Unscented Kalman filter applied to noisy synchronization of rossler chaotic system

Komeil Nosrati; Ali Shokouhi Rostami; Asad Azemi; Naser Pariz

doi:10.1109/ICACC.2011.6016435

Unscented Kalman filter applied to noisy synchronization of rossler chaotic system

Komeil Nosrati, Ali Shokouhi Rostami, Asad Azemi, Naser Pariz

Penn State Brandywine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Extended Kalman Filter (EKF) has been widely used as an important tool in practical applications to estimate states of nonlinear systems. There are a number of deficiencies in EKF such as biased estimation, complexity in calculation and inefficacity in not being able to compute analytical derivatives affect its application in many fields. In this paper, Unscented Kalman Filter (UKF) is employed for estimation of the state variables of the chaotic dynamical system. The chaotic synchronization is implemented by the UKF in the presence of processing noise and measurement noise. The results of the simulation on the Rossler chaotic system by UKF and its comparison with EKF show that the UKF has more accuracy and efficiency than EKF.

Original language	English (US)
Title of host publication	2011 3rd International Conference on Advanced Computer Control, ICACC 2011
Pages	378-383
Number of pages	6
DOIs	https://doi.org/10.1109/ICACC.2011.6016435
State	Published - Oct 4 2011
Event	3rd IEEE International Conference on Advanced Computer Control, ICACC 2011 - Harbin, China Duration: Jan 18 2011 → Jan 20 2011

Publication series

Name	2011 3rd International Conference on Advanced Computer Control, ICACC 2011

Other

Other	3rd IEEE International Conference on Advanced Computer Control, ICACC 2011
Country/Territory	China
City	Harbin
Period	1/18/11 → 1/20/11

All Science Journal Classification (ASJC) codes

Computer Science Applications
Control and Systems Engineering

Access to Document

10.1109/ICACC.2011.6016435

Cite this

Nosrati, K., Rostami, A. S., Azemi, A., & Pariz, N. (2011). Unscented Kalman filter applied to noisy synchronization of rossler chaotic system. In 2011 3rd International Conference on Advanced Computer Control, ICACC 2011 (pp. 378-383). Article 6016435 (2011 3rd International Conference on Advanced Computer Control, ICACC 2011). https://doi.org/10.1109/ICACC.2011.6016435

@inproceedings{c2084ad688044056b699c3f466d9f193,

title = "Unscented Kalman filter applied to noisy synchronization of rossler chaotic system",

abstract = "Extended Kalman Filter (EKF) has been widely used as an important tool in practical applications to estimate states of nonlinear systems. There are a number of deficiencies in EKF such as biased estimation, complexity in calculation and inefficacity in not being able to compute analytical derivatives affect its application in many fields. In this paper, Unscented Kalman Filter (UKF) is employed for estimation of the state variables of the chaotic dynamical system. The chaotic synchronization is implemented by the UKF in the presence of processing noise and measurement noise. The results of the simulation on the Rossler chaotic system by UKF and its comparison with EKF show that the UKF has more accuracy and efficiency than EKF.",

author = "Komeil Nosrati and Rostami, {Ali Shokouhi} and Asad Azemi and Naser Pariz",

year = "2011",

month = oct,

day = "4",

doi = "10.1109/ICACC.2011.6016435",

language = "English (US)",

isbn = "9781424488087",

series = "2011 3rd International Conference on Advanced Computer Control, ICACC 2011",

pages = "378--383",

booktitle = "2011 3rd International Conference on Advanced Computer Control, ICACC 2011",

note = "3rd IEEE International Conference on Advanced Computer Control, ICACC 2011 ; Conference date: 18-01-2011 Through 20-01-2011",

}

Nosrati, K, Rostami, AS, Azemi, A & Pariz, N 2011, Unscented Kalman filter applied to noisy synchronization of rossler chaotic system. in 2011 3rd International Conference on Advanced Computer Control, ICACC 2011., 6016435, 2011 3rd International Conference on Advanced Computer Control, ICACC 2011, pp. 378-383, 3rd IEEE International Conference on Advanced Computer Control, ICACC 2011, Harbin, China, 1/18/11. https://doi.org/10.1109/ICACC.2011.6016435

Unscented Kalman filter applied to noisy synchronization of rossler chaotic system. / Nosrati, Komeil; Rostami, Ali Shokouhi; Azemi, Asad et al.
2011 3rd International Conference on Advanced Computer Control, ICACC 2011. 2011. p. 378-383 6016435 (2011 3rd International Conference on Advanced Computer Control, ICACC 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Unscented Kalman filter applied to noisy synchronization of rossler chaotic system

AU - Nosrati, Komeil

AU - Rostami, Ali Shokouhi

AU - Azemi, Asad

AU - Pariz, Naser

PY - 2011/10/4

Y1 - 2011/10/4

N2 - Extended Kalman Filter (EKF) has been widely used as an important tool in practical applications to estimate states of nonlinear systems. There are a number of deficiencies in EKF such as biased estimation, complexity in calculation and inefficacity in not being able to compute analytical derivatives affect its application in many fields. In this paper, Unscented Kalman Filter (UKF) is employed for estimation of the state variables of the chaotic dynamical system. The chaotic synchronization is implemented by the UKF in the presence of processing noise and measurement noise. The results of the simulation on the Rossler chaotic system by UKF and its comparison with EKF show that the UKF has more accuracy and efficiency than EKF.

AB - Extended Kalman Filter (EKF) has been widely used as an important tool in practical applications to estimate states of nonlinear systems. There are a number of deficiencies in EKF such as biased estimation, complexity in calculation and inefficacity in not being able to compute analytical derivatives affect its application in many fields. In this paper, Unscented Kalman Filter (UKF) is employed for estimation of the state variables of the chaotic dynamical system. The chaotic synchronization is implemented by the UKF in the presence of processing noise and measurement noise. The results of the simulation on the Rossler chaotic system by UKF and its comparison with EKF show that the UKF has more accuracy and efficiency than EKF.

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Unscented Kalman filter applied to noisy synchronization of rossler chaotic system

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