UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems

Li, P; Boem, F; Pin, G; (2020) Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems. European Journal of Control 10.1016/j.ejcon.2020.05.011. (In press).

[img] Text
kernel_NL_fdi_22_04_2020final.pdf - Accepted version
Access restricted to UCL open access staff until 30 May 2021.

Download (1MB)

Abstract

The present work proposes a fast-convergent fault detection and isolation (FDI) scheme for linear systems affected by model uncertainties, such as unknown inputs or unbounded nonlinearities. The finite-time convergence is attained by transforming the I/O signals through Volterra operators with suitably designed kernel functions. A novel feature of the proposed approach is the exploitation of a system decomposition that allows removing the effect of intractable uncertainties while recasting the system dynamics in a form applicable for Volterra operators to achieve non-asymptotic estimation. Remarkably, the proposed approach can reconstruct the state variables of the system in an arbitrarily short time and the fault can be diagnosed efficiently by imposing detection and isolation thresholds on transformed signals. The detectability and isolability of the fault are also characterized. The proposed FDI scheme is applied in simulation to a web process system to diagnose the presence of actuator faults. Simulation results confirm the effectiveness of the proposed scheme in two scenarios with nonlinear uncertainties. Furthermore, comparisons are made between the proposed method and a Sliding Mode Control (SMC) method in terms of estimation performance and computational complexity.

Type: Article
Title: Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems
DOI: 10.1016/j.ejcon.2020.05.011
Publisher version: https://doi.org/10.1016/j.ejcon.2020.05.011
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Non-asymptotic estimation, Volterra operator, Fault detection and isolation, Nonlinear uncertainty
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10104205
Downloads since deposit
1Download
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item