Design and Comparison of PSO, SA and GA tuned PID Controller for Ball Balancer Arrangement

Apoorv Surana, B. Bhushan
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引用次数: 4

Abstract

This paper presents design and control of a 2D Ball Balancer Arrangement using PID controller tuned with Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic algorithm (GA). The paper also compares the results of proposed control techniques with Classical PID controller. The Ball Balancer Arrangement is a non-linear system with complex plant transfer function. Classical control method such as Classical PID is able to control the Ball Balancer Arrangement but performance is dependent on human expertise. PSO, SA and GA are heuristic algorithms which can find the best solution without the need of human experience. Heuristic algorithms improve the solution in every iteration based on cost function minimization. The comparative analysis of PSO, SA and GA tuned PID is shown in terms of delay time, rise time, and settling time. The designing and simulation have been successfully performed in MATLAB/ Simulink environment.
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球平衡器布置的PSO、SA和GA整定PID控制器的设计与比较
本文采用粒子群优化(PSO)、模拟退火(SA)和遗传算法(GA)相结合的PID控制器,设计和控制了一种二维球平衡器布置。本文还将所提出的控制方法与经典PID控制器的控制效果进行了比较。球平衡器布置是一个具有复杂植物传递函数的非线性系统。经典的控制方法,如经典PID能够控制球平衡器的排列,但性能取决于人的专业知识。粒子群算法、粒子群算法和遗传算法都是不需要人类经验就能找到最优解的启发式算法。启发式算法在每次迭代中基于成本函数最小化来改进解。从延迟时间、上升时间和稳定时间三个方面对PSO、SA和GA调谐PID进行了比较分析。在MATLAB/ Simulink环境下成功地进行了设计和仿真。
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