Remote State Estimation with Data-driven Communication and Guaranteed Stability

Publication Date:
Publication Date
6 September 2018

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This paper deals with the problem of remote state estimation with limited communication resources. We propose an online data-driven communication scheme based on cumulative innovation and derive the corresponding minimum mean square error (MMSE) estimator. The communication scheme allows to achieve a trade-off between communication costs and estimation performance. The remote estimator can improve the estimation performance based on the fact that no transmission of data indicates a small cumulative innovation. Further, it is proved that the estimator has guaranteed stability-the expected norm of the mean square error (MSE) matrix is bounded and an upper bound is given. We also derive the conditional probability of a future transmission. A simulation example is provided to illustrate the effectiveness of the proposed method.


2018 21st International Conference on Information Fusion (FUSION), July 2018, doi: 10.23919/ICIF.2018.8455453