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Updated: May 16, 2025

Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Finite frequency distributed fault detection in sensor networks with memory event-triggered scheme and deception

Peng Cheng¹, Chenxiao Cai², PooGyeon Park³

¹School of Automation, Nanjing University of Science and Technology, Nanjing, China; Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macau.

ISA Transactions

|April 5, 2025

Summary

This study introduces a finite frequency distributed fault detection filter for nonlinear switched systems, improving detection speed and accuracy under network constraints and deception attacks.

Keywords:

Distributed fault detection Finite frequency Nonlinear systems Switched systems

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Area of Science:

Control Systems Engineering
Networked Systems Analysis
Nonlinear System Dynamics

Background:

Distributed fault detection (FD) is crucial for nonlinear switched systems (SSs) with time-varying delays in sensor networks.
Network bandwidth limitations and deception attacks pose significant challenges to traditional FD methods.

Purpose of the Study:

To develop a finite frequency distributed fault detection filter (FDF) for discrete-time nonlinear SSs with time-varying delays.
To address challenges posed by sensor networks, distributed memory event-triggered schemes (METS), and malicious deception attacks.

Main Methods:

Utilizing the sojourn probability method to describe the switching mechanism of SSs.
Employing a distributed memory event-triggered scheme (METS) to reduce network load.
Designing a finite frequency distributed FD filter (FDF) for each sensor node, considering METS and deception attacks.
Deriving existence conditions for the FDF using linear matrix inequalities (LMIs).

Main Results:

The proposed FDF ensures mean-square stability of the augmented filter system via Lyapunov stability analysis.
The filter meets specified full-frequency H∞ and finite-frequency H- level bounds.
Comparative simulations confirm superior performance of the finite-frequency distributed FDF over existing full-frequency solutions.

Conclusions:

The developed finite frequency distributed FDF effectively detects unknown faults in nonlinear SSs within sensor networks.
The FDF offers enhanced speed and accuracy compared to existing methods, particularly under network constraints and adversarial conditions.