Distributed adaptive event-triggered iterative learning controller based on a filtering network

Abstract

This paper develops a distributed adaptive event-triggered iterative learning controller over a filtering network for a class of tracking control systems. The proposed distributed control method is more robust than centralized control in terms of node failure and transmission constraints. In view of the limited network bandwidth, adaptive event-triggered mechanisms (AETMs) have been considered in the network communication process. The proposed AETM is characterized by introducing the dynamic threshold parameter, which provides benefits in data scheduling. The existence of filters and controllers is analyzed by Lyapunov stability theory and linear matrix inequality techniques, and their parameters are finally obtained. Moreover, some simulation results on a numerical example and a irrigation canal are presented to show the applicability of the obtained results.

Adaptive iteration learning control with iteration‐varying event‐triggered mechanism for discrete‐time nonlinear systems with random initial states

“…Zhang et al 28 developed an ET‐ILC scheme with quantization for linear multi‐agent systems. Considering filtering network described by a linear discrete‐time model, a distributed ET‐ILC method was proposed by Zhu et al 29 In addition, three types of linear ET‐ILC schemes based on Lyapunov function were developed for linear time‐varying systems 30 . There are also some research efforts on ET‐ILC for nonlinear systems.…”

Sliding mode control based on RBF neural network for a class of underactuated systems with input quantization and event-triggering

“…The event-triggering is an aperiodic control mechanism that transmits the control signal at the next time only when certain triggering conditions are met, which has made rapid development in the control field, especially in dealing with complex networked dynamic systems (Choi and Yoo, 2018; Huang and Wang, 2019; Zhang et al, 2018; Zhu and Peng, 2021). In the work by Xiao et al (2018), a mode-dependent event-triggered transmission scheme is designed for continuous-time switched linear systems.…”

Robust adaptive event‐triggered ILC scheme design for discrete‐time non‐repetitive nonlinear systems

“…Furthermore, Lin et al [31] and Bu et al [32] designed Lyapunov function-based model-free adaptive ET-ILC methods for repetitive nonlinear systems. Several other research efforts have explored ET-ILC for linear systems [33,34]. In addition, Zhang et al [35], Lin et al [36,37], Hua et al [38] and Wang et al [39] developed ET-ILC methods for multi-agent systems.…”

“…[32] designed Lyapunov function‐based model‐free adaptive ET‐ILC methods for repetitive nonlinear systems. Several other research efforts have explored ET‐ILC for linear systems [33, 34]. In addition, Zhang et al.…”