鲁棒扩展H∞滤波与一致控制在多机器人运动系统中的应用

P. Aditya, E. Apriliani, D. K. Arif, Mardlijah
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引用次数: 0

摘要

现在机器人的发展越来越先进,特别是多机器人(一组单个机器人)能够执行给定的协作任务。通过对机器人的大量研究,我们考虑了一种可以估计下一个运动的方法,即鲁棒扩展$H_{\infty }$滤波方法,它是数据同化的发展方法之一。数据同化是一种估计方法,它需要系统模型和系统测量模型。此外,为了接近机器人的运动,本研究还实施了共识控制。共识可以被解释为一个协议,其中多个机器人被观察到被控制在一个协议的点上相遇。本研究的结果是由估计和共识控制方法产生的非常小的误差,这些方法在系统上运行良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Application of Robust Extended H∞ Filter and Consensus Control to The Multi-robot Motion Systems
The development of robots is increasingly advanced now, especially for multi-robots (a group of single robots) that are capable of carrying out cooperative tasks given. With a lot of research on robots, we consider an approach that can estimate the next motion, namely the Robust Extended $H_{\infty }$ filter method, which is one of the development methods of data assimilation. Data assimilation is an estimation method that requires a system model and measurement model of the system. Besides, to approach the motion of robots, the implementation of consensus control was carried out in this study. Consensus can be interpreted as an agreement, where multi-robots were observed to be controlled to meet at a point of an agreement. The results of this study are very small errors generated by estimation and consensus control methods that work well on the system.
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