Enhancement of Photovoltaic Pressurized Irrigation System Based on Hybrid Kalman Fuzzy

Suwito Suwito; Mochamad Ashari; Muhammad Rivai; M. Anis Mustaghfirin

doi:10.22266/ijies2022.0430.39

Enhancement of Photovoltaic Pressurized Irrigation System Based on Hybrid Kalman Fuzzy

Suwito Suwito, Mochamad Ashari^*, Muhammad Rivai, M. Anis Mustaghfirin

^*Corresponding author for this work

Shipbuilding Institute of Polytechnic Surabaya

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This paper presents an enhancement of a pressurized irrigation system without battery and water tank storage. The system is powered by a photovoltaic (PV) system with a hybrid Kalman filter and fuzzy logic (HKF)-based control system. The Kalman filter estimates the maximum power point, whereas fuzzy logic controls the boost converter to optimize the PV output. The system manages the water pressure by matching the power of the brushless DC (BLDC) motor and the number of valves to be operated. A prototype of the system was built on a laboratory scale using a 32-bit ARM microcontroller and pressurized irrigation networks. Results from the simulation and prototype tests were very similar in terms of tracking the optimum power. The average steady-state oscillation amplitude is 0.65 watts, while the average rise time is 1.02 seconds.

Original language	English
Pages (from-to)	426-440
Number of pages	15
Journal	International Journal of Intelligent Engineering and Systems
Volume	15
Issue number	2
DOIs	https://doi.org/10.22266/ijies2022.0430.39
Publication status	Published - Apr 2022

Keywords

Fuzzy logic
Kalman filter
Maximum power point tracking
Microcontroller
Photovoltaic
Pressurized irrigation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.22266/ijies2022.0430.39

Cite this

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title = "Enhancement of Photovoltaic Pressurized Irrigation System Based on Hybrid Kalman Fuzzy",

abstract = "This paper presents an enhancement of a pressurized irrigation system without battery and water tank storage. The system is powered by a photovoltaic (PV) system with a hybrid Kalman filter and fuzzy logic (HKF)-based control system. The Kalman filter estimates the maximum power point, whereas fuzzy logic controls the boost converter to optimize the PV output. The system manages the water pressure by matching the power of the brushless DC (BLDC) motor and the number of valves to be operated. A prototype of the system was built on a laboratory scale using a 32-bit ARM microcontroller and pressurized irrigation networks. Results from the simulation and prototype tests were very similar in terms of tracking the optimum power. The average steady-state oscillation amplitude is 0.65 watts, while the average rise time is 1.02 seconds.",

keywords = "Fuzzy logic, Kalman filter, Maximum power point tracking, Microcontroller, Photovoltaic, Pressurized irrigation",

author = "Suwito Suwito and Mochamad Ashari and Muhammad Rivai and Mustaghfirin, {M. Anis}",

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N2 - This paper presents an enhancement of a pressurized irrigation system without battery and water tank storage. The system is powered by a photovoltaic (PV) system with a hybrid Kalman filter and fuzzy logic (HKF)-based control system. The Kalman filter estimates the maximum power point, whereas fuzzy logic controls the boost converter to optimize the PV output. The system manages the water pressure by matching the power of the brushless DC (BLDC) motor and the number of valves to be operated. A prototype of the system was built on a laboratory scale using a 32-bit ARM microcontroller and pressurized irrigation networks. Results from the simulation and prototype tests were very similar in terms of tracking the optimum power. The average steady-state oscillation amplitude is 0.65 watts, while the average rise time is 1.02 seconds.

AB - This paper presents an enhancement of a pressurized irrigation system without battery and water tank storage. The system is powered by a photovoltaic (PV) system with a hybrid Kalman filter and fuzzy logic (HKF)-based control system. The Kalman filter estimates the maximum power point, whereas fuzzy logic controls the boost converter to optimize the PV output. The system manages the water pressure by matching the power of the brushless DC (BLDC) motor and the number of valves to be operated. A prototype of the system was built on a laboratory scale using a 32-bit ARM microcontroller and pressurized irrigation networks. Results from the simulation and prototype tests were very similar in terms of tracking the optimum power. The average steady-state oscillation amplitude is 0.65 watts, while the average rise time is 1.02 seconds.

KW - Fuzzy logic

KW - Kalman filter

KW - Maximum power point tracking

KW - Microcontroller

KW - Photovoltaic

KW - Pressurized irrigation

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Enhancement of Photovoltaic Pressurized Irrigation System Based on Hybrid Kalman Fuzzy

Abstract

Keywords

UN SDGs

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