A Collision-Free Pursuit-Evasion Framework for Indirect Herding and Formation Control of Noncooperative UAVs

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Ye Zhang, Yutong Zhu, Minghu Tan, Jingyu Wang
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引用次数: 0

Abstract

In this article, we aim to design a general framework for the pursuit-evasion (PE) game of multiple UAVs. Based on the distance between the pursuers and the evader, the whole pursuit-evasion process is decoupled into a seeking stage and a herding stage. A formation control method is proposed to make sure that the pursuers can find and drive the noncooperative evaders along a desired trajectory towards the designated target while maintaining a preset formation. In the meantime, an adaptive potential function is designed to achieve collision avoidance to both obstacles and other agents in the formation. The main contribution is that it combines formation control and collision avoidance in the problem of indirect herding, which is rarely addressed before. Also, the convergence and effectiveness of the designed controller for trajectory tracking and formation maintenance are proven and verified in the article. Simulation results in two and three dimensional space show that the proposed framework achieves the goal of coordinated herding and collision avoidance in a pursuit-evasion scenario under uncertainties and external disturbances.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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