DocumentCode :
2943894
Title :
Modeling and estimation of servo actuator dynamic variability with application to LTO-drives
Author :
Wang, Longhao ; De Callafon, Raymond A.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Univ. of California, La Jolla, CA, USA
fYear :
2012
fDate :
11-14 July 2012
Firstpage :
796
Lastpage :
801
Abstract :
Starting from multiple frequency domain measurements, this paper presents a procedure to formulate a dynamic model of a servo actuator that consists of a nominal model and an allowable model perturbation in the form of a parametric and unstructured uncertainty. A separation between parametric and unstructured uncertainty is achieved by first estimating low order linear parameter models via frequency domain curve fitting followed by a linear Principle Component Analysis (PCA) to bound the parametric variations on the estimated parameters. Remaining differences between the low order parametric models and the measured frequency responses are captured by a bounded unstructured uncertainty on a frequency dependent dual-Youla parameter that uses prior information on a stabilizing feedback controller. The resulting perturbation model is written in a standard Linear Fractional Transformation (LFT) form and the procedure is applied to experimental data obtained from several mechanically equivalent servo actuators in a Linear Tape Open (LTO) drive.
Keywords :
actuators; curve fitting; disc drives; feedback; frequency response; frequency-domain analysis; magnetic tapes; perturbation techniques; principal component analysis; servomechanisms; stability; uncertain systems; LFT; LTO drive; PCA; bounded unstructured uncertainty; curve fitting; feedback controller; frequency dependent dual-Youla parameter; frequency domain measurement; frequency response measurement; linear fractional transformation; linear parameter model; linear tape open; parametric uncertainty; perturbation model; principle component analysis; servo actuator dynamic variability; stabilisation; Actuators; Data models; Frequency domain analysis; Principal component analysis; Servomotors; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2012 IEEE/ASME International Conference on
Conference_Location :
Kachsiung
ISSN :
2159-6247
Print_ISBN :
978-1-4673-2575-2
Type :
conf
DOI :
10.1109/AIM.2012.6265970
Filename :
6265970
Link To Document :
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