Continuous-Time Estimation Filtering with Incorporation of Temporary Model Uncertainty
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.
KeywordsEstimation filtering Finite memory structure filter Infinite memory structure filter Uncertain system Detection rule
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).
- 8.Kim, P.S., Lee, E.H., Jang, M.S., Kang, S.Y.: A finite memory structure filtering for indoor positioning in wireless sensor networks with measurement delay. Int. J. Distrib. Sens. Netw. 13(1), 1–8 (2017)Google Scholar
- 9.Kim, P.S.: A design of finite memory residual generation filter for sensor fault detection. Measur. Sci. Rev. 17(2), 75–81 (2017)Google Scholar
- 11.Kim, P.S.: Two-stage estimation filtering for temporarily uncertain systems. In: Park, J.J.(Jong Hyuk), Jin, H., Jeong, Y.S., Khan, M. (eds.) Advanced Multimedia and Ubiquitous Engineering. LNEE, vol. 393, pp. 303–309. Springer, Singapore (2016). https://doi.org/10.1007/978-981-10-1536-6_40CrossRefGoogle Scholar