Study On Control Algorithm Of Agricultural UAV Stabilized Platform Based On Fuzzy PID Control Technology

Precision agriculture significantly oriented the development of future agriculture. As a high-efficiency solution of field data acquisition, unmanned aerial vehicle (UAV) remote sensing is one of the most important research area. With the help of airborne stabilized platform, the efficiency of field data acquisition could be improved remarkably, and the images obtained could be of higher quality, thus preparing for the following work such as design of prescription map. In this paper, a 3D model was established based on a self-designed airborne stabilized platform. Based on the parameters of the 3D model, three sets of kinematics equation and dynamics equation were established. Each set corresponded to one of the most commonly used agricultural cameras. According to the principle of concision, high real-time performance and strong robustness, PID controller, fuzzy PID control and fuzzy PID controller based on strong tracking adaptive Kalman filter were designed to control the models mentioned above. The simulation results were as follows:1. Without the disturbance of noise, classical PID algorithm was qualified to control the stabilized platform. Under disturbance of noise or change of model, the performance of classical PID algorithm was not sufficient for stabilized platform controlling.2. Contrast to classical PID controller, fuzzy PID controller possessed virtues of smaller overshoot, stronger robustness, higher adaptability and shorter adjusting time. Even if the model changed, fuzzy PID controller still showed satisfactory performance.3. Fuzzy PID controller based on strong tracking adaptive Kalman filter showed great noise suppression capability as well as maintaining the advantage of fuzzy PID controller.