Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/de-gruyter/finite-length-triple-estimation-algorithm-and-its-application-to-f600nDvLMR
References (20)
-
B. West (2021)
Fractional Calculus and the Future of ScienceEntropy, 23
-
D. Sierociuk, M. Macias (2021)
Triple Estimation of Fractional Variable Order, Parameters, and State Variables Based on the Unscented Fractional Order Kalman FilterSensors (Basel, Switzerland), 21
-
G. Anastassiou (2021)
Generalized Fractional Calculus - New Advancements and Applications, 305
-
A. Dzieliński, D. Sierociuk, G. Sarwas (2010)
Some applications of fractional order calculusBulletin of The Polish Academy of Sciences-technical Sciences, 58
-
C. Monje, Y. Chen, B. Vinagre, Dingyu Xue, V. Feliu (2010)
Fractional-order Systems and Controls -
S. Haykin (2001)
Kalman Filtering and Neural Networks -
D. Sierociuk, Pawel Ziubinski (2014)
Fractional Order Estimation Schemes for Fractional and Integer Order Systems with Constant and Variable Fractional Order Colored NoiseCircuits, Systems, and Signal Processing, 33
-
H. Sheng, Y. Chen, T. Qiu (2012)
Fractional Processes and Fractional-Order Signal Processing -
V. Tarasov (2018)
Generalized Memory: Fractional Calculus ApproachFractal and Fractional
-
D. Sierociuk, W. Malesza (2017)
Fractional variable order discrete-time systems, their solutions and propertiesInternational Journal of Systems Science, 48
-
Sreeja S (2015)
Precision Munition Guidance and Moving Target Position Estimation -
M. Ortigueira, J. Machado, Juan Trujillo, B. Vinagre (2011)
Fractional signals and systemsSignal Process., 91
-
M. Macias, D. Sierociuk, W. Malesza (2022)
MEMS Accelerometer Noises Analysis Based on Triple Estimation Fractional Order AlgorithmSensors (Basel, Switzerland), 22
-
Xingling Shao, Haonan Si, Wendong Zhang (2020)
Fuzzy wavelet neural control with improved prescribed performance for MEMS gyroscope subject to input quantizationFuzzy Sets Syst., 411
-
D. Sierociuk, A. Dzieliński, G. Sarwas, I. Petráš, I. Podlubny, T. Skovranek (2013)
Modelling heat transfer in heterogeneous media using fractional calculusPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371
-
C. Muresan, I. Birs, E. Dulf, D. Copot, L. Miclea (2021)
A Review of Recent Advances in Fractional-Order Sensing and Filtering TechniquesSensors (Basel, Switzerland), 21
-
M. Ortigueira, Duarte Valério (2020)
Fractional Signals and Systems -
D. Sierociuk, W. Malesza, M. Macias (2015)
On the Recursive Fractional Variable-Order Derivative: Equivalent Switching Strategy, Duality, and Analog ModelingCircuits, Systems, and Signal Processing, 34
-
D. Sierociuk, I. Tejado, B. Vinagre (2011)
Improved fractional Kalman filter and its application to estimation over lossy networksSignal Process., 91
-
D. Sierociuk, W. Malesza, M. Macias (2013)
Derivation, interpretation, and analog modelling of fractional variable order derivative definitionarXiv: Dynamical Systems
- Publisher
- de Gruyter
- Copyright
- © 2023 Michal Macias et al., published by Sciendo
- ISSN
- 1898-4088
- eISSN
- 2300-5319
- DOI
- 10.2478/ama-2023-0025
- Publisher site
- See Article on Publisher Site
Abstract
AbstractThe noises associated with MEMS measurements can significantly impact their accuracy. The noises characterised by random walk and bias instability errors strictly depend on temperature effects that are difficult to specify during direct measurements. Therefore, the paper aims to estimate the fractional noise dynamics of the stationary MEMS gyroscope based on finite length triple estimation algorithm (FLTEA). The paper deals with the state, order and parameter estimation of fractional order noises originating from the MEMS gyroscope, being part of the popular Inertial Measurement Unit denoted as SparkFun MPU9250. The noise measurements from x, y and z gyroscope axes are identified using a modified triple estimation algorithm (TEA) with finite approximation length. The TEA allows a simultaneous estimation of the state, order and parameter of fractional order systems. Moreover, as it is well-known that the number of samples in fractional difference approximations plays a key role, we try to show the influence of applying the TEA with various approximation length constraints on final estimation results. The validation of finite length TEA in the noise estimation process coming from MEMS gyroscope has been conducted for implementation length reduction achieving 50% of samples needed to estimate the noise with no implementation losses. Additionally, the capabilities of modified TEA in the analysis of fractional constant and variable order systems are confirmed in several numerical examples.
Journal
Acta Mechanica et Automatica – de Gruyter
Published: Jun 1, 2023
Keywords: fractional calculus; fractional Kalman filter; estimation of fractional order systems; fractional order noise