Fault-tolerant Q-learning for discrete-time linear systems with actuator and sensor faults using input-output measured data

This study presents a novel output feedback Q-learning algorithm specifically designed for fault-tolerant control in real-time applications, circumventing the necessity for explicit system models or detailed actuator and sensor fault information. A significant benefit of this algorithm is its capabi...

詳細記述

書誌詳細

出版年:	Franklin Open
主要な著者:	Mohammadrasoul Kankashvar, Sajad Rafiee, Hossein Bolandi
フォーマット:	論文
言語:	英語
出版事項:	Elsevier 2025-06-01
主題:	Reinforcement learning Fault-tolerant control Actuator faults Sensor faults Output feedback Q-learning
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2773186325000490