Event-Triggered Memory Control for Interval Type-2 Fuzzy Heterogeneous Multi-Agent Systems

TL;DR

This paper presents a novel memory-based event-triggered control scheme for heterogeneous multi-agent systems modeled with interval type-2 fuzzy logic, reducing communication and conservatism while ensuring stability and performance.

Contribution

It introduces a distributed dynamic event-triggered mechanism with a dynamic threshold for resource-efficient control of complex fuzzy multi-agent systems, along with a non-PDC controller design method.

Findings

Reduces unnecessary communication in MASs

Ensures asymptotic stability of the closed-loop system

Improves control performance through simulation validation

Abstract

This study explores the design of a memory-based dynamic event-triggered mechanisms (DETM) scheme for heterogeneous multi-agent systems (MASs) characterized by interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy models. To address the complex nonlinear uncertainties inherent in such systems, discrete IT2 T-S fuzzy models are employed to accurately capture system dynamics. In response to the limitations on communication resources and computational capabilities within MASs, this research introduces a distributed DETM approach based on a dynamic threshold method. This mechanism effectively minimizes unnecessary communication while maintaining robust performance. The proposed memory-based control strategy not only reduces the conservatism associated with controller design conditions but also enhances overall controller performance. Furthermore, leveraging a non-parallel distributed compensation (non-PDC) strategy, a novel derivation method is developed for controller design conditions that significantly decreases conservatism. This leads to sufficient conditions for the asymptotic stability of the closed-loop system. The designed distributed event-triggered controllers improve the overall performance of MASs, as evidenced by numerical simulations that validate the effectiveness of the proposed approach. Overall, these findings advance the state-of-the-art in control strategies for heterogeneous MASs, offering practical solutions for real-world applications where resource constraints are critical.