欠驱动机械系统的能量轨迹跟踪:无速度和抗干扰方法

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
N. Javanmardi, P. Borja, A. J. van der Schaft, M. J. Yazdanpanah, J. M. A. Scherpen
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引用次数: 0

摘要

这项工作研究了三种能量整形控制方法来解决特定类别的欠驱动机械系统的轨迹跟踪问题。特别是,利用收缩系统和动态扩展的概念来解决轨迹跟踪问题,同时解决诸如缺乏速度传感器和持续干扰的存在等实现问题。为此,开发了第一个不需要速度测量的跟踪控制器。引入了第二个控制器,解决了轨迹跟踪问题,同时抑制了匹配的恒定干扰。然后,第三种方法建立组合上述两个控制器的条件。结果表明,对于特定类型的欠驱动机械系统,所提出的设计方法保证了闭环系统的指数收敛性。用实例说明了第三种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Energy-Based Trajectory Tracking for Underactuated Mechanical Systems: Velocity-Free and Disturbance Rejection Methods

Energy-Based Trajectory Tracking for Underactuated Mechanical Systems: Velocity-Free and Disturbance Rejection Methods

This work investigates three energy-shaping control approaches to address the trajectory-tracking problem for specific classes of underactuated mechanical systems. In particular, the notions of contractive systems and dynamic extensions are utilized to solve the trajectory-tracking problem while addressing implementation issues such as the lack of velocity sensors and the presence of constant disturbances. To this end, a first tracking controller is developed without the need for velocity measurements. A second controller is introduced, solving the trajectory-tracking problem while rejecting matched constant disturbances. Then, a third approach establishes conditions to combine both mentioned controllers. It is shown that the proposed design methods guarantee exponential convergence of closed-loop systems for specific classes of underactuated mechanical systems. The third method is illustrated with an example.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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