Temperature control of green house system using evolutionary computation

R. Umashankari, K. Valarmathi, G. SaravanaKumar
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引用次数: 2

Abstract

This paper deals with the controlling problem of the inside temperature of the greenhouse. The control objective is to tune the control parameters for the system using evolutionary computation and to minimize the error. In this paper, the Maximal Stability Degree (MSD) based approach is applied to obtain the control parameters. When the control parameters are identified, then Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are applied to optimize the controller parameter. The simulation results show that the proposed PSO technique is effective in identifying the parameters and has resulted in a minimum value of overshoot, rise time, peak value and settling time as compared to other methods.
基于进化计算的温室系统温度控制
本文论述了温室室内温度的控制问题。控制目标是利用进化计算对系统的控制参数进行调整,使误差最小化。本文采用基于最大稳定度(MSD)的方法来获取控制参数。在确定控制参数后,采用遗传算法(GA)和粒子群算法(PSO)对控制器参数进行优化。仿真结果表明,与其他方法相比,所提出的粒子群算法在参数识别方面是有效的,并能获得最小的超调量、最小的上升时间、最小的峰值和最小的沉降时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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