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CDC
2015
IEEE

Removing erroneous history stack elements in concurrent learning

7 years 11 months ago
Removing erroneous history stack elements in concurrent learning
— This paper is concerned with erroneous history stack elements in concurrent learning. Concurrent learningbased update laws make concurrent use of current measurements and recorded data. This replaces persistence of excitation by a less restrictive linear independence of the recorded data. However, erroneous or outdated data prevents convergence to the true parameters. We present insights into the convergence properties of concurrent learning and propose a routine to recognize and remove erroneous data online. We characterize erroneous data based on its inconsistency with the current measurement-based update. We numerically validate that the proposed routine restores the tracking ability and improves the convergence properties of concurrent learning.
Stefan Kersting, Martin Buss
Added 18 Apr 2016
Updated 18 Apr 2016
Type Journal
Year 2015
Where CDC
Authors Stefan Kersting, Martin Buss
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