TY - JFULL AU - Doaa M. Atia and Faten H. Fahmy and Ninet M. Ahmed and Hassen T. Dorrah PY - 2011/10/ TI - Design and Control of PEM Fuel Cell Diffused Aeration System using Artificial Intelligence Techniques T2 - International Journal of Electrical and Computer Engineering SP - 1190 EP - 1198 VL - 5 SN - 1307-6892 UR - https://publications.waset.org/pdf/10945 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 57, 2011 N2 - Fuel cells have become one of the major areas of research in the academia and the industry. The goal of most fish farmers is to maximize production and profits while holding labor and management efforts to the minimum. Risk of fish kills, disease outbreaks, poor water quality in most pond culture operations, aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) techniques control is used to control the fuel cell output power by control input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparison study is applied between the performance of fuzzy logic control (FLC) and neural network control (NNC). The results show the effectiveness of NNC over FLC. ER -