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Solar Thermal Aquaculture System Controller Based on Artificial Neural Network

Author(s): Doaa M Atia | Faten H Fahmy | Ninet M Ahmed | Hassen T Dorrah

Journal: Engineering
ISSN 1947-3931

Volume: 03;
Issue: 08;
Start page: 815;
Date: 2011;
Original page

Keywords: Aquaculture | Forced Circulation Hot Water System | Artificial Neural Networks

Temperature is one of the most principle factors affects aquaculture system. The water temperature is very important parameter for shrimp growth. It can cause stress and mortality or superior environment for growth and reproduction. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it causes death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt as presented in this paper. This paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the solar thermal aquaculture system. Moreover the paper presents the control of pond water temperature using artificial intelligence technique. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. They have been used to solve complicated practical problems. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.
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