Design PID Neural Network Controller for Trajectory Tracking of Differential Drive Mobile Robot Based on PSO | ||
| Engineering and Technology Journal | ||
| Article 12, Volume 37, 12A, December 2019, Pages 574-583 PDF (1.17 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.30684/etj.37.12A.12 | ||
| Authors | ||
| Mohamed J. Mohamed; Mohammed K. Hamza | ||
| Department of Control and Systems Engineering, University of Technology - Iraq | ||
| 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. | ||
| Keywords | ||
| Two Wheel Mobile Robot; PID Neural Network Controller; Particle swarm optimization | ||
| References | ||
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