Input-To-State Stable Tracking Control Design for Fully Actuated Mechanical Systems Using Position Measurements Only

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Joel Ferguson, Naoki Sakata, Kenji Fujimoto
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引用次数: 0

Abstract

In this article, we consider tracking control design for fully actuated mechanical systems using position measurements only. A recently developed hybrid momentum observer is used, which has the property that the momentum estimation error is a passive output from the estimation error dynamics. To complement this, a tracking error system is constructed with error coordinates defined between the momentum estimate and the desired momentum. The tracking error dynamics are similarly passive with the momentum estimation error as the passive input to the tracking error system. Exploiting the passivity of both the observer and tracking controller subsystems, a passive interconnection is constructed which results in a storage function for the joint observer and controller systems. It is shown that the joint system is Input-to-State Stable (ISS) with respect to external disturbances and the effect of the disturbance can be attenuated via tuning gains. The results are numerically demonstrated on a 2-link manipulator system.

仅使用位置测量的全驱动机械系统的输入到状态稳定跟踪控制设计
在本文中,我们只考虑使用位置测量的全驱动机械系统的跟踪控制设计。采用了一种新开发的混合动量观测器,该观测器具有动量估计误差是估计误差动态的被动输出的特性。为此,在动量估计和期望动量之间定义误差坐标,构造跟踪误差系统。跟踪误差动力学同样是被动的,动量估计误差作为跟踪误差系统的被动输入。利用观测器子系统和跟踪控制器子系统的无源性,构建了无源互联,实现了观测器与控制器联合系统的存储功能。结果表明,对于外部干扰,该联合系统是输入到状态稳定的,并且干扰的影响可以通过调谐增益来减弱。结果在一个二连杆机械手系统上进行了数值验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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