Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/94766
Type: Conference paper
Title: A novel unknown-input estimator for disturbance estimation and compensation
Author: Tang, D.
Chen, L.
Hu, E.
Citation: Proceedings of Australasian Conference on Robotics and Automation, 2014 / vol.02-04-December-2014, pp.116-1-116-8
Publisher: ARAA
Issue Date: 2014
ISBN: 9780980740448
ISSN: 1448-2053
Conference Name: Australasian Conference on Robotics and Automation (ACRA) (02 Dec 2014 - 04 Dec 2014 : Melbourne, Vic.)
Statement of
Responsibility: 
Difan Tang, Lei Chen, Eric Hu
Abstract: A novel unknown-input estimator (UIE) for estimating and rejecting disturbances is proposed in this paper. Effective treatment of unknown disturbing inputs is of vital importance to maintaining satisfactory performance of control systems. Advanced methods that estimate these disturbances and cancel them accordingly outperform traditional approaches. However, limitations remain, including requirements for some knowledge on unknown inputs, derivatives of measured outputs, inversion of plant dynamics, constrained state observer design, parameter optimisation (global optimum not guaranteed), or complicated structures. The proposed UIE is exempted from the aforementioned limitations. It consists of an estimation gain matrix, a state observer, and a low-pass-filter-characterised subsystem. Comparison via simulation is drawn between the new UIE and a benchmark disturbance observer on a multi-input multi-output system. The proposed UIE is shown to be more effective in estimating and compensating unknown inputs.
Description: Paper 116
Rights: Copyright status unknown
RMID: 0030036020
Published version: http://www.araa.asn.au/acra/acra2014/papers/pap116.pdf
Appears in Collections:Mechanical Engineering conference papers

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