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A Word of Thanks, and the Reviewer List for 2023 致谢词和 2023 年审稿人名单
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-16 DOI: 10.1142/s2301385024010015
Jie Chen, Ben M. Chen, Lihua Xie
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引用次数: 0
Development and Flight Testing of Guidance, Navigation, Control, and Operator Interface for Shipboard Helicopter Operations 用于舰载直升机操作的制导、导航、控制和操作员界面的开发和飞行测试
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-14 DOI: 10.1142/s2301385025500220
Jintasit Pravitra, Eric N. Johnson
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引用次数: 0
Safety-critical Stabilizing Design of Switched Linear Autonomous Systems 开关线性自主系统的安全关键稳定设计
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-14 DOI: 10.1142/s2301385024410139
Miaomiao Wang, Zhendong Sun
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引用次数: 0
Distributed Event-Triggered Algorithms for Multi-Objective Resource Allocation Problem 多目标资源分配问题的分布式事件触发算法
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-14 DOI: 10.1142/s2301385024410140
Xuesi Zhao, Kunpeng Zhang, Lei Xu, Weinan Gao, Tao Yang
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引用次数: 0
Defense for Advanced Persistent Threat with Inadvertent and Malicious Insider Threats 利用无意和恶意内部威胁防御高级持续性威胁
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-14 DOI: 10.1142/s2301385024410152
Ziqin Chen, Guanpu Chen, Yiguang Hong
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引用次数: 0
UAV Trajectory Optimization for Maximum Soaring in Windy Environment 优化无人机轨迹,使其在多风环境中实现最大翱翔
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-14 DOI: 10.1142/s2301385025500232
Hassan Haghighi, Daniel Delahaye, J. Moschetta, D. Asadi
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引用次数: 0
A Distributed Optimization Approach for Collaborative Object Lifting Using Multiple Aerial Robots 使用多个空中机器人协作提升物体的分布式优化方法
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-08 DOI: 10.1142/s2301385024410127
Jinxin Liu, Chao Sun, Zhi Feng, Renhe Guan, Jindong Chang, Guoqiang Hu
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引用次数: 0
Controlling Musculoskeletal System with Spinal Cord-inspired Constraint Force Field Primitives 用脊髓启发的约束力场基元控制肌肉骨骼系统
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-08 DOI: 10.1142/s2301385024410115
Shanlin Zhong, Yaxiong Wu, Wei Wu, Hong Qiao
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引用次数: 0
A Particle Fusion Approach for Distributed Filtering and Smoothing 分布式过滤和平滑的粒子融合方法
IF 5.3 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-12-01 DOI: 10.1142/s2301385024410103
Tony X. Lin, Samuel Coogan, Donald A. Sofge, Fumin Zhang
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引用次数: 0
Cooperative guidance of a multi-quadrotors system with switching and reduced network information exchange: application to uncooperative target entrapping 具有交换和减少网络信息交换的多四旋翼系统协同制导:在非合作目标诱捕中的应用
3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-11-10 DOI: 10.1142/s2301385025500141
Ahmed Allam, Abdelkrim Nemra, Mohamed Tadjine
In this paper, we investigate the leader–followers Time-Varying Formation Tracking (TVFT) problem of a networked Multi-Agent Systems (MASs) based output feedback. The agents’ behavior is featured by linear dynamics. The interaction topology among the agents is switching over time, directed and only assumed to contain a directed spanning tree. This latter is rooted by a leader-agent whose control input is unknown and bounded. A novel fully distributed TVFT controller is proposed that exhibits a reduced network information exchange property among the agents, thus less communicating-resources are utilized. The proposed controlled design is based on an adaptive observer and disturbance rejection technique, where the unknown leader-input is viewed as an external disturbance. The key feature lies in introducing a local observer in each agent-controller design to observe all the relative neighboring output-measurements and the relative neighboring distributed observer-outputs, all gathered in one signal that we denote the agent’s network information signal. The Lyapunov theory is used to prove that the closed-loop MASs tracking error is stable. An analysis of the effect of the interaction topology structure on the tracking-error convergence rate is further provided, showing the validity of the proposed formation control for switching interaction topologies. Finally, to verify the effectiveness of the obtained results, the proposed controller is extended to a cooperative guidance of a networked quadrotors to track and entrap an uncooperative aerial target that plays the role of a passive leader.
本文研究了基于输出反馈的网络化多智能体系统(MASs)的leader - follower时变队形跟踪问题。智能体的行为具有线性动力学特征。代理之间的交互拓扑是随时间切换的,有向的,并且只假设包含有向生成树。后者是由一个控制输入未知且有界的领导-代理建立的。提出了一种新型的全分布式TVFT控制器,该控制器减少了智能体之间的网络信息交换特性,从而减少了通信资源的使用。所提出的控制设计基于自适应观测器和干扰抑制技术,其中未知的前导输入被视为外部干扰。关键特征在于在每个代理控制器设计中引入一个局部观测器来观察所有相对相邻的输出-测量和相对相邻的分布式观测器-输出,所有这些都聚集在一个信号中,我们表示代理的网络信息信号。利用李雅普诺夫理论证明了闭环质量跟踪误差是稳定的。进一步分析了交互拓扑结构对跟踪误差收敛速度的影响,验证了所提编队控制在切换交互拓扑时的有效性。最后,为了验证所获得结果的有效性,将所提出的控制器扩展到网络化四旋翼飞行器的协同制导,以跟踪和诱捕扮演被动领导者角色的非合作空中目标。
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引用次数: 0
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Unmanned Systems
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