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computers in agriculture and natural resources, Orlando, July 2006, pp 612–617
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greenhouse climate for reducing energy and water consumption. Comput Electron Agric
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robust control. Comput Electron Agric 61:96–107
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the 11th Brazilian Congress of thermal sciences and engineering, ENCIT 2006 Brazilian
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40(3):815–821
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robotics and automotive mechanics conference, CERMA 2011, pp 283–288
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predictive control using the particle swarm optimization algorithm. Comput Electron Agric
49:330–344
Chalabi ZS, Bailey BJ, Wilkinson DJ (1996) A real-time optimal control algorithm for
greenhouse heating. Comput Electron Agric 15:1–13
Chalabi Z, Zhou W (1996) Optimal control methods for agricultural systems. Acta Hortic
406:221–228
Chalabi ZS, Biro A, Bailey BJ, Aikman DP, Cockshull KE (2002a) Optimal control strategies for
carbon dioxide enrichment in greenhouse tomato crops-part 1: using pure carbon dioxide.
Biosyst Eng 81(4):421–431
Chalabi ZS, Biro A, Bailey BJ, Aikman DP, Cockshull KE (2002) Optimal control strategies for
carbon dioxide enrichment in greenhouse tomato crops-part 2: using the exhaust gases of
natural gas fired boilers. Biosyst Eng 81(3):323–332
Cheng M, Yuan H, Cai Z, Wang N (2013) Environment control method in greenhouse based on
global variable prediction model. Trans Chin Soc Agric Eng 29:177–183
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crop using genetic algorithms. Appl Soft Comput 9:13–19
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Inc, Natick
De Weck OL (2004) Multiobjective optimization: history and promise. CJK-OSM3, Kanazawa
Deng L, Wang H (2006) Fuzzy logic technology for modeling of greenhouse crop transpiration
rate. In: Sixth international symposium on instrumentation and control technology: sensors,
416
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integrated approach. Wageningen Pers, Wageningen, p 279
Bernardo JI, Silverio M, Amancio SM, Atarassi RT, Hirakawa AR (2006) Analytical modeling in
greenhouse for simulation and optimized multivariable control. In: 4th World Congress on
computers in agriculture and natural resources, Orlando, July 2006, pp 612–617
Blasco X, Martínez M, Herrero JM, Ramos C, Sanchis J (2007) Model-based predictive control of
greenhouse climate for reducing energy and water consumption. Comput Electron Agric
55:49–70
Bennis N, Duplaix J, Enéa G, Haloua M, Youlal H (2008) Greenhouse climate modeling and
robust control. Comput Electron Agric 61:96–107
Berenguel M, Yebra LJ, Rodríguez F (2003) Adaptive control strategies for greenhouse
temperature control. In: European control conference, Cambridge, U.K
Bounaama F, Draoui B (2011) Greenhouse environmental control using optimized MIMO PID
tecnique. Sens Transduc 133:44–52
Blum EK, Li LK (1991) Approximation theory and feedforward networks. Neural Networks
4:511–515
Braga W (2006) Optimization of radiative heat transfer inside a greenhouse. In: Proceedings of
the 11th Brazilian Congress of thermal sciences and engineering, ENCIT 2006 Brazilian
Society of mechanical science and engineering, ABCM, Curitiba, Brazil
Bryson AE Jr (1999) Dynamic optimization. Addison-Wesley, California
Camacho EF, Bordons C (1998) Model predictive control. Springer-Verlag, London, p 280
Caponetto R, Fortuna L, Nunnari G, Occhipinti L, Xibilia MG (2000) Soft computing for
greenhouse climate control. IEEE Trans Fuzzy Syst 8(6):753–760
Castañeda-Miranda R, Ventura-Ramos E, Peniche-Vera RR, Herrera-Ruiz G (2006) Fuzzy
greenhouse climate control system base on a field programmable gate array. Biosyst Eng
94:165–177
Center B, Verma BP (1997) A fuzzy photosynthesis model for tomato. Trans ASAE
40(3):815–821
Cepeda P, Romero D, Ponce P, Molina A (2011) Fuzzy C-means clustering technique applied for
modeling parameters of an intelligent greenhouse open control system. In: IEEE electronics,
robotics and automotive mechanics conference, CERMA 2011, pp 283–288
Coelho JP, de Moura Oliveira PB, Boaventura Cunha J (2005) Greenhouse air temperature
predictive control using the particle swarm optimization algorithm. Comput Electron Agric
49:330–344
Chalabi ZS, Bailey BJ, Wilkinson DJ (1996) A real-time optimal control algorithm for
greenhouse heating. Comput Electron Agric 15:1–13
Chalabi Z, Zhou W (1996) Optimal control methods for agricultural systems. Acta Hortic
406:221–228
Chalabi ZS, Biro A, Bailey BJ, Aikman DP, Cockshull KE (2002a) Optimal control strategies for
carbon dioxide enrichment in greenhouse tomato crops-part 1: using pure carbon dioxide.
Biosyst Eng 81(4):421–431
Chalabi ZS, Biro A, Bailey BJ, Aikman DP, Cockshull KE (2002) Optimal control strategies for
carbon dioxide enrichment in greenhouse tomato crops-part 2: using the exhaust gases of
natural gas fired boilers. Biosyst Eng 81(3):323–332
Cheng M, Yuan H, Cai Z, Wang N (2013) Environment control method in greenhouse based on
global variable prediction model. Trans Chin Soc Agric Eng 29:177–183
Dai C, Yao M, Xie Z, Chen C, Liu J (2009) Parameter estimation for growth model of greenhouse
crop using genetic algorithms. Appl Soft Comput 9:13–19
Demuth H, Beale M, Hagan M (2007) Neural network toolbox 5: user’s guide. The MathWorks
Inc, Natick
De Weck OL (2004) Multiobjective optimization: history and promise. CJK-OSM3, Kanazawa
Deng L, Wang H (2006) Fuzzy logic technology for modeling of greenhouse crop transpiration
rate. In: Sixth international symposium on instrumentation and control technology: sensors,
416
I. L. López-Cruz et al.