UAV Control Mapping Based on Fuzzy Logic-automatic Control Theory Algo-rithm
In order to improve the control accuracy of drone surveying,a fuzzy PID controller has been studied and designed,utilizing fuzzy logic and automatic control theory algorithms to improve the control accuracy of drones in surveying tasks.The research adjusted the parameters and fuzzy rules of the control algorithm,and added a threshold as a new control variable to reduce control errors.The experimental results show that the error fluctuation range of the controller is smaller,stable within the range of-0.05～0.05 m/s,and its adjustment time for a single action is only 0.58 s.The steady-state error is 0.05 m,and the maximum overshoot is 0.4%.The improved fuzzy PID has higher regulation efficiency,higher control accuracy,and stronger stability.Research is of great significance in promoting the development of unmanned aerial vehicle applications and improving the efficiency and accuracy of tasks such as geo-graphic surveying and environmental monitoring.
fuzzy logicautomatic control theorycontrollerUAV surveying and mapping
万方数据
维普
