模块化机器人操纵器的动态事件触发的基于战略的最佳控制:一个多人非零和游戏视角
IEEE transactions on cybernetics
|October 7, 2024
概括
本研究引入了一个动态事件触发控制模块化机器人操纵器 (MRM) 面临有限的资源和干扰. 这种新的方法提高了资源效率,并确保了系统稳定性,这对于复杂的机器人应用至关重要.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 人工智能的人工智能
背景情况:
- 模块化机器人操纵器 (MRM) 面临传感器和控制器的计算限制,需要高效的通信范式.
- 传统的事件触发机制与资源限制作斗争,推动了对先进解决方案的需求,如动态事件触发控制.
- 在MRM系统中不确定的干扰对控制精度和稳定性构成重大挑战.
研究的目的:
- 为MRM系统开发一个最佳的控制方案,使用动态事件触发机制.
- 解决资源限制和MRM应用中的不确定性干扰问题.
- 提高资源利用效率和系统设计灵活性在MRM.
主要方法:
- 使用联合扭矩反建立了MRM的动态模型,并使用数据驱动的神经网络进行不确定性估计.
- 将MRM跟踪控制问题转化为多人非零和差分游戏框架.
- 利用自适应动态编程进行静态事件触发控制,引入内部动态变量来分析动态触发规则.
主要成果:
- 开发了一个动态事件触发的MRMs与不确定的干扰的控制策略.
- 与传统方法相比,证明了更好的资源利用和系统设计灵活性.
- 通过指数减弱信号确保正的最小采样间隔,排除Zeno行为.
结论:
- 拟议的动态事件触发控制方案确保了MRM系统的非对称稳定性,该稳定性得到了利亚普诺夫理论的验证.
- 实验结果证实了开发的最佳控制策略的有效性.
- 该方法为资源有限的MRM应用提供了强大而高效的解决方案.
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