Lee, JG and Shim, H (2019) *A Distributed Algorithm That Finds Almost Best Possible Estimate under Non-Vanishing and Time-Varying Measurement Noise.* IEEE Control Systems Letters, 4. pp. 229-234.

## Abstract

In this letter, we review an existing distributed least-squares solver and share some new insights on it. Then, by the observation that an estimation of a constant vector under output noise can be translated into finding the least-squares solution, we present an algorithm for distributed estimation of the state of linear time-invariant systems under measurement noise. The proposed algorithm consists of a network of local observers, where each of them utilizes local measurements and information transmitted from the neighbors. It is proven that even under non-vanishing and time-varying measurement noise, we could obtain an almost best possible estimate with arbitrary precision. Some discussions regarding the plug-and-play operation are also given.

Item Type: | Article |
---|---|

Subjects: | UNSPECIFIED |

Divisions: | Div F > Control |

Depositing User: | Cron Job |

Date Deposited: | 15 Oct 2020 03:36 |

Last Modified: | 01 Jul 2021 09:54 |

DOI: | 10.1109/LCSYS.2019.2923475 |