Distributed input and state estimation for linear discrete-time systems - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2012

Distributed input and state estimation for linear discrete-time systems

Alireza Esna Ashari
  • Function : Author
  • PersonId : 929303
Alain Kibangou
Federica Garin

Abstract

This paper provides a solution for distributed input and state estimation, simultaneously. A set of sensors with the capability of exchanging information is used to collect data from a discrete-time system. Various distributed implementations of Kalman filter have already been developed to track system states in such a setup when the system is subject to noise with known stochastic properties. However, practical systems might be subject to unknown input signals as well as stochastic noise, which leads to a biased state estimation. This study proposes new distributed filter that calculate state estimation in the presence of unknown inputs. In addition, the filter provides an estimation of the unknown inputs. A consensus-based distributed estimation algorithm is proposed in this paper. The algorithm gives an optimal unbiased minimum variance estimation if perfect consensus is achieved. Simulation results show the efficiency of the method.
No file

Dates and versions

hal-00725518 , version 1 (27-08-2012)

Identifiers

Cite

Alireza Esna Ashari, Alain Kibangou, Federica Garin. Distributed input and state estimation for linear discrete-time systems. CDC 2012 - 51st IEEE Conference on Decision and Control, Dec 2012, Maui (Hawaii), United States. pp.782-787, ⟨10.1109/CDC.2012.6426366⟩. ⟨hal-00725518⟩
221 View
1 Download

Altmetric

Share

Gmail Facebook X LinkedIn More