Probabilistic learning technique for improved accuracy ofsinusoidal encoders
Kavanagh, R.C.
Dept. of Electr. & Electron. Eng., Univ. Coll. Cork;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Jun 2001
Volume: 48,
Issue: 3
On page(s): 673-681
ISSN: 0278-0046
References Cited: 26
CODEN: ITIED6
INSPEC Accession Number: 6951742
Digital Object Identifier: 10.1109/41.925595
Current Version Published: 2002-08-07
Abstract
Sinusoidal-encoder-based digital tachometers are often limited by
nonidealities in both encoder construction and interface electronics. A
probabilistically based compensation technique is presented which
dispenses with the need for specialized calibration equipment. A
code-density array, obtained during a learning phase, is utilized to
yield a compensation function which approximates to the average
relationship over the mechanical cycle between the calculated electrical
angle (as determined by an arctangent-based algorithm) and the actual
angle. An extended version of this probabilistically compensated
sinusoidal encoder technique is used to compensate for variations in the
encoder characteristics as it rotates through a mechanical cycle. An
analysis of the learning-time requirements of the system is presented.
Practical results, utilizing performance measures common in the testing
of analog-to-digital converters, confirm the utility of the method. An
example of the benefits which accrue from the inclusion of the enhanced
sensor in closed-loop systems is also provided
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