Quantized Dissipative Uncertain Model for Fractional T_S Fuzzy systems with Time_Varying Delays Under Networked Control System

TL;DR

This paper develops a quantized dissipative uncertain model for delayed fractional T_S fuzzy systems in networked control, integrating dissipativity analysis with event-triggered schemes to improve resource efficiency and stability.

Contribution

It introduces a novel event-triggered scheme with logarithmic quantization for fractional fuzzy systems, unifying dissipativity, H-infinity, and passivity analyses under network constraints.

Findings

Proposes an effective event-triggered scheme with logarithmic quantization.

Provides stability conditions via linear matrix inequalities.

Demonstrates the approach's effectiveness on a truck-trailer model.

Abstract

This paper addressed with the quantized dissipative uncertain problem for delayed fractional T_S Fuzzy system for event_triggered networked systems (E_NS), where the extended dissipativity analysis combines the H infinity, dissipativity, L2 and L infinity and passivity performance in a unified frame. To attain the high efficiency for available channel resources, measurement size decrease mechanism and event_triggered scheme (ETS) are proposed. Firstly, we present the ETS in which signal is transmitted through the channel with logical function then logarithmic quantization methodology is implemented for size reduction. Then, we transfer the original delayed fractional T_S fuzzy systems with the effect of quantization under ETS as induced communications delays. Furthermore, by employing the associative Lyapunov functional method in terms of linear matrix inequalities, adequate conditions for asymptotical stability is given. Moreover, we also construct the design fuzzy model for state space filtering system. At last, a truck_trailer model is given to show the effectiveness of the proposed strategy.