Abstract
In this paper, a continuous-time estimation filtering is developed to incorporate temporary model uncertainty. The infinite memory structure (IMS) estimation filter is applied for the certain system and the finite memory structure (FMS) estimation filter is applied for the temporarily uncertain system, selectively. Therefore, one of two filtered estimates is selected as the valid estimate according to presence or absence of uncertainty. In order to indicate presence or absence of uncertainty and select the valid filtered estimate from IMS and FMS filtered estimates, two test variables and detection rule are defined. Computer simulations show that the proposed continuous-time estimation filter works well for both certain system and temporarily uncertain system.
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Acknowledgement
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03033024).
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Kim, P.S. (2018). Continuous-Time Estimation Filtering with Incorporation of Temporary Model Uncertainty. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_159
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DOI: https://doi.org/10.1007/978-981-10-7605-3_159
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