Fuzzy Optimization Control of Airborne Photoelectric Pod Based on Genetic Algorithm.

According to the stability of airborne photoelectric pod, a fuzzy PID controller based on genetic algorithm is designed. The photoelectric pod is easily interfered by the external environment during the working process, which causes the camera's visual axis to shake and affect the shooting quality. However, the traditional PID control has a poor control effect on the nonlinear system with time delay and time variation. The genetic algorithm is used to optimize the fuzzy PID controller parameters, and the optimal parameter values are continuously obtained to improve the stability and adaptability of the system. The simulation using Matlab software shows that compared with the conventional PID controller, the controller based on genetic algorithm optimization fuzzy PID control parameter tuning has better control effect and stronger adaptability.