JOURNAL ARTICLE

Event-triggered reliable dissipative filtering for the delay nonlinear system under networked systems with the sensor fault

Muhammad Shamrooz AslamZiran Chen

Year: 2018 Journal:   International Journal of Control Vol: 93 (3)Pages: 640-654   Publisher: Taylor & Francis

Abstract

This paper investigates the problem of fuzzy filter design for a class of delayed nonlinear system under random sensor faults with an event-triggered (ET) mechanism. (1) To estimate the dynamics of nonlinear plant, a T–S fuzzy model is manipulated. Random variables are disclosed to express the sensor fault. (2) To take some advantages over existing one, a variable ET mechanism is offered in networked systems (NSs). Under the ET mechanism, sensor data are released only when the plant's measurement (sampled) violate specific threshold of the event condition. (3) Another purpose of this article is to design filters involving system state delays. Then, by using a novel fuzzy Lyapunov–Krasovskii function approach with free weighting matrix technique, dissipative filter design of ET delay networked control systems is proposed. We consider both the sensor fault and ET scheme simultaneously. The simulation example is given to demonstrate the effectiveness of design method.

Keywords:
Control theory (sociology) Dissipative system Filter (signal processing) Nonlinear system Fuzzy logic Weighting Fault (geology) Fault detection and isolation Fuzzy control system Event (particle physics) Control system Lyapunov function Computer science Control engineering Engineering Control (management) Actuator Artificial intelligence

Metrics

10
Cited By
0.76
FWCI (Field Weighted Citation Impact)
31
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Stability and Control of Uncertain Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Neural Networks Stability and Synchronization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Fault Detection and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering

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