为网络无人地面车辆提供紧的阵列和轨迹跟踪
Xiaomin Zhao1, Zhengrong Cui1, Chee-Meng Chew2
1School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, China.
Fundamental research
|February 6, 2026
概括
这项研究涉及无人地面车辆群系统的网络干扰. 合作适应性强大的控制确保稳定,紧的构成和轨迹跟踪,尽管网络安全挑战.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 网络物理系统 网络物理系统
- 网络化自主系统 网络化自主系统
背景情况:
- 无人地面车辆 (UGV) 群需要强大的控制策略来管理复杂的行为.
- 网络干扰和系统不确定性对网络群系统的安全性和性能构成重大威胁.
- 面对网络攻击,确保可靠的操作对于UGV群体应用程序至关重要.
研究的目的:
- 为面临网络干扰的无人地面车辆群系统开发合作控制框架.
- 设计适应性强大的控制策略,考虑系统不确定性和网络威胁.
- 为了实现全球稳定,紧的形成,合作狩猎,以及追踪UGV群的轨迹.
主要方法:
- 将集成的潜在函数抽象化,以模拟群体行为 (吸引力,排斥力,轨迹跟踪) 进入动态模型中.
- 利用动力学模型作为系统约束,分解系统的不确定性.
- 提出一类合作性适应性强大的控制,以确保遵守系统约束.
主要成果:
- 证明了全球稳定性,包括UGV群的统一边界和统一终极边界.
- 在无人地面车辆中实现了紧的形成维护.
- 在群体中成功实施了合作的狩猎行为.
- 验证了整个UGV系统的准确轨迹跟踪.
结论:
- 拟议的合作适应性强有力的控制有效地管理UGV群中的网络干扰和系统不确定性.
- 开发的控制策略确保了多个关键群目标的强大性能:稳定性,形成,狩猎和跟踪.
- 这项研究为智能自动驾驶汽车系统的安全可靠的合作控制提供了可行的解决方案.
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