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- Publisher Website: 10.1109/ASCC.2015.7244614
- Scopus: eid_2-s2.0-84957613817
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Conference Paper: Joint unscented kalman filter for dual estimation in a bifilar pendulum for a small UAV
Title | Joint unscented kalman filter for dual estimation in a bifilar pendulum for a small UAV |
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Authors | |
Keywords | Joint Unscented Kalman Filter Machine learning Model identification Dual estimation UAV Quadrotor |
Issue Date | 2015 |
Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1002417 |
Citation | The 10th Asian Control Conference (ASCC 2015), Kota Kinabalu, Malaysia, 31 May-3 June 2015. In Conference Proceedings, 2015, p. 1-6 How to Cite? |
Abstract | It has always been difficult to accurately estimate the moment of inertia of an object, e.g. an unmanned aerial vehicle (UAV). Whilst various offline estimation methods exist to allow accurate parametric estimation by minimizing an error cost function, they require large memory consumption, high computational effort, and a long convergence time. The initial estimate's accuracy is also vital in attaining convergence. In this paper, a new real time solution to the model identification problem is provided with the use of a Joint Unscented Kalman Filter for dual estimation. The identification procedures can be easily implemented using a microcontroller, a gyroscope sensor, and a simple bifilar pendulum setup. Accuracy, robustness, and convergence speed are achieved. |
Persistent Identifier | http://hdl.handle.net/10722/217501 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Ma, C | - |
dc.contributor.author | Chen, MZ | - |
dc.contributor.author | Lam, J | - |
dc.contributor.author | Cheung, KC | - |
dc.creator | sml 101516 | - |
dc.date.accessioned | 2015-09-18T06:01:05Z | - |
dc.date.available | 2015-09-18T06:01:05Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | The 10th Asian Control Conference (ASCC 2015), Kota Kinabalu, Malaysia, 31 May-3 June 2015. In Conference Proceedings, 2015, p. 1-6 | - |
dc.identifier.isbn | 978-1-4799-7862-5 | - |
dc.identifier.uri | http://hdl.handle.net/10722/217501 | - |
dc.description.abstract | It has always been difficult to accurately estimate the moment of inertia of an object, e.g. an unmanned aerial vehicle (UAV). Whilst various offline estimation methods exist to allow accurate parametric estimation by minimizing an error cost function, they require large memory consumption, high computational effort, and a long convergence time. The initial estimate's accuracy is also vital in attaining convergence. In this paper, a new real time solution to the model identification problem is provided with the use of a Joint Unscented Kalman Filter for dual estimation. The identification procedures can be easily implemented using a microcontroller, a gyroscope sensor, and a simple bifilar pendulum setup. Accuracy, robustness, and convergence speed are achieved. | - |
dc.language | eng | - |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1002417 | - |
dc.relation.ispartof | Asian Control Conference | - |
dc.subject | Joint Unscented Kalman Filter | - |
dc.subject | Machine learning | - |
dc.subject | Model identification | - |
dc.subject | Dual estimation | - |
dc.subject | UAV | - |
dc.subject | Quadrotor | - |
dc.title | Joint unscented kalman filter for dual estimation in a bifilar pendulum for a small UAV | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Chen, MZ: mzqchen@hku.hk | - |
dc.identifier.email | Lam, J: jlam@hku.hk | - |
dc.identifier.email | Cheung, KC: kccheung@hku.hk | - |
dc.identifier.authority | Chen, MZ=rp01317 | - |
dc.identifier.authority | Lam, J=rp00133 | - |
dc.identifier.authority | Cheung, KC=rp01322 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ASCC.2015.7244614 | - |
dc.identifier.scopus | eid_2-s2.0-84957613817 | - |
dc.identifier.hkuros | 250977 | - |
dc.identifier.hkuros | 254434 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 6 | - |
dc.publisher.place | United States | - |