基于模糊逻辑-自动控制理论算法的无人机控制测绘研究  

UAV Control Mapping Based on Fuzzy Logic-automatic Control Theory Algorithm

作　　者：张伟佳[1,2] 纪海源 ZHANG Weijia;JI Haiyuan(School of Civil Engineering,Shaanxi Polytechnic Institute,Xianyang 712000,China;Key Laboratory of Digital City and Geospatial Big Data Technology,Xianyang 712000,China)

机构地区：[1]陕西工业职业技术学院土木工程学院,咸阳712000 [2]咸阳市数字城市与地理空间大数据技术重点实验室,咸阳712000

出　　处：《自动化与仪表》2024年第9期158-161,164,共5页Automation & Instrumentation

基　　金：陕西工业职业技术学院青年科技创新团队基金(KCTD2022-01)。

摘　　要：为提高无人机测绘的控制精度,研究设计了模糊PID控制器,利用模糊逻辑和自动控制理论算法,来改进无人机在测绘任务中的控制精度。研究调整了控制算法的参数和模糊规则,增加了一个阈值作为新的控制量以减少控制误差。实验结果显示,该控制器的误差波动范围更小,稳定在-0.05~0.05 m/s范围之内,其对单个动作的调节时间也仅为0.58 s,稳态误差为0.05 m,最大超调量为0.4%。改进模糊PID的调节效率高、控制精度高、稳定性强,对推动无人机应用领域的发展,提升地理测绘和环境监测等任务的效率和精确性具有重要意义。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 geographic surveying and environmental monitoring.

关 键 词：模糊逻辑 自动控制理论 控制器 无人机测绘 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]