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Design of Soft Computing Based Optimal PI Controller for Greenhouse System

Design of Soft Computing Based Optimal PI Controller for Greenhouse System

作     者:A. Manonmani T. Thyagarajan S. Sutha V. Gayathri A. Manonmani;T. Thyagarajan;S. Sutha;V. Gayathri

作者机构:Department of Electronics and Instrumentation Engineering Saveetha Engineering College Chennai India Department of Instrumentation Engineering MIT Campus Anna University Chennai India 

出 版 物:《Circuits and Systems》 (电路与系统(英文))

年 卷 期:2016年第7卷第11期

页      面:3431-3447页

学科分类:0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主  题:Greenhouse System Feedback-Feed Forward Linearization and Decoupling IMC Based PI Controller Genetic Algorithm Particle Swarm Optimization Nonlinear System 

摘      要:Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.

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