Improving Aquaculture Water Quality Using Dual-Input Fuzzy Logic Control for Ammonia Nitrogen Management

Abstract

In this paper, a closed-loop control system using dual-input fuzzy logic theory is proposed to improve the water quality of aquaculture. The new closed-loop control system is implemented on a Raspberry-Pi-embedded platform using Python programming. The proposed closed-loop control system integrates an RS485 function, a database transfer module, a simulating variable group function, and a trigger function import to achieve savings in human resources, power, and water consumption. The proposed closed-loop control system is equipped with an ammonia nitrogen sensor and solenoid valves for the water exchange. The experimental results demonstrate that the intelligent controller can rapidly eliminate ammonia nitrogen within the range of 2.0 ppm and maintain robust control in response to changes in ammonia nitrogen excretion from a school of fish. The experimental results provide insights into the relationship between tank capacity, water exchange solenoid valves, and ammonia nitrogen degradation time, which can be used to optimize aquaculture density and improve industrialization. The experimental results demonstrate that the savings for power and water can be achieved above 95%.