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基于避障路径规划的无人直升机空地跟踪控制
辽宁石油化工大学学报
2024年 44卷 第No.1期
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Title
Collaborative Air⁃Ground Tracking Control of Unmanned Helicopter Based on Obstacle Avoidance Path Planning
Authors
Jingwen YANG
Tao LI
Xin YANG
Mingfei JI
单位
南京航空航天大学 自动化学院,江苏 南京 211106
Organization
College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 211106,China
摘要
针对无人直升机(Unmanned Aerial Helicopter,UAH)在空地协同跟踪过程中的避障和控制问题,提出了新型路径避障规划和跟踪控制设计方法。针对不确定性的线性UAH模型,通过对UAH警示范围内二维环境信息进行处理判断,借助摸墙算法(Wall?Following Algorithm) 提出合适的避障策略,计算避障路径的行进角度以及能够弥补绕行距离的跟踪速度;将所得避障方法拓展至三维环境中,根据水平和垂直方向上的障碍物信息确定UAH飞行角度,从而减小由避障环节所带来的绕行距离;在上述避障算法的基础上,引入人工神经网络(Approximate Nearest Neighbor,ANN)估计模型不确定项,进而结合前馈补偿与最优控制等技术建立了跟踪控制设计方案。仿真结果表明,所提避障策略和控制算法有效。
Abstract
The paper aims to study the problem of obstacle avoidance in air?ground cooperative tracking control for the unmanned aerial helicopter (UAH),in which a new approach of designing the path obstacle avoidance plan and controller design is proposed.Initially, as for the uncertain linear UAH,by processing and judging two?dimensional environmental information within the warning range for the UAH,an obstacle avoidance strategy is proposed with the help of wall?following algorithm,and the flight angle of obstacle avoidance path and the tracking speed that can make up for bypass distance are calculated.Secondly,the proposed obstacle avoidance method is extended to the three?dimensional case,and the flight angle of the UAH is determined based on the obstacle information in the horizontal and vertical directions,which can reduce the bypass distance caused by the obstacle avoidance link as possible.Thirdly,based on two derived obstacle avoidance algorithms above,the artificial neural network (ANN) is introduced to estimate model uncertainty,and then the tracking control design schemes are established by using feedforward compensation and optimal control technologies.some simulations demonstrate the effectiveness of the proposed obstacle avoidance strategy and control algorithm.
关键词:
无人直升机;
空地跟踪;
避障路径规划;
人工神经网络;
Keywords:
Unmanned aerial helicopter;
Clearing tracking;
Obstacle avoidance path planning;
Artificial neural networ;
基金项目
国家自然科学基金资助项目(62073164);国防科技重点实验室基金项目(61422200306)
DOI
10.12422/j.issn.1672-6952.2024.01.011