What type of study is this?

This is a Experimental Study study.

September 17, 2025Open Access

Data‐Driven Stabilization of Linear Discrete‐Time Delay Systems With Noisy Data

Key Points

Effective design of stabilizing controllers ensures asymptotic stability for linear discrete-time delay systems.
Criteria derived using the Lyapunov functional approach demonstrate an ability to manage upper-bounded uncertainties.
Simulation results validate the proposed method, showing an extended allowable delay range.
The study addresses stabilization challenges that arise from process disturbances affecting system measurements.

Abstract

ABSTRACT This paper is concerned with the stabilization of linear discrete‐time delay systems with unknown system matrices. The objective is to design stabilizing controllers using input and state measurements collected from experiments, which are affected by process disturbances. Assuming that these unknown disturbances are upper‐bounded, the pair of system matrices is represented as a data‐based nominal matrix plus a norm‐bounded uncertain matrix. By utilizing the Lyapunov functional approach, sufficient criteria are derived to design control gains that ensure asymptotic stability of the closed‐loop system. Simulation results validate the effectiveness of the proposed approach, demonstrating an extended allowable delay range compared to some recent methods.

Data‐Driven Stabilization of Linear Discrete‐Time Delay Systems With Noisy Data

Key Points

Abstract

Cite This Study

Also Consider

Also Consider