State estimation and fault detection of fractional order nonlinear systems
Document Type
Conference Proceeding
Publication Date
1-22-2019
Publication Title
Midwest Symposium on Circuits and Systems
Volume
2018-August
First Page
1086
Keywords
Disturbance decoupling, Extended unknown input observer, Fault detection, Fractional Kalman filter, Fractional order systems, State estimation
Last Page
1089
Abstract
This study is devoted to robust state estimation and fault detection for nonlinear discrete fractional order systems using a novel fractional order filter algorithm. While noise and disturbance effects can suppress or even disturb the state estimation, the proposed filter can preciously estimate the states of nonlinear fractional order systems. Disturbance decoupling approach is the fundamental basis for the proposed filter to make it robust against unknown inputs. Simulation results illustrate the advantages of the proposed filter for state estimation and fault detection of nonlinear fractional order systems in the presence of both noise and disturbance.
DOI
10.1109/MWSCAS.2018.8623870
ISSN
15483746
ISBN
9781538673928
Recommended Citation
Tabatabaei, Mahmood; Zarei, Jafar; Razavi-Far, Roozbeh; and Saif, Mehrdad. (2019). State estimation and fault detection of fractional order nonlinear systems. Midwest Symposium on Circuits and Systems, 2018-August, 1086-1089.
https://scholar.uwindsor.ca/electricalengpub/131