NONLINEAR KALMAN FILTER DESIGN FOR THE FRACTIONAL ORDER NONLINEAR STOCHASTIC SYSTEMS WITH STUDENT’S T MEASUREMENT NOISE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

TORABI HAMED; PARIZ NASER; KARIMPOUR ALI

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Control Year:2017 | Volume:10 | Issue:4 Page(s): 55-68

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

734

Download:

Cites:

Information Journal Paper

Title

NONLINEAR KALMAN FILTER DESIGN FOR THE FRACTIONAL ORDER NONLINEAR STOCHASTIC SYSTEMS WITH STUDENT’S T MEASUREMENT NOISE

Author(s)

TORABI HAMED | PARIZ NASER | KARIMPOUR ALI | Issue Writer Certificate

Keywords

FRACTIONAL ORDER NONLINEAR SYSTEMSQ2

STUDENT'S T DISTRIBUTIONQ2

STATE ESTIMATION AND KALMAN FILTERINGQ2

VARIATIONAL BAYESIAN INFERENCEQ2

Abstract

This paper presents a fractional order Kalman filter for the stochastic nonlinear fractional order systems where the measurement noise is assumed to haveStudent’s t distribution.Modeling of the system and measurement noises in the state space representation, for target tracking problems, often carried out by additive Gaussian noise, but Gaussian distribution is not enough robust to the outliers, in the other words, Gaussian distribution has much less robustness againstoutliers than STUDENT'S T DISTRIBUTION, so if the tracking system affected by noises that have outliers, modeling of theses noises by the Gaussian distribution, may cause large estimation error or divergence of filter in the filtering and estimation problems. In this paper, after defining the stochastic fractional order systems, by comparing the performance of two Student’s t and Gaussian distributions in the modeling of noises that have outliers, try to design a nonlinear Kalman filter for fractional order systems using VARIATIONAL BAYESIAN INFERENCE method. Finally by comparing the simulation results of proposed filter in this paper and a fractional extended Kalman filer in the presence of Gaussian and Student’s tnoises, the effectiveness of the proposed filter in estimation of states of the fractional order systems is demonestrated.

Cites

No record.

References

No record.

Cite

APA: Copy

TORABI, HAMED, PARIZ, NASER, & KARIMPOUR, ALI. (2017). NONLINEAR KALMAN FILTER DESIGN FOR THE FRACTIONAL ORDER NONLINEAR STOCHASTIC SYSTEMS WITH STUDENT’S T MEASUREMENT NOISE. JOURNAL OF CONTROL, 10(4 ), 55-68. SID. https://sid.ir/paper/120748/en

Vancouver: Copy

TORABI HAMED, PARIZ NASER, KARIMPOUR ALI. NONLINEAR KALMAN FILTER DESIGN FOR THE FRACTIONAL ORDER NONLINEAR STOCHASTIC SYSTEMS WITH STUDENT’S T MEASUREMENT NOISE. JOURNAL OF CONTROL[Internet]. 2017;10(4 ):55-68. Available from: https://sid.ir/paper/120748/en

IEEE: Copy

HAMED TORABI, NASER PARIZ, and ALI KARIMPOUR, “NONLINEAR KALMAN FILTER DESIGN FOR THE FRACTIONAL ORDER NONLINEAR STOCHASTIC SYSTEMS WITH STUDENT’S T MEASUREMENT NOISE,” JOURNAL OF CONTROL, vol. 10, no. 4 , pp. 55–68, 2017, [Online]. Available: https://sid.ir/paper/120748/en

Related Journal Papers