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http://dx.doi.org/10.5302/J.ICROS.2016.16.0061

An Experimental Study on Realtime Estimation of a Nominal Model for a Disturbance Observer: Recursive Least Squares Approach  

Lee, Sang-Deok (ISEE, Department of Mechatronics Engineering, Chungnam National University)
Jung, Seul (ISEE, Department of Mechatronics Engineering, Chungnam National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.22, no.8, 2016 , pp. 650-655 More about this Journal
Abstract
In this paper, a novel RLS-based DOB (Recursive Least Squares Disturbance Observer) scheme is proposed to improve the performance of DOB for nominal model identification. A nominal model can be generally assumed to be a second order system in the form of a proper transfer function of an ARMA (Autoregressive Moving Average) model. The RLS algorithm for the model identification is proposed in association with DOB. Experimental studies of the balancing control of a one-wheel robot are conducted to demonstrate the feasibility of the proposed method. The performances between the conventional DOB scheme and the proposed scheme are compared.
Keywords
autoregressive moving average; disturbance observer; model identification; one-wheel robot; recursive least square;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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