Reinforcement learning–based fault-tolerant control with application to flux cored wire system

Zhang, Dapeng and Gao, Zhiwei (2018) Reinforcement learning–based fault-tolerant control with application to flux cored wire system. Measurement and Control, 51 (7-8). pp. 349-359. ISSN 0020-2940

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Official URL: http://dx.doi.org/10.1177/0020294018789202

Abstract

Background:
Processes and systems are always subjected to faults or malfunctions due to age or unexpected events, which would degrade the operation performance and even lead to operation failure. Therefore, it is motivated to develop fault-tolerant control strategy so that the system can operate with tolerated performance degradation.

Methods:
In this paper, a reinforcement learning-based fault-tolerant control method is proposed without need of the system model and the information of faults.

Results and Conclusions:
Under the real-time tolerant control, the dynamic system can achieve performance tolerance against unexpected actuator or sensor faults. The effectiveness of the algorithm is demonstrated and validated by the rolling system in a test bed of the flux cored wire.

Item Type: Article
Uncontrolled Keywords: Fault-tolerant control, reinforcement learning, performance index, flux cored wire
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Zhiwei Gao
Date Deposited: 10 Oct 2018 13:26
Last Modified: 11 Oct 2019 17:48
URI: http://nrl.northumbria.ac.uk/id/eprint/36162

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