Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

Sensors

Haigen Hu¹  Lihong Xu²  Ruihua Wei² 

[1] School of Information Engineering, Zhejiang Agriculture & Forestry University, Lin’an City 311300, Zhejiang Province, China; E-Mail:;Department of Control Science and Engineering, Tongji University, Shanghai 200092, China; E-Mails:

关键词: greenhouse environment control;    PID control;    feedback control;    multi-objective optimization;    evolutionary algorithms;    nonlinear systems;   

DOI  :  10.3390/s110605792

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.