Reinforcement-learning based fault-tolerant control

Dapeng Zhang, Zhiling Lin, Zhiwei Gao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Engineering systems are always subjected to faults or malfunctions due to age or unexpected events, which would degrade the operation performance and even lead to the operation failure-Therefore, there is a strong motivation to develop fault-tolerant control strategy so that the system can operate with tolerated perform ance de ggr ad ation-In this p ap er, a novel approach based on reinforcement leaning is proposed to design a fault-tolerant controller without need of the information on faults-T simulation example.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages671-676
Number of pages6
ISBN (Electronic)9781538608371
DOIs
Publication statusPublished - 10 Nov 2017
Event15th IEEE International Conference on Industrial Informatics, INDIN 2017 - Emden, Germany
Duration: 24 Jul 201726 Jul 2017

Publication series

NameProceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017

Conference

Conference15th IEEE International Conference on Industrial Informatics, INDIN 2017
CountryGermany
CityEmden
Period24/07/1726/07/17

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