Fractional Order Extended Kalman Filter for Attitude Estimation

Sharma, Nimmi; Rufus, Elizabeth; Karar, Vinod; Poddar, Shashi

doi:10.1007/978-3-030-16657-1_77

Cited by 1 publication

(2 citation statements)

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“…The well-known Kalman filter is one of the most popular technique in the field of sensor fusion being employed to compensate the effect of sensor noise [ 106 ]. Applications of fractional-order filters cover mostly areas such as data transmission and networking issues, as well as estimations of state of charge in lithium-ion batteries (largely used in several industrial domains, including automotive industry).…”

Section: Applications Of Fractional-order Filtersmentioning

confidence: 99%

“…The concepts of fractional calculus are extended to these types of filters and the results show that the proposed approach is indeed efficient on systems with non-Gaussian. In [ 106 ] a fractional Kalman filter (FKF) is implemented for attitude estimation of a moving vehicle. The input signals used are taken from a tri-axial MEMS (Microelectromechanical Systems) inertial sensors, i.e., accelerometer, magnetometer and gyroscope.…”

Section: Applications Of Fractional-order Filtersmentioning

confidence: 99%

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A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques

Muresan

Birs

Dulf

et al. 2021

Sensors

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The present manuscript aims at raising awareness of the endless possibilities of fractional calculus applied not only to system identification and control engineering, but also into sensing and filtering domains. The creation of the fractance device has enabled the physical realization of a new array of sensors capable of gathering more information. The same fractional-order electronic component has led to the possibility of exploring analog filtering techniques from a practical perspective, enlarging the horizon to a wider frequency range, with increased robustness to component variation, stability and noise reduction. Furthermore, fractional-order digital filters have developed to provide an alternative solution to higher-order integer-order filters, with increased design flexibility and better performance. The present study is a comprehensive review of the latest advances in fractional-order sensors and filters, with a focus on design methodologies and their real-life applicability reported in the last decade. The potential enhancements brought by the use of fractional calculus have been exploited as well in sensing and filtering techniques. Several extensions of the classical sensing and filtering methods have been proposed to date. The basics of fractional-order filters are reviewed, with a focus on the popular fractional-order Kalman filter, as well as those related to sensing. A detailed presentation of fractional-order filters is included in applications such as data transmission and networking, electrical and chemical engineering, biomedicine and various industrial fields.

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Section: Applications Of Fractional-order Filtersmentioning

confidence: 99%

Section: Applications Of Fractional-order Filtersmentioning

confidence: 99%