Mechanized irrigation center pivots

Center pivot irrigation systems are widely used for large-scale agricultural irrigation, providing uniform water distribution. However, their circular coverage leaves field corners unwatered, reducing efficiency and requiring additional irrigation infrastructure. To address this, swing arm extensions are attached to the last tower of the center pivot, improving coverage. Despite their benefits, current swing arm systems require further optimization in control mechanisms to enhance accuracy, automation, and maneuverability while reducing operational costs. Existing swing arm control solutions primarily rely on buried cables, hydraulic actuators, or electromechanical systems. These approaches, while functional, present significant drawbacks, including high installation and maintenance costs, susceptibility to wear, and limited adaptability to real-time field conditions. This study proposes an advanced swing arm control system integrating Real-Time Kinematic (GPS-RTK) guidance and inverse kinematics (IK) for a 2-degree-of-freedom (2-DOF) swing arm. The IK model dynamically adjusts the arm’s position based on real-time GPS-RTK data, improving boundary tracking and maximizing irrigation efficiency. Additionally, a U-channel mechanism is introduced to passively regulate the swing arm’s motion, reducing reliance on real-time speed calculations while ensuring smoother operation. To evaluate system performance, a systematic analysis was conducted, assessing irrigation coverage, synchronization accuracy, and overall efficiency. A case study examined the role of the U-channel in stabilizing swing arm movement, minimizing fluctuations without requiring active intervention. MATLAB simulations were performed to visualize the swing arm’s trajectory and behavior in square, rectangular, and trapezoidal fields. These simulations analyzed the synchronization between the swing arm and the last tower of the center pivot, demonstrating the effectiveness of the proposed control approach. The results indicate that integrating GPS-RTK and IK significantly enhances precision, automation, and synchronization with the center pivot’s motion. The optimized system expands irrigation coverage to previously unwatered field corners, improving water distribution while reducing infrastructure needs. Furthermore, the U-channel mechanism effectively stabilizes motion, mitigating synchronization errors and ensuring smoother transitions. These improvements contribute to more sustainable, cost-effective irrigation practices, reducing operational costs while enhancing field coverage. This study highlights the potential of integrating real-time positioning and kinematic modeling into agricultural irrigation systems for improved adaptability, efficiency, and resource optimization. Future research could explore machine learning-based optimization, real-time soil moisture sensing, and adaptive control mechanisms to further enhance precision irrigation and sustainable farming.