Artificial Neural Network Based Control Strategies for Paddy Drying Process

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Shekhar F. Lilhare 1,* N. G. Bawane 2

1. GHRCE, Nagpur, 440016, India

2. S. B. Jain Institute of Technology, Management & Research, Nagpur, 441501, India

* Corresponding author.


Received: 2 Jan. 2014 / Revised: 15 Apr. 2014 / Accepted: 7 Jun. 2014 / Published: 8 Oct. 2014

Index Terms

Paddy, Drying Time, Neural Controller, Simulation, Control Strategies


Paddy drying process depends upon ambient conditions, paddy quality, temperature and mass of hot drying air. Existing techniques of paddy drying process are highly nonlinear. In this paper, a neural network based automated controller for paddy drying is designed. The designed controller manages the steam temperature and blower motor speed to achieve constant paddy drying time. A Layer recurrent neural network is adopted for the controller. Atmospheric conditions such as temperature and humidity along with the size of the paddy are used as input to the network. Experimental results show that the developed controller can be used to control the paddy drying process. Implementation of developed controller will help in controlling the drying time at almost constant value which will definitely improve the quality of rice.

Cite This Paper

Shekhar F. Lilhare, N. G. Bawane, "Artificial Neural Network Based Control Strategies for Paddy Drying Process", International Journal of Information Technology and Computer Science(IJITCS), vol.6, no.11, pp.28-35, 2014. DOI:10.5815/ijitcs.2014.11.04


[1]M.H. Saifullah Saif, A. Dwayne, and Yubin Lan, "Effects of Processing Conditions and Environmental Exposure on the Tensile Properties of Parboiled Rice," Journal of Bio Systems Engineering, Vol. 89 (3), pp. 321–330, 2004.

[2]H. N. Larsen, "Glycaemic index of parboiled rice depends on the severity of processing," European Journal of Clinical Nutrition, Vol. 54(5), pp. 380 -385, 2000.

[3]A. Chakraborty and D. S. Dey, "Post Harvest Technology," Oxford and IBH Publishing Co. Pvt. Ltd, New Delhi, pp. 72, 94, 125, 2008.

[4]G. N. Tiwari, A. K. Singh, and P. S. Bhatia, "Experimental simulation of a grain drying system," Elsevier's, Energy conversion management, Vol. 35, No. 5, pp. 453-458, 1994.

[5]S. Somchart, "Fluidised Bed Grain Drying," School of Energy and Materials, King Mongkut’s University of Technology, Thonburi Suksawat, 48 , Bangkok , Thailand, pp. 54-71, 2010.

[6]J. Wang, "Researches on variable temperature drying technology and on-line control for high moisture content," New Technology of Agricultural Engineering (ICAE), International Conference, Zibo, pp. 27-29, 2011.

[7]N.B. Camila, N. S. J. Fernando, and A. F. Ferreira, "High performance controllers for drying processes, "Acta Scientiarum, Technology, Maringá," Vol. 35, No. 2, pp. 279-289, 2013.

[8]N.B. Camila, N.S. J. Fernando, A. F. Ferreirac, and M. P. S. Santosd, "Experimental Comparison Between Control Schemes for a Drying Process Dynamics," Advances in Mathematical and Computational Methods, ISSN 2160-0635, Vol. 2, No.1, 2012.

[9]Samsul, Bahari Mohd. Noor, Hasmah Mansor, Raja Kamil Raja Ahmad, and Farah Saleena Taip, "Online quantitative feedback theory (QFT) - based self-tuning controller for grain drying process," Scientific Research and Essays, Vol. 6(31), pp. 6520-6534, 2011.

[10]D. Wang, C. Li, J. Xu, and B. Zhang, "A control-parameter data collecting and processing system of grain drying in a deep fixed-bed," World Automation Congress (WAC), pp. 325-330, 2010.

[11]S. Atthajariyakul and T. Leephakpreeda, "Fluidized bed paddy drying in optimal conditions via adaptive fuzzy logic control," Journal of Food Engineering, Vol. 75, pp. 104–114, 2006.

[12]K. H. Lee and O. J. Kim, "Investigation on drying performance and energy saving of the batch –type heat pump dryer," Drying Technology, Vol. 27, pp. 565-573, 2009.

[13]W. C. Wang, R. K. Calay, and Y. K. Chan, "Experimental study on an energy efficient hybrid system for surface drying," Applied Thermal Engineering Vol. 31, pp. 425-431, 2011.

[14]S. S. Mohapatra and P. Mahanta, "Thermodynamic evaluation of natural convection paddy dryer," Developments in Renewable Energy Technology (ICDRET), 2nd International IEEE Conference , Dhaka , pp. 1- 4, 2012.

[15]S. Hung –Jung and Yi-Iuenchen, "Thin layer model for Intermittent Drying of Rough Rice," American Association of Cereal Chemists, Inc. Cereal chemistry Vol. 76, No. 4, pp. 577-581, 1999.

[16]J. F. Steffe and R. P. Singh, "Theoretical and practical aspects of rough rice tempering," American Society of Agriculture Engineering, Vol.23, pp. 775-782,1980.

[17]J. L. Parry, "Mathematical modelling and computer simulation of heat and mass transfer in agricultural grain drying," Journal Agriculture Engineering Research, Vol. 32, pp.1-29, 1985.

[18]A. Iguaz, M. B. San Martin, J. I. Mate, T. Fernandez, and P. Virseda, "Modelling Effective Moisture diffusivity of rough rice at low drying temperatures," Journal of food engineering, Vol. 59, pp. 253-258, 1994.

[19]X. Zheng and Y. Lan, "Effects of Drying Temperature and Moisture Content on Rice Taste Quality," Agricultural Engineering International: The CIGR E Journal Manuscript FP 07 023, Vol. 9, 2007.

[20]S. F. Lilhare and N. G. Bawane, "Simulation of Paddy Drying Characteristics Under Different Ambient Conditions," International Journal of Engineering Systems Modeling and Simulation, Vol. 1, Issue 7, pp. 1-4, 2012.

[21]N. S. Visen, J. Paliwal, D. S. Jayas, and N. D. G. White, "Specialist neural Networks for cereal Grain Classification," Elsevier Science, Bio systems Engineering, Vol. 82(2), pp. 151-159, 2002.

[22]S. F. Lilhare and N. G. Bawane, "Classification of paddy Varieties using Image processing," National Conference on Innovative Paradigms in Engineering and Technology, NCPIET-12, pp. 33-35, 2012.

[23]Y. Liu, F. Cheng, Y. b. Ying and X. Q. Rao, "Identification of rice seed varieties using neural network," Journal of Zhejiang university Science, Vol. 6b (11), pp. 1095-1100, 2005.

[24]B. T. Mazhar and B. Mohamed E.El, "ECG images classification using artificial neural network based on several feature extraction methods," IEEExplore International Conference on Computer Engineering & Systems (ICCES), pp.113-115, 2008.

[25]D. Malathi and N. Gunasekaran, "A Novel Neural Learning Algorithm for Separation of Blind Signals," Medwell Publishing, International journal of Soft Computing Vol. 4(1), pp. 1624, 2009.

[26]A. Goshvarpour, H. Ebrahimnezhad and A. Goshvarpour, "Shape classification based on normalized distance and angle histograms using PNN," Journal of Information Technology and Computer Science (IJITCS), Vol. 5, No. 9, 2013.

[27]F.F.G. Areed, M.S. El kasassy, and M. S. Mahmood, "Design of Neuro Fuzzy Controller for a Rotary Dryer," International Journal of Computer Application, Vol. 37, No. 5, pp. 34- 41, 2012.

[28]S. F. Lilhare and N. G. Bawane, "Modelling and simulation of control strategies for paddy dryer system," National Conference on Innovative Paradigms in Engineering and Technology, NCPIET-13, pp. 23-28, 2013.

[29]Koushal Kumar and Abhishek, "Artificial Neural Networks for Diagnosis of Kidney Stones Disease," International Journal of Information Technology and Computer Science (IJITCS), Vol. 4, No. 7, pp. 20-25, 2012. 

[30]Koushal Kumar, Gour Sunder, and Mitra Thakur, "Advance Application of Neural Network and Artificial Intelligence: A Review," International Journal of Information Technology and Computer Science (IJITCS), 6, pp. 57-68, 2012.

[31]P. Somkiat, S. Somchart, Y. Mustafa, and W. Montri, "Prototype and commercialization of fluidized Bed Paddy Dryer," Research and Development, Journal of the Engineering Institute of Thailand, Vol. 6, No. 2, pp. 2, 1995.