Fractional order unknown input filter design for fault detection of discrete linear systems

Document Type

Conference Proceeding

Publication Date

12-15-2017

Publication Title

Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

Volume

2017-January

First Page

4333

Keywords

fault detection, fractional Kalman filter, fractional order systems, unknown input filter

Last Page

4338

Abstract

This work deals with the problem of filter design for disturbance decoupling in discrete-time linear fractional order systems (FOS) under noisy environments. To this end, Fractional Unknown Input Filter (FUIF) is developed based on Fractional Kalman Filter (FKF) framework. Accordingly, the proposed structure can result in robustness against unknown inputs (UIs) in noisy environments. This algorithm can be used for robust fault detection since the disturbance is decoupled from state estimation error. The designed filter is applied to a fractional order (FO) model of an ultra-capacitor (UC), under noisy condition, for the state estimation and fault detection purposes. Simulation results illustrate the benefits of the proposed approach.

DOI

10.1109/IECON.2017.8216745

ISBN

9781538611272

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