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Application of Unscented Kalman Filter for Parameter Estimation of Nonlinear Systems

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Advances in Information Communication Technology and Computing

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 135))

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Abstract

Sometimes the parameters of a system dynamics are not exactly known while these are required to set the control law and update the existing control scheme. This becomes much difficult when the dynamics of the system is nonlinear. Thus, this paper deals with the estimation of the parameters of a nonlinear system using unscented Kalman filter (UKF). The UKF handles the nonlinear dynamics without linearization and approximation during the estimation and hence estimates the parameters as well as states perfectly. A well-known example of nonlinear dynamics, Van Der Pol oscillator system, has been used to illustrate the parameter estimation. The simulation of the Van Der Pol oscillator has been done first to generate the measurements, and then, the state and measurement model of the system have been setup which further have been used during the estimation.

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Acknowledgements

This research work is funded from the Collaborative Research Scheme (CRS) of RTU (ATU) under TEQIP-III.

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Correspondence to Ganesh P. Prajapat .

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Solanki, U., Prajapat, G.P., Chhimpa, M. (2021). Application of Unscented Kalman Filter for Parameter Estimation of Nonlinear Systems. In: Goar, V., Kuri, M., Kumar, R., Senjyu, T. (eds) Advances in Information Communication Technology and Computing. Lecture Notes in Networks and Systems, vol 135. Springer, Singapore. https://doi.org/10.1007/978-981-15-5421-6_27

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  • DOI: https://doi.org/10.1007/978-981-15-5421-6_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5420-9

  • Online ISBN: 978-981-15-5421-6

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