Design of optimal repetitive control based on EID estimator with adaptive periodic event-triggered mechanism for linear systems subjected to exogenous disturbances

TL;DR

This paper presents an advanced control scheme combining modified repetitive control, an EID estimator, and an adaptive event-triggered mechanism to improve disturbance rejection and reduce communication load in linear systems with external disturbances.

Contribution

It introduces a novel integrated control framework that enhances disturbance rejection and communication efficiency for linear systems under unknown disturbances and resource constraints.

Findings

Effective disturbance rejection demonstrated in simulations

Reduced communication load via adaptive event-triggering

Enhanced robustness and stability of the control system

Abstract

The periodic signal tracking and the unknown disturbance rejection under limited communication resources are main important issues in many physical systems and practical applications. The control of such systems has some challenges such as time-varying delay, unknown external disturbances, structure uncertainty, and the heavy communication burden on the sensors and controller. These challenges affect the system performance and may destabilize the system. Hence, in this article, an improved scheme has been designed to overcome these challenges to achieve a good control performance based on optimization technique, and to guarantee the closed-loop system stability. The proposed scheme can be described as: modified repetitive control (MRC) with equivalent-input-disturbance (EID) estimator based on adaptive periodic event-triggered mechanism (APETM). The scheme that has been created is intended for linear systems that experience external disturbances which are not known, and must operate within constraints on communication resources. MRC based on EID has been developed with the goal of achieving periodic reference tracking and enhancing the ability to effectively reject both periodic and aperiodic unknown disturbances. In addition, utilizing APETM to reduce data transmission, computational burden and to save communication resources. Additionally, an optimization method is employed to fine-tune the parameters of the controller, enabling adjustments to the control and learning actions. Overall architecture of the system, incorporating the APETM-MRC with the utilization of an EID estimator and optimal techniques, can be described as a time-varying delay system. Proposed schemes were demonstrated to be effective, feasible, and robust through simulated application.