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Zhang, X.M., Han, Q.L., Ge, X.H., Ding, D.R., Ning, B.D. and Zhang, B.L. (2025) An Overview of Recent Advances in Event-Triggered Control. Science China Information Sciences, 68, Article No. 161201.
https://doi.org/10.1007/s11432-024-4437-9

has been cited by the following article:

• TITLE: Co-Design of Periodic Event-Triggered Quantization Control for Linear Systems with Packet Losses

  AUTHORS: Mengfan Hou

  KEYWORDS: Periodic Event-Triggered Mechanism (PETM), Dynamic Output Feedback Control, Packet Losses, Dynamic Quantizer, Linear Matrix Inequalities (LMIs)

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.16 No.10, October 30, 2026

  ABSTRACT: This paper investigates the co-design problem of an event-triggered communication mechanism and a dynamic output feedback controller for networked control systems (NCSs) subject to packet losses and quantization errors under a no-ACK transmission mechanism. For the baseline scenario with packet losses only, an augmented closed-loop system model incorporating registers and auxiliary variables is constructed to characterize the effects of consecutive packet losses. A Lyapunov-based approach is then employed to derive sufficient linear matrix inequality (LMI) conditions for ℒ 2 -stability, based on which the dynamic periodic event-triggered mechanism (PETM) and the dynamic output feedback controller are co-designed. To further account for quantized signal transmission, a dynamic quantization scheme is introduced to prevent quantizer saturation caused by external disturbances through adaptive adjustment of the quantization scaling parameter. The dynamic PETM and dynamic quantizer are jointly designed as a unified dynamic periodic event-triggered quantization mechanism (PETQM), based on which an augmented closed-loop system model is established. The LMI conditions derived for the baseline scenario are then employed to facilitate the joint design of the dynamic PETQM and the dynamic output feedback controller, while accounting for the coupled effects of packet losses and quantization errors. Numerical examples demonstrate that the proposed method reduces network transmissions while maintaining the stability and control performance of the closed-loop system.