基于遗传算法和粒子群算法的PID CSTR温度控制的比较研究

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI:10.1109/ICETCCT.2017.8280312

Swapnadeep Baruah, L. Dewan

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引用次数: 12

摘要

工业过程是高度集成化的过程，连续搅拌槽式反应器(CSTR)是其中的重要组成部分。为了在系统中有效地工作，需要对CSTR的某些参数进行控制。本文提出了一种采用齐格勒尼科尔斯整定的PID控制器模型，用于CSTR的温度控制。优化技术采用遗传算法(GA)和粒子群算法(PSO)对控制器参数进行优化，并在考虑暂态和稳态特性的情况下进行了对比研究。结果表明，与其他优化方法相比，粒子群优化方法在不考虑干扰的情况下，对控制器参数的优化效果最好。

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A comparative study of PID based temperature control of CSTR using Genetic Algorithm and Particle Swarm Optimization

Industrial processes are highly integrated processes and Continuous Stirred Tank Reactor (CSTR) is an integral part of it. To work efficiently in a system certain parameters of the CSTR needs to be controlled. This paper presents a model of the PID controller using Zeigler Nichols tuning for the temperature control of the CSTR. Optimization techniques Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been used to optimize the controller parameters and a comparative study is done taking the transient and steady-state characteristics into considerations. It is found that the controller parameters are best optimized by Particle Swarm Optimization irrespective of the disturbances than other optimization techniques.

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2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT)

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