Abstract

This paper proposes a new general adaptive 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 publicationECTI-CON 2018 - 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages45-48
Number of pages4
ISBN (Electronic)978-1-5386-3555-1
DOIs
Publication statusPublished - 18 Jan 2019
Event15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2018 - Chiang Rai, Thailand
Duration: 18 Jul 201821 Jul 2018

Conference

Conference15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2018
CountryThailand
CityChiang Rai
Period18/07/1821/07/18

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Gil, P., Oliveira, T., Cardoso, A., & Palma, L. (2019). Adaptive state-space neuro-fuzzy control. In ECTI-CON 2018 - 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (pp. 45-48). [8620064] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECTICon.2018.8620064