PID NN controller has a satisfied ability to make the mobile robot tracking any path with good performance, high accuracy and acceptable robustness.

Recommended Citation

Mohamed, Mohamed and Hamza, Mohammed (2026) "Design PID Neural Network Controller for Trajectory Tracking of Differential Drive Mobile Robot Based on PSO," Engineering and Technology Journal: Vol. 37: Iss. 12, Article 12.
DOI: https://doi.org/10.30684/etj.37.12A.12

DOI

10.30684/etj.37.12A.12

First Page

574

Last Page

583