ESO-Based Robust and High-Precision Tracking Control for Aerial Manipulation

四轴飞行器 控制理论(社会学) 控制器(灌溉) 弹道 控制工程 计算机科学 水准点(测量) 人工智能 鲁棒控制 国家(计算机科学) 规划师 控制系统 工程类 控制(管理) 算法 电气工程 农学 物理 大地测量学 天文 地理 生物 航空航天工程
作者
Huazi Cao,Yongqi Li,Cunjia Liu,Shiyu Zhao
出处
期刊:IEEE Transactions on Automation Science and Engineering [Institute of Electrical and Electronics Engineers]
卷期号:: 1-17 被引量:7
标识
DOI:10.1109/tase.2023.3260874
摘要

This paper studies the tracking control problem of an aerial manipulator that consists of a quadcopter flying base and a Delta robotic arm. We propose a novel control approach that consists of extended state observers (ESOs) for dynamic coupling estimation, ESO-based flight controllers, and a cooperative trajectory planner. Compared to the state-of-the-art approaches, the proposed one has some attractive features. First, it requires much less measurement information as opposed to the full-body control approaches and hence can be implemented conveniently and efficiently in practice. Second, while the existing approaches estimate the coupling effect based on precise models, the proposed ESOs can do that based on much less information about the system model. The proposed approach is verified by four experiments on a real aerial manipulation platform. The experimental results show that the average tracking error can reach 1 cm by the proposed approach as opposed to 10 cm by the PX4 baseline controller. Although force control is not considered specifically in the approach, the system can complete aerial weaving tasks thanks to the ESOs in the presence of drag forces applied to the end-effector during manipulation. Note to Practitioners —Aerial manipulators have received increasing research attention in recent years due to their wide range of applications. In this paper, we particularly focus on the high-precision and robust control of aerial manipulators. We propose a novel control approach that consists of extended state observers (ESOs) for dynamic coupling estimation, ESO-based flight controllers, and a cooperative trajectory planner. Four experiments on a real aerial manipulation platform demonstrate the effectiveness of the approach. In future research, we will address the control problem when the aerial manipulator contacts the environment.
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