Abstract
In conventional system identification and state estimation problems, it is commonly assumed that the output signal of a dynamical system is sampled at every regular time interval. This paper addresses the identification and estimation problems under the Lebesgue sampling, which is a type of event-triggered sampling such that the output signal is sampled only when it crosses a specific threshold. In this paper, it is assumed that the output signal is sampled under the Lebesgue sampling rule. Then, the time interval between two samples possesses information such that the signal crosses none of the thresholds during the interval. The inter-sample information plays a key role to improve the accuracy of modeling and estimation. The problems utilizing the information are formulated. We propose likelihood-based methods of both system identification and state estimation to solve the problems. The effectiveness of the methods are illustrated in numerical examples.
| Original language | English |
|---|---|
| Title of host publication | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1408-1413 |
| Number of pages | 6 |
| Volume | 2017-January |
| ISBN (Electronic) | 9781509021826 |
| DOIs | |
| Publication status | Published - 2017 Oct 6 |
| Event | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 - Kohala Coast, United States Duration: 2017 Aug 27 → 2017 Aug 30 |
Other
| Other | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 |
|---|---|
| Country | United States |
| City | Kohala Coast |
| Period | 17/8/27 → 17/8/30 |
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ASJC Scopus subject areas
- Theoretical Computer Science
- Hardware and Architecture
- Software
- Control and Systems Engineering
Cite this
System identification and state estimation under lebesgue sampling : Use of inter-sample information. / Kawaguchi, Takahiro; Inoue, Masaki; Maruta, Ichiro; Adachi, Shuichi.
1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 1408-1413.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - System identification and state estimation under lebesgue sampling
T2 - Use of inter-sample information
AU - Kawaguchi, Takahiro
AU - Inoue, Masaki
AU - Maruta, Ichiro
AU - Adachi, Shuichi
PY - 2017/10/6
Y1 - 2017/10/6
N2 - In conventional system identification and state estimation problems, it is commonly assumed that the output signal of a dynamical system is sampled at every regular time interval. This paper addresses the identification and estimation problems under the Lebesgue sampling, which is a type of event-triggered sampling such that the output signal is sampled only when it crosses a specific threshold. In this paper, it is assumed that the output signal is sampled under the Lebesgue sampling rule. Then, the time interval between two samples possesses information such that the signal crosses none of the thresholds during the interval. The inter-sample information plays a key role to improve the accuracy of modeling and estimation. The problems utilizing the information are formulated. We propose likelihood-based methods of both system identification and state estimation to solve the problems. The effectiveness of the methods are illustrated in numerical examples.
AB - In conventional system identification and state estimation problems, it is commonly assumed that the output signal of a dynamical system is sampled at every regular time interval. This paper addresses the identification and estimation problems under the Lebesgue sampling, which is a type of event-triggered sampling such that the output signal is sampled only when it crosses a specific threshold. In this paper, it is assumed that the output signal is sampled under the Lebesgue sampling rule. Then, the time interval between two samples possesses information such that the signal crosses none of the thresholds during the interval. The inter-sample information plays a key role to improve the accuracy of modeling and estimation. The problems utilizing the information are formulated. We propose likelihood-based methods of both system identification and state estimation to solve the problems. The effectiveness of the methods are illustrated in numerical examples.
UR - http://www.scopus.com/inward/record.url?scp=85047736199&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047736199&partnerID=8YFLogxK
U2 - 10.1109/CCTA.2017.8062656
DO - 10.1109/CCTA.2017.8062656
M3 - Conference contribution
VL - 2017-January
SP - 1408
EP - 1413
BT - 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -