PID/Multi-Loop Control Strategy for Poultry House System Using Multi-Objective Ant Colony Optimization
Two of the main constraints of managing the livestock development are the high temperature and the relative humidity. For this reason, it is indispensable to design an optimal controller able to decrease the heat stress inside the poultry house system. In this paper, a metaheuristic method, - Ant Colony Optimization (ACO) – has been adopted with the Proportional Integral Derivative (PID) controller to control and stabilize the set point of the internal temperature and the relative humidity for the poultry house system during the hot climates. The initial stability region of the proposed first feedback controller has been obtained by using the Routh criterion stability. Then, the ACO algorithm has been employed to generate the best parameters (Kp, Ki, Kd) using the four multi-objective performances: the criterion of Integrated Squared Error (ISE), Integrated Absolute Error (IAE), Integrated Time Absolute Error (ITAE) and Integrated Time Squared Error (ITSE). The simulation results obtained show a good performance in tracking the desired set point with the disturbed poultry house process.
Copyright © 2018 Praise Worthy Prize - All rights reserved.
N. J. Daghir, Ed., Poultry production in hot climates, 2nd ed. Wallingford: CABI, 2008.
T. Banhazi et al., Issues related to livestock housing under hot climatic conditions including the animals’ response to high temperatures, Anim. Hous. Hot Clim., p. 4, 2007.
Animal housing in hot climates: A multidisciplinary view, Research Centre Bygholm, Danish Institute of Agricultural Sciences, Schüttesvej 17, 8700 Horsens, Denmark, 2006. 105p., Irenilza de Alencar Naas, 2006.
D. O. Aborisade and O. Stephen, Poultry house temperature control using Fuzzy-PID controller, IJETT Chennai, vol. 11, no. 6, pp. 310–314, 2014.
B. O. Oladayo and A. O. Titus, Pid Temperature Controller System for Poultry House System Using Fuzzy Logic, American Journal of Engineering Research (AJER), vol. 5 no. 6, pp. 183-188, 2016.
R. Manoj Manjunath and S.Janaki Raman, Fuzzy adaptive PID for Flow Control System based on OPC. IJCA Special Issue on “Computational Science-New Dimensions & perspectives", 2011.
P. I. Daskalov, K. G. Arvanitis, G. D. Pasgianos, and N. A. Sigrimis, Non-linear Adaptive Temperature and Humidity Control in Animal Buildings, Biosyst. Eng., vol. 93, no. 1, pp. 1–24, Jan. 2006.
J. P. O. B. O.Ola and O. O.Awodoye, Performance Evaluation of Particle Swarm Optimization on poultry House Temperature Control System, J. Comput. Eng. IOSR-JCE, vol. 19, no. 5, pp. 69–76, 2017.
International Commission of Agricultural Engineering, Ed., CIGR handbook of agricultural engineering. St. Joseph, MI: American Society of Agricultural Engineers, 1999.
P. I. Daskalov, Prediction of temperature and humidity in a naturally ventilated pig building, J. Agric. Eng. Res., vol. 68, no. 4, pp. 329–339, 1997.
T. Upachaban, K. Khongsatit, and T. Radpukdee, Mathematical Model and Simulation Study of a Closed-poultry House Environment, Int. J. Technol., vol. 7, no. 7, p. 1246, Dec. 2016.
Lahlouh, I., El Akkary, A., Sefiani, N., Mathematical Modelling of the Hygro-Thermal Regimeof a Poultry Livestock Building: Simulation for Spring Climate, (2018) International Review of Civil Engineering (IRECE), 9 (2), pp. 79-85.
U. C. Berkeley and A.Packard, Jacobian Linearizations, equilibrium points. ME 132, Spring, 2005.
M. Ababneh, M. Salah, and K. Alwidyanm, Linearization of nonlinear dynamical systems: A comparative study, Jordan J. Mech. Ind. Eng., vol. 5, no. 6, pp. 567–571, 2011.
T. F. E. Dale E.Seborg and Duncan A.Melichamp, Process Dynamics and Control. John Wiley & Sons, Inc., 2003.
H.-P. Huang, M. Ohshima, and I. Hashimoto, Dynamic interaction and multiloop control system design, J. Process Control, vol. 4, no. 1, pp. 15–27, 1994.
M. Dorigo and T. Stützle, Ant colony optimization. Cambridge, Mass.: MIT Press, 2004.
Jianghua Sui, An AND-OR Fuzzy Neural Network. INTECH Open Access Publisher, 2011.
M. A. Sahib and B. S. Ahmed, A new multiobjective performance criterion used in PID tuning optimization algorithms, J. Adv. Res., vol. 7, no. 1, pp. 125–134, Jan. 2016.
C. Ryan, ACM Digital Library, Association for Computing Machinery, and SIGEVO, Proceedings of the 10th annual conference on Genetic and evolutionary computation. New York, NY: ACM, 2008.
Chiha, I., Liouane, H., Liouane, N., A hybrid method based on multi-objective ant colony optimization and differential evolution to design PID DC motor speed controller, (2012) International Review on Modelling and Simulations (IREMOS), 5 (2), pp. 905-912.
Y. K. Soni and R. Bhatt, BF-PSO optimized PID controller design using ISE, IAE, IATE and MSE error criteria, Int. J. Adv. Res. Comput. Eng. Technol., vol. 2, no. 7, pp. 2333–2336, 2013.
P. A. Geraert, Métabolisme énergétique du poulet de chair en climat chaud,”INRA Prod Anim, vol. 4, no. 3, pp. 257–267, 1991.
Hamid, Z., Musirin, I., Mohamad Kerta, S., An Approach on Non-Discriminatory Losses Charge Allocation for Deregulated Power Market Using Meta-Heuristic-Optimization-Based-Electricity-Tracing (MOET), (2017) International Review of Electrical Engineering (IREE), 12 (2), pp. 121-134.
Hannane, A., Fizazi, H., Metaheuristics and Neural Network for Satellite Images Classification, (2016) International Review of Aerospace Engineering (IREASE), 9 (4), pp. 107-113.
Saraereh, O., Al Saraira, A., Alsafasfeh, Q., Arfoa, A., Bio-Inspired Algorithms Applied on Microstrip Patch Antennas: a Review, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (6), pp. 336-347.
Jhajj, H., Garg, R., Saluja, N., Efficient Spectrum Sensing in Cognitive Radio Networks Using Hybridized Particle Swarm Intelligence and Ant Colony Algorithm, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (7), pp. 586-593.
Mandave, D., Pole, G., SyntcRec: a Syntactic Recommender System Based on Improved Feature Selection Technique in Large Scholarly Data, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (6), pp. 537-544.
Aabid, M., Elakkary, A., Sefiani, N., PID Parameters Optimization Using Ant-Colony Algorithm for Human Heart Control, (2017) International Review on Modelling and Simulations (IREMOS), 10 (2), pp. 94-102.
Chebli, S., Elakkary, A., Sefiani, N., Multi-Objective Genetic Algorithm Optimization Using PID Controller for AQM/TCP Networks, (2017) International Review of Automatic Control (IREACO), 10 (1), pp. 33-39.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2021 Praise Worthy Prize