Particle Swarm Optimization Based Control of a Differential Drive Mobile Wheeled Robot

摘要

This work aims at the efficient control of a mobile robot using optimised PID controller. The two DC motors are controlled precisely which in turn regulate the movement of the robot. Numerous techniques have been developed to enhance the PID control strategy applied to linear and non-linear systems. In this work, first the actuator model of the mobile robot is simulated and then the optimal computation techniques i.e., Simulated Annealing (SA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are considered to tune the gains of PID controller. ITAE is considered as the objective function for optimization. The comparative study reveals that PSO tuned PID provides the least ITAE and is thus used for the mobile robot. The velocity plots are analysed for various positions of wheels. The motion characteristics for different paths are also analysed which justify the effectiveness of the PSO-PID controller over the other considered techniques.