Designing of PSO Tuned PID Controller for Ball Balancer Arrangement and Comparative Analysis with Classical PID and Fuzzy Logic Controller

Abstract

This paper presents design and control of a 2D Ball Balancer Arrangement using Particle Swarm Optimization (PSO) algorithm. The paper also compares the results of proposed control technique with Classical PID controller and Fuzzy logic controller. The Ball Balancer Arrangement is a nonlinear system with complex plant transfer function. Classical control methods such as Classical PID and Fuzzy logic controller are also able to control the Ball Balancer Arrangement but manual tuning and rule base optimization is slow and inefficient. PSO tuning on the other hand, is a heuristic approach which finds the solution with its own experience rather than relying on human expertise. Search space, population size, cost function and number of iterations are the few key parameters that PSO requires to find optimal gains for PID controller. The comparative analysis of PSO tuned PID with classical control methods show improved trajectory of the ball in terms of delay time, rise time, and settling time. The designing and simulation have been successfully performed in MATLAB/ Simulink environment.