Artificial Neural Network Based Control Strategies for Paddy Drying Process
Author(s) -
Shekhar F. Lilhare,
N. G. Bawane
Publication year - 2014
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2014.11.04
Subject(s) - controller (irrigation) , computer science , artificial neural network , process (computing) , humidity , process engineering , nonlinear system , process control , agricultural engineering , environmental science , control theory (sociology) , control (management) , artificial intelligence , agronomy , meteorology , engineering , physics , quantum mechanics , biology , operating system
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
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