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. The performance of the HKF is much better than perturb and observe (P&O) method