Neural predictive control of broiler chicken growth

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 43, Issue 6 PART 1, 2010, Pages 311-316

  Demmers, T G M ^a   Cao, Y ^b   Gauss, S ^a   Lowe, J C ^a   Parsons, D J ^b   Wathes, C M ^a  

^a ROYAL VETERINARY COLLEGE   (United Kingdom)

^b CRANFIELD UNIVERSITY   (United Kingdom)

Author keywords

Broiler; Growth; Neural network models; Optimal control; Predictive control; System identification

Indexed keywords

ANIMALS; GROWTH (MATERIALS); IDENTIFICATION (CONTROL SYSTEMS); NONLINEAR SYSTEMS; PREDICTIVE CONTROL SYSTEMS; RELIGIOUS BUILDINGS;

BROILER; MEAN RELATIVE ERROR; NEURAL NETWORK MODEL; NEURAL-PREDICTIVE CONTROLS; NON-LINEAR SYSTEM IDENTIFICATION; OPTIMAL CONTROLS; PREDICTIVE CONTROL; PRODUCTION EFFICIENCY;

RECURRENT NEURAL NETWORKS;

EID: 80051893359     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20100707-3-BE-2012.0061     Document Type: Conference Paper

References (18)

1. J.M. Aerts, S. Van Buggenhout, E. Vranken, M. Lippens, J. Buyse, E. Decuypere, and D. Berckmans. Active control of the growth trajectory of broiler chickens based on online animal responses. Poultry Science, 82(12): 1853-1862, 2003a. (Pubitemid 38641807)
2. J.M. Aerts, M. Lippens, G. De Groote, J. Buyse, E. Decuypere, E. Vranken, and D. Berckmans. Recursive prediction of broiler growth response to feed intake by using a time-variant parameter estimation method. Poultry Science, 82(1):40-49, 2003b. (Pubitemid 38642000)
3. H. Ahmadi and M. Mottaghitalab. Hyperbolastic models as a new powerful tool to describe broiler growth kinetics. Poultry Science, 86:2461-2465, 2007. (Pubitemid 350097232)
4. H. Ahmadi and M. Mottaghitalab. Predicting performance of broiler chickens from dietary nutrients using group method of data handling-type neural networks. British Poultry Science, 49(3):315-320, 2008. (Pubitemid 351882555)
5. R.K. Al-Seyab and Y. Cao. Differential recurrent neural network based predictive control. Computers and Chemical Engineering, 32(7):1533-1545, 2008a. (Pubitemid 351608423)
6. R.K. Al-Seyab and Y. Cao. Nonlinear system identification for predictive control using continuous time recurrent neural networks and automatic differentiation. Journal of Process Control, 18(6):568-581, 2008b. (Pubitemid 351645107)
7. Aviagen. Broiler management manual. Aviagen Ltd, Newbridge, Midlothian, Scotland, UK., 2002.
8. A. Butterworth and D. Arnould. Standardisation of measures of broiler lameness. In B. Forkman and L. Keeling, editors, Assessment of Animal Welfare Measures for Layers and Broilers., number 9 in Welfare Quality Reports, pages 31-39, Cardif, UK, 2009. Cardif University.
9. O. Cangar, J.-M. Aerts, E. Vranken, and D. Berckmans. Effects of different target trajectories on the broiler performance in growth control. Poultry Science, 87(11): 2196-2207, 2008.
10. Y. Cao. A formulation of nonlinear model predictive control using automatic differentiation. Journal of Process Control, 15(8):851-858, 2005. (Pubitemid 40999984)
11. D.R. Charles and A.W. Walker. Poultry Environment Problems. A guide to solutions. Nottingham University Press, Nottingham, UK., 2002.
12. G.C. Emmans. Problems in modeling the growth of poultry. Worlds Poultry Science Journal, 51(1):77-89, 1995.
13. A.R. Frost, C.P. Schofield, S.A. Beaulah, T.T. Mottram, J.A. Lines, and C.M.Wathes. A review of livestock monitoring and the need for integrated systems. Computers and Electronics in Agriculture, 17(2):139-159, 1997. (Pubitemid 127425728)
14. A.R. Frost, D.J. Parsons, K.F. Stacey, A.P. Robertson, S.K. Welch, D. Filmer, and A. Fothergill. Progress towards the development of an integrated management system for broiler chicken production. Computers and Electronics in Agriculture, 39:227-240, 2003. (Pubitemid 36964753)
15. R.M. Gous, E.T. Moran, H.R. Stilborn, G.D. Bradford, and G.C. Emmans. Evaluation of the parameters needed to describe the overall growth, the chemical growth, and the growth of feathers and breast muscles of broilers. Poultry Science, 78(6):812-821, 1999. (Pubitemid 129555338)
16. D. Marquardt. An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal of Applied Mathematics, 11:431-441, 1963.
17. K.F. Stacey, D.J. Parsons, A.R. Frost, C. Fisher, D. Filmer, and A. Fothergill. An automatic growth and nutrition control system for broiler production. Biosystems Engineering, 89(3):363-371, 2004. (Pubitemid 39547984)
18. C.M. Wathes, H.H. Kristensen, J.-M. Aerts, and D. Berckmans. Is precision livestock farming an engineer's daydream or nightmare, an animal's friend or foe, and a farmer's panacea or pitfall? Computers and electronics in agriculture, 64(1):2-10, 2008.