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Unbiased FIR Filtering with Incomplete Measurement Information

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  • Control Theory and Applications
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Abstract

This paper proposes an unbiased filter with finite impulse response (FIR) structure for linear discrete time systems in state space form with incomplete measurement information. The measurements are transmitted from the plant to the FIR filter imperfectly due to random packet loss or sensor faults. The Bernoulli random process is used to describe the missing measurement details, and the missing data is replaced with recently transmitted data on the missing horizon. The missing horizon can hold the assumption for finite measurement of the FIR filter. Two examples are provided to demonstrate the proposed unbiased FIR (UFIR) filter robustness against temporary model uncertainty and consecutive missing measurement data compared with existing filters considering missing measurement.

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Authors and Affiliations

  1. Defence Agency for Technology and Quality, IT Venture Town Complex 5F, 35, Techno-9 ro, Yuseong-gu, Daejeon, 34027, Korea

    Dong Ki Ryu

  2. School of Electrical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Korea

    Chang Joo Lee, Sang Kyoo Park & Myo Taeg Lim

Authors
  1. Dong Ki Ryu
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  2. Chang Joo Lee
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  3. Sang Kyoo Park
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  4. Myo Taeg Lim
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Corresponding authors

Correspondence to Chang Joo Lee or Myo Taeg Lim.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Ding Zhai under the direction of Editor Guang-Hong Yang. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant No. NRF-2016R1D1A1B01016071).

Dong Ki Ryu received his B.S. and M.S. degrees in the School of Electronic Engineering from Kyungbook National University, Daegu, Korea, in 1991 and 1993, respectively. Since 2009, he has been a Ph.D. candidate in the School of Mechatronics Engineering, Korea University. His current research interests in robust control, fuzzy control, guidance, navigation and control of missile systems.

Chang Joo Lee received his B.S. degree in the School of Electronic Engineering from Soongsil University, Seoul, Korea in 2012. Since 2012, he has been a Ph.D. candidate in the School of Electrical Engineering, Korea University. His current research interests include fuzzy systems, neural networks, robust control, FIR filters, finite memory controls, nonlinear systems, and advanced driver assistance systems.

Sang Kyoo Park received his B.S. degree in the School of Electrical Engineering from Korea University, Seoul, Korea in 2016. Since 2016, he has been a Ph.D. candidate in the School of Electrical Engineering, Korea University. His current research interests include deep learning, computer vision, sensor fusion and advanced driver assistance systems.

Myo Taeg Lim received his B.S. and M.S. degrees in Electrical Engineering from Korea University, Seoul, Korea, in 1985 and 1987, respectively. He also received M.S. and Ph.D. degrees in Electrical Engineering from Rutgers University, NJ, USA, in 1990 and 1994, respectively. He was a Senior Research Engineer with the Samsung Advanced Institute of Technology and a Professor in the Department of Control and Instrumentation, National Changwon University, Korea. Since 1996, he has been a Professor in the School of Electrical Engineering at Korea University. His research interests include optimal and robust control, vision based motion control, and intelligent vehicle systems. He is the author or coauthor of more than 100 journal papers and two books (Optimal Control of Singularly Perturbed Linear Systems and Application: High-Accuracy Techniques, Control Engineering Series, Marcel Dekker, New York, 2001; Optimal Control: Weakly Coupled Systems and Applications, Automation and Control Engineering Series, CRC Press, New York, 2009). Prof. Lim currently serves as an Editor for International Journal of Control, Automation, and Systems. He is a Fellow of the Institute of Control, Robotics and System, and a member of the IEEE and Korean Institute of Electrical Engineers.

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Ryu, D.K., Lee, C.J., Park, S.K. et al. Unbiased FIR Filtering with Incomplete Measurement Information. Int. J. Control Autom. Syst. 18, 330–338 (2020). https://doi.org/10.1007/s12555-018-0316-2

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  • DOI: https://doi.org/10.1007/s12555-018-0316-2

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