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Article

Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter

1
Laboratorio de Ingeniería Mecánica, University of A Coruna, Escuela Politécnica Superior, Mendizábal s/n, 15403 Ferrol, Spain
2
Test Division, Siemens Digital Industries Software, Interleuvenlaan 68, B-3001 Leuven, Belgium
*
Author to whom correspondence should be addressed.
Academic Editor: Stefano Mariani
Sensors 2021, 21(15), 5241; https://doi.org/10.3390/s21155241
Received: 31 May 2021 / Revised: 22 July 2021 / Accepted: 29 July 2021 / Published: 3 August 2021
The aim of this work is to explore the suitability of adaptive methods for state estimators based on multibody dynamics, which present severe non-linearities. The performance of a Kalman filter relies on the knowledge of the noise covariance matrices, which are difficult to obtain. This challenge can be overcome by the use of adaptive techniques. Based on an error-extended Kalman filter with force estimation (errorEKF-FE), the adaptive method known as maximum likelihood is adjusted to fulfill the multibody requirements. This new filter is called adaptive error-extended Kalman filter (AerrorEKF-FE). In order to present a general approach, the method is tested on two different mechanisms in a simulation environment. In addition, different sensor configurations are also studied. Results show that, in spite of the maneuver conditions and initial statistics, the AerrorEKF-FE provides estimations with accuracy and robustness. The AerrorEKF-FE proves that adaptive techniques can be applied to multibody-based state estimators, increasing, therefore, their fields of application. View Full-Text
Keywords: adaptive Kalman filter; multibody dynamics; nonlinear models; virtual sensing; multibody based observers adaptive Kalman filter; multibody dynamics; nonlinear models; virtual sensing; multibody based observers
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MDPI and ACS Style

Rodríguez, A.J.; Sanjurjo, E.; Pastorino, R.; Naya, M.Á. Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter. Sensors 2021, 21, 5241. https://doi.org/10.3390/s21155241

AMA Style

Rodríguez AJ, Sanjurjo E, Pastorino R, Naya MÁ. Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter. Sensors. 2021; 21(15):5241. https://doi.org/10.3390/s21155241

Chicago/Turabian Style

Rodríguez, Antonio J., Emilio Sanjurjo, Roland Pastorino, and Miguel Á. Naya. 2021. "Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter" Sensors 21, no. 15: 5241. https://doi.org/10.3390/s21155241

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