Skip to search boxSkip to navigationSkip to main content

Robust fault detection for a class of uncertain switched nonlinear systems via the state updating approach

  • Weiming Xiang(corresponding author)
    ,
  • Jian Xiao
    ,
  • Muhammad Naveed Iqbal
*Corresponding author for this work
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

In this paper, the fault detection problem for a class of state-dependent switched nonlinear systems with linear switching surface is addressed. The investigation of fault detection problem includes two parts: design sub-filters for each subsystem, and determine a proper update of estimated state. A fault detection filter is proposed incorporating the update of estimated state at switching instants and the multiple Lyapunov function approach is employed in the design process to reduce the conservativeness. It should be pointed out that the state update relation is derived based upon multiple Lyapunov functions and also on the information of switching surface. In the end, a special case in which the state space is divided into several polyhedral cells is discussed. A numerical example is given to illustrate the effectiveness of proposed results.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 132-146 (15 pages)

Journal (Volume, Issue Number)

Nonlinear Analysis: Hybrid Systems (Volume 12, Issue 1)

Publication milestones

  • Published - 05/2014

Publication status

Published - 05/2014

ISSN

1751-570X

Publication IDs

  • Scopus: 84892538586

Publication metrics

Metrics

Scopus
citations
SciVal
FWCI
3.16
SciVal
Author count
3
SciVal
citations
21
SciVal
Paper percentile
82
Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
1

PlumX, opens in new tab

Citation count
28
Captures
16

Funding Details

This work was supported by the National Natural Science Foundation of China (No. 51177137 , No. 61134001 ).
FunderFunding numbers
NSFC
51177137, 61134001