对于智能制造中的机器人系统的随机游戏的分布式算法
Xiongnan He1, Zongli Lin1, Qing Chang2
1Charles L. Brown Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia 22904, USA.
Chaos (Woodbury, N.Y.)
|February 3, 2025
概括
本研究针对面临不确定的成本的机器人系统的分布式通用随机纳什平衡. 提霍诺夫规范化方法确保了趋同,使机器人能够在约束范围内有效运行.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制理论 控制理论
- 优化优化 优化优化
背景情况:
- 分布式系统需要强大的寻求平衡的算法.
- 成本函数的不确定性给机器人系统协调带来了挑战.
- 不平等的约束定义了机器人代理的操作界限.
研究的目的:
- 开发一种分布式算法,用于在机器人系统中寻求概括的随机纳什平衡.
- 处理不确定性和不平等约束的成本函数.
- 为了确保多个机器人的稳定和高效的协调.
主要方法:
- 使用提霍诺夫规范化来管理成本函数的不确定性.
- 在控制规律中引入辅助参数,用于寻找平衡.
- 采用运营商分割方法进行趋同分析.
主要成果:
- 成功地将强烈单调的条件放松到严格单调.
- 证明了拟议的控制法律的趋同.
- 在多机器人通信网络中验证了算法的有效性.
结论:
- 提出的方法有效地实现了分布式通用静态纳什平衡寻找机器人.
- 提霍诺夫规范化和辅助参数是处理不确定性和约束的关键.
- 运营商分割方法为趋同分析提供了一个严格的框架.
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