基于鸟群的多智能体系统编队旋转控制的能量平衡先导切换策略

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS
C. Dotson, Geronimo Macias, Kooktae Lee
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引用次数: 0

摘要

本文研究了受鸟群启发的多智能体系统的编队旋转控制的能量平衡先导切换策略。排成v形队形并采用领队轮换策略的鸟类能够飞得更远,因为阻力更小,因此能量消耗更少。这种领队轮换的群居行为将导致更多的整体能量守恒,对那些需要长途飞行而不着陆的候鸟尤其有益。为了提高多智能体系统的飞行距离,在此基础上提出了一种能量平衡的机头切换策略。多智能体系统的编队控制由共识算法实现,该算法通过利用智能体之间的信息交换实现完全去中心化。所提出的leader-switching方法并不一定与共识动力学相结合,因此leader-switching算法可以与群体控制动力学解耦。因此,该方法可以简化引线切换算法,使其易于实现。在此基础上,提出了基于各agent能量消耗模型的解析飞行距离。为了验证该方法的有效性,给出了几个仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy-Balanced Leader-Switching Policy for Formation Rotation Control of Multi-Agent Systems Inspired by Bird Flocks
This paper addresses an energy-balanced leader-switching policy for formation rotation control of multi-agent systems inspired by bird flocks. Birds that flock in V-formation with a leader rotation strategy are able to travel longer distances due to reduced drag and therefore less energy expenditure. This flocking behavior with a leader rotation will result in more conservation of overall energy and will be particularly beneficial to migrating birds that should fly long distances without landing. In this paper, we propose an energy-balanced leader-switching policy inspired by this bird flocking behavior in order to increase the flight range for multi-agent systems. The formation control of multi-agent systems is achieved by the consensus algorithm, which is fully decentralized through the use of information exchanges between agents. The proposed leader-switching method is not necessarily incorporated with the consensus dynamics and thus, the leader-switching algorithm can be decoupled from formation control dynamics. Therefore, the proposed method can simplify the leader-switching algorithm, making it easy to implement. Moreover, we propose the analytic flight distance based on the energy consumption model for each agent. To test the validity of the developed method, several simulation results are presented.
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来源期刊
Mechatronic Systems and Control
Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.40
自引率
66.70%
发文量
27
期刊介绍: This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.
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