摘要
针对无人机在复杂环境下,利用传统的单环控制与卡尔曼滤波进行目标跟踪与降落任务时,出现跟踪目标丢失、降落精确性不足的问题,提出一种基于混合滤波和多环控制的状态估计与控制算法。利用卡尔曼滤波和扩展卡尔曼滤波的混合滤波方法对移动降落平台进行状态估计,同时通过速度PI控制环、姿态PID控制环、位置PID控制环及加速度PID控制环来完成无人机的跟踪与降落任务。仿真试验结果表明,在面对简易或复杂的环境时,该方法都具有较好的跟踪性能和更高的降落精度,并能够应用在多种环境下的无人机自主追踪和降落作业中。
A state estimation and control algorithm based on hybrid filtering and multi loop control is proposed to address the problems of target loss and insufficient landing accuracy when unmanned aerial vehicles uses traditional single loop control and Kalman filtering for target tracking and landing tasks in complex environments.The hybrid filtering method of Kalman filter and extended Kalman filter is used to estimate the state of the mobile landing platform,and the tracking and landing tasks of the unmanned aerial vehicles are completed by means of the speed PI control loop,attitude PID control loop,position PID control loop,and acceleration PID control loop.The simulation experimental results show that when facing both simple and complex environments,this method has good tracking performance and higher landing accuracy,and can be applied to autonomous tracking and landing operations of unmanned aerial vehicles in various environments.
作者
任倩倩
王晓松
郑恩辉
REN Qianqian;WANG Xiaosong;ZHENG Enhui(School of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou 310018,China)
出处
《现代电子技术》
北大核心
2024年第14期108-114,共7页
Modern Electronics Technique
关键词
混合滤波
多环控制
无人机
扩展卡尔曼滤波
PID控制
位姿估计
移动目标跟踪
hybrid filtering
multi-loop control
unmanned aerial vehicle
extended Kalman filtering
PID control
pose estimation
moving target tracking
