Adaptive Tracking of a Multi-Sinusoidal Signal with DREM-Based Parameters Estimation*. Issue 1 (July 2017)
- Record Type:
- Journal Article
- Title:
- Adaptive Tracking of a Multi-Sinusoidal Signal with DREM-Based Parameters Estimation*. Issue 1 (July 2017)
- Main Title:
- Adaptive Tracking of a Multi-Sinusoidal Signal with DREM-Based Parameters Estimation*
- Authors:
- Borisov, Oleg I.
Gromov, Vladislav S.
Vedyakov, Alexey A.
Pyrkin, Anton A.
Bobtsov, Alexey A.
Aranovskiy, Stanislav V. - Abstract:
- Abstract: In this paper tracking of an unknown multi-sinusoidal signal with fast online frequency estimation is addressed. The latter has been achieved by the so-called dynamic regressor extension and mixing (DREM) approach, which allows to increase performance of multiple frequency estimation. Designed predictive compensation algorithm is capable to operate under presence of computational or transmission delays. The resultant controller has been implemented to a robotic arm with a computer vision system. An extensive experimental study shows undoubted advantages of the DREM-based frequency estimator in comparison to the classical gradient approach. A detailed analysis of the transient response properties is provided in the paper.
- Is Part Of:
- IFAC-PapersOnLine. Volume 50:Issue 1(2017)
- Journal:
- IFAC-PapersOnLine
- Issue:
- Volume 50:Issue 1(2017)
- Issue Display:
- Volume 50, Issue 1 (2017)
- Year:
- 2017
- Volume:
- 50
- Issue:
- 1
- Issue Sort Value:
- 2017-0050-0001-0000
- Page Start:
- 4282
- Page End:
- 4287
- Publication Date:
- 2017-07
- Subjects:
- Adaptive control -- target tracking -- frequency estimation -- time delay -- robotic manipulators
Automatic control -- Periodicals
629.805 - Journal URLs:
- https://www.journals.elsevier.com/ifac-papersonline/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.ifacol.2017.08.835 ↗
- Languages:
- English
- ISSNs:
- 2405-8963
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8260.xml