Iterative Learning Control with Adaptive Kalman Filtering for Trajectory Tracking in Non-Repetitive Time-Varying Systems

Iterative Learning Control with Adaptive Kalman Filtering for Trajectory Tracking in Non-Repetitive Time-Varying Systems

This paper presents an adaptive Kalman filter (AKF)-enhanced iterative learning control (ILC) scheme to improve trajectory tracking in non-repetitive time-varying systems (NTVSs), particularly in industrial applications. Unlike traditional ILC methods that assume fixed system dynamics, gradual param...

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Bibliographic Details
Main Authors: Lei Wang, Shunjie Zhu, Menghan Wei, Xiaoxiao Wang, Ziwei Huangfu, Yiyang Chen
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Axioms
Subjects:
iterative learning control
non-repetitive time-varying systems
adaptive Kalman filter
robust convergence
Online Access:https://www.mdpi.com/2075-1680/14/5/324
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