@inbook{241fe0cb0b6b4f69a27a29fe9ea6e7de,
title = "Force Estimation and Control Enhanced by a Force-Derivative Sensor",
abstract = "The paper presents a scheme for force estimation and control of a motion system in contact with an environment. Especially, force-derivative sensing is used to facilitate force estimation and control. Regarding force estimation, this paper proposes an integrated force estimator (IFE) that fuses an extended state observer (ESO) and force-derivative sensing. The force-derivative sensing provides the derivative of force, referred to as yank. Meanwhile, the ESO receives positional information and estimates a force. The IFE fuses the yank signal with the force estimate produced by the ESO and provides an improved force estimate. Compared with previous research on yank, the proposed system does not require an additional force sensor to simultaneously obtain both yank and force information. The proposed IFE can provide a better force estimate than traditional ESOs and alleviates the drift problem encountered in the direct integration of yank. Concerning force control, derivative control can be used to offer damping due to the existence of force-derivative sensing. Experimental results on a platform with a linear motor are reported, and a comparative study is conducted in this work. The experimental results demonstrate the feasibility and advantage of the proposed scheme.",
keywords = "Extended state observer, Force derivative, Force observation, Motion system, Piezoelectric sensor, Sensor fusion",
author = "Lu, {Yu Sheng} and Chen, {Liang Hao}",
note = "Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2024",
doi = "10.1007/978-3-031-39303-7_1",
language = "English",
series = "IUTAM Bookseries",
publisher = "Springer Science and Business Media B.V.",
pages = "3--19",
booktitle = "IUTAM Bookseries",
}