Automated pH Control of Nutrient Solution in Hydroponic System using Modified Fuzzy Logic Control

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Thanavin Mansakul
Kanticha Kittipeerachon


A hydroponic system can control many factors significantly, such as the amount of water and fertilizer. However, the system is a high investment and requires some skills to operate. The unsuitable quantity of pH can cause root damage from acidity and inadequate nutrient uptake. This paper presents the pH control in a nutrient solution using modified fuzzy logic control. The fuzzy logic control is a design based on experienced personal adjustment data. However, the defuzzification technique is modified to suit the controlled system using the area under an appropriately designed graph. From the results obtained from the prototype systems, it was found that the proposed system can control pH value in nutrient solution and reject disturbance better than the conventional P control system. Since the system can decide the proper quantity of acid and base automatically, the system can reduce human workload and reduce complicated procedures for the farmer.


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T. Wada, “Theory and technology to control the nutrient solution of hydroponics,” in Plant Factory using Artificial Light, Japan: Elsevier, 2019, ch.1, sec.1.1, pp. 5-13.

T. Kaewwiset and T. Yooyativong, “Electrical conductivity and pH adjusting system for hydroponics by using linear regression,” in 14th ECTI-CON, Phuket, Thailand, Jun. 2017, pp. 761-764.

M. Fuangthong and P. Pramokchon, “Automatic control of electrical conductivity and pH using fuzzy logic for hydroponics system,” in 3rd ICDAMT, Chiangrai, Thailand, Feb. 2018, pp. 65-70.

R. C. Dorf and R. H. Bishop, “PID controllers,” in Modern Control System, 13th ed. Malaysia: Pearson Education, 2017, ch.7, sec.7.6, p. 479.

K. Ogata, “Tuning rules for PID controller,” in System Dynamic, 4th ed. Upper Saddle River, NJ, USA: Pearson Education, 2004, ch.10, sec.10, p. 566.

K. M. Passino and S. Yurkovich, “Fuzzy control: The basics,” in Fuzzy Control. Menlo Park, CA, USA: Addison Wesley Longman, 1998, ch.1, sec.1.3, p. 23.