Greenhouse climate modelling and robust control

被引:142
作者
Bennis, N. [1 ,4 ]
Duplaix, J. [2 ]
Enea, G. [2 ]
Haloua, M. [3 ]
Youlal, H. [4 ]
机构
[1] Rabat Inst, ENSET Rabat, Rabat, Morocco
[2] CNRS, UMR 6168, LSIS, F-13397 Marseille 20, France
[3] Ecol Mohammadia Ingenieurs, Rabat, Morocco
[4] Fac Sci Rabat, UFR ATI, Rabat, Morocco
关键词
greenhouse climate models; parameters identification; H-2 robust control; LMI;
D O I
10.1016/j.compag.2007.09.014
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
This paper deals with the problem of modelling and control of greenhouses inside climate defined by two variables: the temperature and hygrometry. The control objective aims to ensure a favourable inside microclimate for the culture development and to minimize the production cost. Achievingthis objective is difficult, due to the complexityof the phenomena involved in the plant growth process: the two variables are correlated and very sensitive to the outside weather and also to many other practical constraints (actuators, moistening cycle...). we propose highly performing regulation for the greenhouse internal state based on H-2 robust control design. It involves a linear control model of the process, obtained by an off-line parametric identification technique. Evaluation of control performance is achieved through a benchmark physical model derived from energy balance for the temperature and water mass balance for the hygrometry. The main steps in deriving this nonlinear model are also outlined. A successful feasibility study of the proposed controller is presented for an experimental greenhouse located at the University of South Toulon-Var (France). Simulation results show promising performances despite the high interaction between the process internal variables and the high impact on these variables of the external meteorological conditions. (c) 2008 Published by Elsevier B.V.
引用
收藏
页码:96 / 107
页数:12
相关论文
共 18 条
[1]   Multirate adaptive temperature control of greenhouses [J].
Arvanitis, KG ;
Paraskevopoulos, PN ;
Vernardos, AA .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2000, 26 (03) :303-320
[2]  
BENNIS N, 2005, 33 INT S ACT TASKS A, P265
[3]  
Boaventura Cunha J., 2003, EFITA 2003 C 5 9 JUL, P823
[4]  
BOUCHOUICHA M, 2002, STA 2002, P22
[5]   Greenhouse air temperature predictive control using the particle swarm optimisation algorithm [J].
Coelho, JP ;
Oliveira, PBD ;
Cunha, JB .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2005, 49 (03) :330-344
[6]   Real-time parameter estimation of dynamic temperature models for greenhouse environmental control [J].
Cunha, JB ;
Couto, C ;
Ruano, AE .
CONTROL ENGINEERING PRACTICE, 1997, 5 (10) :1473-1481
[7]  
de Oliveira M. C., 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304), P3611, DOI 10.1109/CDC.1999.827913
[8]   STATE-SPACE SOLUTIONS TO STANDARD H-2 AND H-INFINITY CONTROL-PROBLEMS [J].
DOYLE, JC ;
GLOVER, K ;
KHARGONEKAR, PP ;
FRANCIS, BA .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1989, 34 (08) :831-847
[9]  
ENEA G, 2002, 224SI00 U TOUL
[10]   Neural network models in greenhouse air temperature prediction [J].
Ferreira, PM ;
Faria, EA ;
Ruano, AE .
NEUROCOMPUTING, 2002, 43 :51-75