A Luenberger-like State Estimation with False Data Injection on Input and Model Mismatch: LMI Approach

EasyChair Preprint no. 8398

Abstract

This paper investigates a proportional-integral Luenberger-like state estimation for continous linear systems under disturbed inputs or false data inhection attacks on inputs and model mismatch. A general design algorithm is proposed to estimate the states of a linear system in the presence of model mismatch, external disturbance, and disturbed inputs / false data injection. In reality, the absence of the conditions is very rare, therefore it is required to develop a method for designing robust observers in presence of uncertainties, external disturbances, and disturbed inputs.  Lyapunov method and LMI theory have been used to obtain the gains of the Proportional-Integral Observer (PIO). The stability of the proposed PI observer is proved and with a numerical example, its efficiencies have been shown under different cases including model mismatch, disturbances, and attacks. The results illustrate that the proposed algorithm can estimate the state of a system according to defined conditions.  This paper investigates a proportional-integral Luenberger-like state estimation for continous linear systems under disturbed inputs or false data inhection attacks on inputs and model mismatch. A general design algorithm is proposed to estimate the states of a linear system in the presence of model mismatch, external disturbance, and disturbed inputs / false data injection. In reality, the absence of the conditions is very rare, therefore it is required to develop a method for designing robust observers in presence of uncertainties, external disturbances, and disturbed inputs.  Lyapunov method and LMI theory have been used to obtain the gains of the Proportional-Integral Observer (PIO). The stability of the proposed PI observer is proved and with a numerical example, its efficiencies have been shown under different cases including model mismatch, disturbances, and attacks.

Keyphrases: False Data Injection., Luenberger-like observer, model mismatch

@Booklet{EasyChair:8398,
  author = {Mohammad Tahmasbi and Alireza Farbod and Ahmadreza Fakhari},
  title = {A Luenberger-like State Estimation with False Data Injection on Input and Model Mismatch: LMI Approach},
  howpublished = {EasyChair Preprint no. 8398},

  year = {EasyChair, 2022}}