PSO-based optimized neural network PID control approach for a four wheeled omnidirectional mobile robot

Abstract

The demand for automation using mobile robots has been increased dramatically in the last decade. Nowadays, mobile robots are used for various applications that are not attainable to humans. Omnidirectional mobile robots are one particular type of these mobile robots, which has been the center of attention for their maneuverability and ability to track complex trajectories with ease, unlike their differential type counterparts. However, one of the disadvantages of these robots is their complex dynamical model, which poses several challenges to their control approach. In this work, the modeling of a four-wheeled omnidirectional mobile robot is developed. Moreover, an intelligent Proportional Integral Derivative (PID) neural network control methodology is developed for trajectory tracking tasks, and Particle Swarm Optimization (PSO) algorithm is utilized to find optimized controller's weights. The simulation study is conducted using Simulink and Matlab package, and the results confirmed the accuracy of the proposed intelligent control method to perform trajectory tracking tasks.