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Research Paper | Mechatronic Engineering | India | Volume 13 Issue 6, June 2024 | Rating: 5.9 / 10
Fuzzy Logic and ANFIS Model Based Fresh Water Control System and Fish Health Detection in Aquaculture
Abstract: Fuzzy logic is an innovative technology to design solutions for multi parameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC) for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming. The fish?s diseases occurred due to change in parameters i.e. dissolved oxygen, ammonia, nitrogen, carbon dioxide, calcium, ozone, hydrogen sulphide, pH present into the water. If these parameters vary abruptly changes, the fishes get affected by the several diseases. It is well known that fish have a low food conversion rate and feeding represents the most important expenditure, approximately 40% of total production cost.
Keywords: Fuzzy Logic Controller, Stress Parameter, Dissolved Oxygen, MATLAB Simulink
Edition: Volume 13 Issue 6, June 2024,
Pages: 1852 - 1858