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Stochastically resilient extended Kalman filtering for discrete-time nonlinear systems with sensor failures

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  • Xin Wang
  • Edwin E. Yaz

Abstract

Missing sensor data is a common problem, which severely influences the overall performance of modern data-intensive control and computing applications. In order to address this important issue, a novel resilient extended Kalman filter is proposed for discrete-time nonlinear stochastic systems with sensor failures and random observer gain perturbations. The failure mechanisms of multiple sensors are assumed to be independent of each other with different failure rates. The locally unbiased robust minimum mean square filter is designed for state estimation under these conditions. The performance of the proposed estimation method is verified by means of numerical Monte Carlo simulation of two different nonlinear stochastic systems, involving a sinusoidal system and a Lorenz oscillator system.

Suggested Citation

  • Xin Wang & Edwin E. Yaz, 2014. "Stochastically resilient extended Kalman filtering for discrete-time nonlinear systems with sensor failures," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(7), pages 1393-1401, July.
    • Handle: RePEc:taf:tsysxx:v:45:y:2014:i:7:p:1393-1401
    DOI: 10.1080/00207721.2013.879257
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    Cited by:

    1. Joon B. Park & Xin Wang, 2018. "Sensorless Direct Torque Control of Surface-Mounted Permanent Magnet Synchronous Motors with Nonlinear Kalman Filtering," Energies, MDPI, vol. 11(4), pages 1-19, April.
    2. Manman Luo & Baibin Yang & Zhaolei Yan & Yuwen Shen & Manfeng Hu, 2024. "The Dynamic Event-Based Non-Fragile H ∞ State Estimation for Discrete Nonlinear Systems with Dynamical Bias and Fading Measurement," Mathematics, MDPI, vol. 12(18), pages 1-16, September.
    3. Tao Liu & Qiaoling Tong & Qiao Zhang & Qidong Li & Linkai Li & Zhaoxuan Wu, 2018. "A Method to Improve the Response of a Speed Loop by Using a Reduced-Order Extended Kalman Filter," Energies, MDPI, vol. 11(11), pages 1-16, October.

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