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Comparative Performance Analysis of Nutrient and pH Control in Hydroponic Systems Using Coupled and Decoupled Methods
Corresponding Author(s) : Ina Rahmawati Putri
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control,
Vol. 11, No. 2, May 2026
Abstract
pH and TDS are critical parameters in hydroponic systems that directly influence plant growth. This research develops an automatic control system for nutrient solution and pH regulation in hydroponic cultivation using a PID controller implemented with both coupled and decoupled methods. The aim of the research is to evaluate the performance differences between these two control approaches and to contribute to the development of more accurate and adaptive strategies for maintaining nutrient solution quality. Lettuce plants were used as test subjects with target conditions of 550 ppm TDS and pH 6.5. The research was conducted through MATLAB simulations and hardware implementation to assess system performance. The simulation results indicated that the decoupled method provides superior performance, achieving a pH rise time of 6.04 s, a settling time of 31.24 s, an overshoot of 9.5%, and zero steady-state error. The TDS response exhibits a rise time of 84.97 s, a settling time of 161.67 s, zero overshoot, and zero steady-state error. Hardware implementation demonstrates similar trends, with a pH rise time of 8.34 s, a settling time of 11 s, zero overshoot, and a steady-state error of 0.90%. The TDS response shows a rise time of 30.7 s, a settling time of 36 s, an overshoot of 4.36%, and a steady-state error of 0.60%. In contrast, the coupled method produces slower responses, longer settling times, and higher steady-state errors. Overall, the decoupled method proves to be more effective and responsive in maintaining pH and nutrient stability, demonstrating strong potential for application in smart agriculture systems.
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H. Sirhan, M. Al-ajouz, and R. Al-sa, “Hydroponics as a Sustainable Water-Efficient Agricultural Strategy for Enhancing Resilience and Food Security in the Gaza Strip,” vol. 1, no. 3, pp. 6–20, 2025. https://doi.org/10.63095/NBSEH.25.774983
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H. Sulaiman, A. A. Yusof, and M. K. Mohamed Nor, “Automated Hydroponic Nutrient Dosing System: A Scoping Review of pH and Electrical Conductivity Dosing Frameworks,” AgriEngineering, vol. 7, no. 2, pp. 1–23, 2025. https://doi.org/10.3390/agriengineering7020043
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J. E. Elektro, D. Yulianto, A. F. Nugraha, F. F. Rahami, and U. A. Dahlan, “Automated Hydroponics System using the Internet of Things,” vol. 8, no. 2, pp. 149–160, 2024. https://doi.org/10.21831/jee.v8i2.76816
N. Surantha and V. Vincentdo, “NFT-Based Hydroponic Automated Control Using Adaptive Network-Based Fuzzy Inference System,” 2022 2nd Int. Conf. Robot. Autom. Artif. Intell. RAAI 2022, pp. 118–123, 2022. https://doi.org/10.1109/RAAI56146.2022.10092958
Fitriani, Z. Zainuddin, and Syafaruddin, “Nutrition Control System In Nutrient Film Technique (NFT) Hydroponics With Convolutional Neural Network (CNN) Method,” Proc. - ISMODE 2022 2nd Int. Semin. Mach. Learn. Optim. Data Sci., pp. 41–46, 2022. https://doi.org/10.1109/ISMODE56940.2022.10180412
D. L. Methods, “JOURNAL OF ENGINEERING SCIENCES Hydroponic Agriculture with Machine Learning and,” vol. 9, no. 3, pp. 508–519, 2023. https://doi.org/10.30855/gmbd.0705083
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K. Liu, Y. Liu, F. Song, C. Zhang, W. Li, and Z. Wang, “Data Driven Dynamic Decoupling Control for MIMO Precision Mechatronic Systems,” Proc. 2024 IEEE 13th Data Driven Control Learn. Syst. Conf. DDCLS 2024, pp. 1305–1310, 2024. https://doi.org/10.1109/DDCLS61622.2024.10606678
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D. S. Bhandare, N. R. Kulkarni, and M. V. Bakshi, “Linearization of a Coupled tank MIMO system and its validation using MATLAB,” 2021 6th Int. Conf. Converg. Technol. I2CT 2021, pp. 1–5, 2021. https://doi.org/10.1109/I2CT51068.2021.9417875
J. M. Daif-Alkhasraji, S. W. Shneen, and M. Q. Sulttan, “Reduction of Large Scale Linear Dynamic MIMO Systems Using ACO-PID Controller,” Ing. e Investig., vol. 44, no. 1, pp. 1–7, 2024. https://doi.org/10.15446/ing.investig.106657
P. Kumar, V. Kumar, and B. Tyagi, “Experimental Validation of PI Controllers and Modelling of DC Servo Motor by FOPDT Model,” PESGRE 2022 - IEEE Int. Conf. “Power Electron. Smart Grid, Renew. Energy,” pp. 1–5, 2022. https://doi.org/10.1109/PESGRE52268.2022.9715815
M. Science, “Cross-Coupled Dynamics and MPA-Optimized Robust MIMO Control for a Compact Unmanned Underwater Vehicle,” 2023. https://doi.org/10.3390/jmse11071411
S. R. Mahapatro and B. Subudhi, “A New H∞Weighted Sensitive Function-Based Robust Multi-Loop PID Controller for a Multi-Variable System,” IEEE Trans. Circuits Syst. II Express Briefs, vol. 71, no. 3, pp. 1256–1260, 2024. https://doi.org/10.1109/TCSII.2023.3319388