Neuro-fuzzy control for generalised nonlinear systems under a recursive framework

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Abstract

This paper proposes a general recursive state-space Neuro-Fuzzy control framework. It combines a eight-layered neuro-fuzzy architecture with a state feedback quadratic stabilising controller. Both the model and controller are updated online within a constrained unscented Kalman filter. Results from a benchmark Multi-Input and Multi-Output system demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of 2018 10th International Conference on Information Technology and Electrical Engineering: Smart Technology for Better Society, ICITEE 2018
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages89-93
Number of pages5
ISBN (Electronic)9781538647394
DOIs
Publication statusPublished - 13 Nov 2018
Event10th International Conference on Information Technology and Electrical Engineering, ICITEE 2018 - Bali, Indonesia
Duration: 24 Jul 201826 Jul 2018

Conference

Conference10th International Conference on Information Technology and Electrical Engineering, ICITEE 2018
Country/TerritoryIndonesia
CityBali
Period24/07/1826/07/18

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