Neuro-fuzzy control techniques for optimal water quality index in a small scale tiger prawn aquaculture setup

• Main Authors: Gustilo, Reggie C., Dadios, Elmer P., Calilung, Edwin, Gan Lim, Laurence A.
• Format: text
• Published: Animo Repository 2014
• Subjects: Shrimp culture; Water quality—Measurement; Intelligent sensors; Electrical and Electronics; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1830; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2829/type/native/viewcontent
• Institution: De La Salle University

A small scale real time tiger prawn aquaculture setup was built and tested in the laboratory using ordinary aquariums to test the controllability and control of the four most important parameters in culturing tiger prawns, the temperature, salinity, pH and dissolved oxygen. These parameters were monitored using Vernier sensors via Labview program. The water quality index of the artificial habitat was monitored and computed using fuzzy logic. New values for the safe parameter conditions of the tiger prawns were observed and used in the computation of the water quality index. Lastly, electronic valves and actuators are used to automatically control the four said water parameters and set them to their optimal values. The control needed by each parameter to force them to stay within their optimal values was done using neural network. This control system is used to activate the electronic valves that will dispense correction fluids for each of the four monitored water parameter. © 2014, Fuji Technology Press. All rights reserved.