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Event-triggered control of nonlinear networked control systems via a data-based representation.

Xianming Wang¹, Yang Gu², Wen Qin²

¹School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, 211816, China.

ISA Transactions

|April 17, 2026

Summary

This study introduces event-triggered control for nonlinear networked control systems using a data-based approach. The proposed methods reduce data transmission while ensuring system stability.

Keywords:

Event-triggered control Linear matrix inequality Networked control systems

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Area of Science:

Control Engineering
Systems Science
Computer Science

Background:

Networked control systems (NCS) face challenges with communication bandwidth and stability.
Event-triggered control strategies aim to optimize data transmission in NCS.

Purpose of the Study:

To develop novel event-triggered control schemes for nonlinear NCS.
To reduce communication load while maintaining system stability.
To propose both static and dynamic event-triggered mechanisms.

Main Methods:

A data-based representation using second-order Taylor series expansion for controller design.
An improved data-dependent static event-triggered mechanism with a relaxing parameter.
A dynamic event-triggered mechanism for adjustable inter-event intervals.
Linear matrix inequalities (LMIs) to determine control gains and ensure stability.

Main Results:

The proposed static event-triggered mechanism effectively reduces communication transmission.
The dynamic version allows for adjustable inter-event intervals.
Sufficient conditions derived using LMIs guarantee local stability of the closed-loop systems.
Simulations validate the effectiveness of the proposed control schemes.

Conclusions:

The developed data-based event-triggered control strategies are effective for nonlinear NCS.
The proposed mechanisms offer a trade-off between communication reduction and system performance.
The LMI-based approach provides a systematic way to design stable controllers for these systems.