Hybrid-triggered H∞ Fault Detection for Distributed Time-delay Systems with Communication Quantization Based on T-S Fuzzy Model

Authors

  • Ying Zhang

DOI:

https://doi.org/10.54097/ajst.v1i3.401

Keywords:

H∞ performance, Fault detection, Hybrid trigger mechanism, Networked system, T-S fuzzy model, Communication quantification.

Abstract

In the network environment, the time-triggered mechanism wastes limited bandwidth resources due to the transmission of all sampled data to the network. The event-triggered mechanism may increase system errors due to ignoring factors such as changes in network utilization. In order to reduce the design conservatism, this paper studies the design of a hybrid-triggered H∞ fault detection filter for a class of nonlinear networked control systems described by Takagi-Sugeno (T-S) fuzzy model, and applies quantization techniques in the communication channel. Using the Lyapunov-Krasovskii functional and integral inequality methods, new results on the stability and H∞ performance of fuzzy fault detection systems are presented. In particular, the designed fault detection filter has a specific H∞ noise attenuation level γ. The final simulation results verify the effectiveness of the design.

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References

Zhong Z, Fu S, Hayat T, Alsaadi F. Decentralized piecewise H∞ fuzzy filtering design for discrete-time large-scale nonlinear systems with time-varying delay. J Frankl Inst. 2015;352(9):3782-3807.

Shen H, Li F, Yan H, Karimi HR, Lam H-K. Finite-time event-triggered H∞ control for T-S fuzzy Markov jump systems. IEEE Trans Fuzzy Syst. 2018;26(5):3122-3135.

Li Y, Tong S, Liu L, Feng G. Adaptive output-feedback control design with prescribed performance for switched nonlinear systems. Automatica. 2017;80:225-231.

Chibani A, Chadli M, Shi P, Braiek NB. Fuzzy fault detection filter design for T-S fuzzy systems in finite frequency domain. IEEE Trans Fuzzy Syst. 2017;25(5):1051-1061.

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Published

26-05-2022

Issue

Section

Articles

How to Cite

Zhang, Y. (2022). Hybrid-triggered H∞ Fault Detection for Distributed Time-delay Systems with Communication Quantization Based on T-S Fuzzy Model. Academic Journal of Science and Technology, 1(3), 20-23. https://doi.org/10.54097/ajst.v1i3.401