Sensors 2011, 11(6), 5792-5807; doi:10.3390/s110605792
Article

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

1 School of Information Engineering, Zhejiang Agriculture & Forestry University, Lin’an City 311300, Zhejiang Province, China 2 Department of Control Science and Engineering, Tongji University, Shanghai 200092, China
* Author to whom correspondence should be addressed.
Received: 26 March 2011; in revised form: 18 May 2011 / Accepted: 20 May 2011 / Published: 27 May 2011
(This article belongs to the Section Physical Sensors)
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Abstract: This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production.
Keywords: greenhouse environment control; PID control; feedback control; multi-objective optimization; evolutionary algorithms; nonlinear systems

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MDPI and ACS Style

Hu, H.; Xu, L.; Wei, R.; Zhu, B. Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms. Sensors 2011, 11, 5792-5807.

AMA Style

Hu H, Xu L, Wei R, Zhu B. Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms. Sensors. 2011; 11(6):5792-5807.

Chicago/Turabian Style

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun. 2011. "Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms." Sensors 11, no. 6: 5792-5807.

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