On-line identification of a municipal solid waste incinerator by fully tuned RBF neural networks

A. Giantomassi, G. Ippoliti, S. Longhi, I. Bertini, S. Pizzuti

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

The paper describes an on-line identification algorithm to estimate the steam production of a municipal solid waste incinerator. The algorithm has to learn on-line the system dynamics due to the heavy disturbances acting on the incineration process. The learning algorithm is based on radial basis function networks and combines the growth criterion of the resource allocating network technique with an adaptive extended Kalman filter to update all the parameters of the networks. © 2009 IFAC.
Original languageEnglish
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event15th IFAC Symposium on System Identification, SYSID 2009 - , France
Duration: 1 Jan 2009 → …

Conference

Conference15th IFAC Symposium on System Identification, SYSID 2009
CountryFrance
Period1/1/09 → …

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Giantomassi, A., Ippoliti, G., Longhi, S., Bertini, I., & Pizzuti, S. (2009). On-line identification of a municipal solid waste incinerator by fully tuned RBF neural networks. Paper presented at 15th IFAC Symposium on System Identification, SYSID 2009, France. https://doi.org/10.3182/20090706-3-FR-2004.0378