Protocol-Based Unscented Kalman Filtering in the Presence of Stochastic Uncertainties
In this paper, the unscented Kalman filtering (UKF) problem is investigated for a class of general nonlinear systems with stochastic uncertainties under communication protocols. A modified unscented transformation is put forward to account for stochastic uncertainties caused by modeling errors. For...
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| Published in | IEEE transactions on automatic control Vol. 65; no. 3; pp. 1303 - 1309 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.03.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0018-9286 1558-2523 |
| DOI | 10.1109/TAC.2019.2929817 |
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| Abstract | In this paper, the unscented Kalman filtering (UKF) problem is investigated for a class of general nonlinear systems with stochastic uncertainties under communication protocols. A modified unscented transformation is put forward to account for stochastic uncertainties caused by modeling errors. For preventing data collisions and mitigating communication burden, the round-robin protocol and the weighted try-once-discard protocol are, respectively, introduced to regulate the data transmission order from sensors to the filter. Then, by employing two kinds of data-holding strategies (i.e., zero-order holder and zero input) for those nodes without transmission privilege, two novel protocol-based measurement models are formulated. Subsequently, by resorting to the sigma point approximation method, two resource-saving UKF algorithms are developed, where the impact from the underlying protocols on the filter design is explicitly quantified. Finally, compared with the protocol-based extended Kalman filtering algorithms, a simulation example is presented to demonstrate the effectiveness of the proposed protocol-based UKF algorithms. |
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| AbstractList | In this paper, the unscented Kalman filtering (UKF) problem is investigated for a class of general nonlinear systems with stochastic uncertainties under communication protocols. A modified unscented transformation is put forward to account for stochastic uncertainties caused by modeling errors. For preventing data collisions and mitigating communication burden, the round-robin protocol and the weighted try-once-discard protocol are, respectively, introduced to regulate the data transmission order from sensors to the filter. Then, by employing two kinds of data-holding strategies (i.e., zero-order holder and zero input) for those nodes without transmission privilege, two novel protocol-based measurement models are formulated. Subsequently, by resorting to the sigma point approximation method, two resource-saving UKF algorithms are developed, where the impact from the underlying protocols on the filter design is explicitly quantified. Finally, compared with the protocol-based extended Kalman filtering algorithms, a simulation example is presented to demonstrate the effectiveness of the proposed protocol-based UKF algorithms. |
| Author | Chen, Yun Wei, Guoliang Liu, Shuai Wang, Zidong |
| Author_xml | – sequence: 1 givenname: Shuai orcidid: 0000-0003-0523-022X surname: Liu fullname: Liu, Shuai email: liushuai871030@163.com organization: College of Science, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai, China – sequence: 2 givenname: Zidong orcidid: 0000-0002-9576-7401 surname: Wang fullname: Wang, Zidong email: Zidong.Wang@brunel.ac.uk organization: Department of Computer Science, Brunel University London, Uxbridge, U.K – sequence: 3 givenname: Yun orcidid: 0000-0002-9934-9979 surname: Chen fullname: Chen, Yun email: yunchen@hdu.edu.cn organization: Institute of Information and Control, Hangzhou Dianzi University, Hangzhou, China – sequence: 4 givenname: Guoliang orcidid: 0000-0003-2928-4142 surname: Wei fullname: Wei, Guoliang email: guoliang.wei@usst.edu.cn organization: College of Science, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai, China |
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| SubjectTerms | Algorithms Approximation algorithms Communication protocols Computer simulation Data transmission Filter design (mathematics) Kalman filtering (KF) Kalman filters Nonlinear systems Protocols Stochastic processes stochastic uncertainties Time-varying systems Uncertainty unscented transformation (UT) |
| Title | Protocol-Based Unscented Kalman Filtering in the Presence of Stochastic Uncertainties |
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