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Appl. Sci. 2017, 7(1), 67; doi:10.3390/app7010067

Nonlinear Integral Type Observer Design for State Estimation and Unknown Input Reconstruction

Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 701, Taiwan
Academic Editors: Chien-Hung Liu and Huei-Chu Weng
Received: 12 November 2016 / Revised: 2 January 2017 / Accepted: 4 January 2017 / Published: 14 January 2017
(This article belongs to the Special Issue Selected Papers from the 2016 International Conference on Inventions)
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Abstract

This paper is concerned with model-based robust observer designs for state observation and its application for unknown input reconstruction. Firstly, a sliding mode observer (SMO), which provides exponential convergence of estimation error, is designed for a class of multivariable perturbed systems. Observer gain matrices subject to specific structures are going to be imposed such that the unknown perturbation will not affect estimate precision during the sliding modes; Secondly, to improve discontinuous control induced in the SMO as well as pursue asymptotic estimate precision, a proportional-integral type observer (PIO) is further developed. Both the design procedures of the SMO and PIO algorithms are characterized as feasibility issues of linear matrix inequality (LMI) and thus the computations of the control parameters can be efficiently solved. Compared with the SMO, it will be demonstrated that the PIO is capable of achieving better estimation precision as long as the unknown inputs are continuous. Finally, a servo-drive flexible robot arm is selected as an example to demonstrate the applications of the robust observer designs. View Full-Text
Keywords: sliding mode control; robust observer; input reconstruction; linear matrix inequality sliding mode control; robust observer; input reconstruction; linear matrix inequality
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Peng, C.-C. Nonlinear Integral Type Observer Design for State Estimation and Unknown Input Reconstruction. Appl. Sci. 2017, 7, 67.

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