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Recursive filtering for nonlinear systems subject to measurement outliers

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Abstract

In this paper, an innovative recursive filtering algorithm (RFA) is proposed for a class of nonlinear systems (NSs) subject to multiplicative noises (MNs) and measurement outliers (MOs). Initially, the MNs are employed to formulate the random influence on the NSs with the stochastic noises. Next, the outlier phenomenon could occur unpredictably during measurement transmission. Then, a self-adaptive saturation function is introduced to the constructed filter to mitigate the influence of MOs on the filter performance. In this paper, we design a resistant-outlier filter for NSs with MNs and MOs, and the filter gain ensures that the trace of the filtering error covariance matrix is minimized by solving the constructed Riccati-like difference equations. Moreover, the exponential boundedness of the filtering error in the sense of mean square is analyzed. Finally, the feasibility of the proposed RFA is illustrated by a simulation example when the MOs occur.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61873058, 61933007) and in part by Natural Science Foundation of Heilongjiang Province of China (Grant No. ZD2019F001).

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Northeast Petroleum University, Daqing, 163318, China

    Bo Jiang & Hongyu Gao

  2. Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, 163318, China

    Bo Jiang, Fei Han & Hongli Dong

  3. Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Daqing, 163318, China

    Hongyu Gao, Fei Han & Hongli Dong

Authors
  1. Bo Jiang
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  2. Hongyu Gao
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  3. Fei Han
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  4. Hongli Dong
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Correspondence to Hongyu Gao.

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Jiang, B., Gao, H., Han, F. et al. Recursive filtering for nonlinear systems subject to measurement outliers. Sci. China Inf. Sci. 64, 172206 (2021). https://doi.org/10.1007/s11432-020-3135-y

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  • DOI: https://doi.org/10.1007/s11432-020-3135-y

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