Inversion of fuzzy neural networks for the reduction of noise in the control loop

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

A robust throttle valve control has always been a attractive problem since throttle by wire systems were established in the mid-nineties. Often in control strategy, a feedforward controller is adopted in which an inverse model is used. Mathematical inversions of models imply a high order of differentiation of the state variables and consequently noise effects. In general, neural networks are a very effective and popular tool mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the control problem schemes. This paper presents a control strategy based upon an inversion of a feed forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented in which two control loops are explicitly compared
Original languageEnglish
Title of host publicationIntelligent Manufacturing Systems
EditorsCarlos Eduardo Pereira, Oleg Zaikin, Zbigniew A. Banaszak
Number of pages6
Volume9
PublisherInternational Federation of Automatic Control
Publication date2008
Pages157-162
ISBN (print)978-3-902661-40-1
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event9th International Federation on Automatic Control Conference on Intelligent Manufacturing Systems - 2008 - Szczecin, Poland
Duration: 09.10.200810.10.2008
Conference number: 9
http://www.ifacims2019.com/

    Research areas

  • Engineering - Fuzzy networks, inversion, noise reduction

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