Optimization of PID control strategy for UAV gimbal stability based on improved whale optimization algorithm (WOA)

This paper aims to boost the performance of a self-stabilizing three-axis gimbal system, emphasizing environmental adaptability and rapid response. It innovatively adapts and enhances the Whale Optimization Algorithm (WOA) to optimize Proportional-Integral-Derivative (PID) controller parameters. This tailored strategy leverages WOA's improved global search and local tuning abilities for precise PID parameter adjustment. Comparative tests with traditional PID and Genetic Algorithm (GA)-optimized PID reveal that the WOA-optimized PID significantly enhances adaptability and response speed. The strategy dynamically tunes parameters based on system states, ensuring gimbal stability and efficiency across conditions. The findings confirm WOA's effectiveness in PID optimization and its potential to upgrade UAV mounted gimbal performance. This work paves a new way for gimbal control system design and optimization, strengthening UAV technology development.