Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.11/2135
Título: Artificial neural networks and neuro-fuzzy systems for modelling and controlling real systems: a comparative study
Autor: Vieira, J.A.B.
Dias, Fernando
Mota, Alexandre
Palavras-chave: Temperature control
Fuzzy hybridsystems
Artificial neural networks
Applied neuro-fuzzy control
Model-based control
Real-time control
Data: 8-Mar-2004
Editora: Elsevier
Citação: VIEIRA, José; DIAS, Fernando; MOTA, Alexandre (2004) - Artificial neural networks and neuro-fuzzy systems for modelling and controlling real systems: a comparative study. Engineering Applications of Artificial Intelligence. ISSN 0952-1976. Vol. 17, nº 3. p. 265–273
Resumo: This article presents a comparison of artificial neural networks andneuro-fuzzy systems appliedfor modelling andcontrolling a real system. The main objective is to model and control the temperature inside of a kiln for the ceramic industry. The details of all system components are described. The steps taken to arrive at the direct and inverse models using the two architectures: adaptive neuro fuzzy inference system and feedforward neural networks are described and compared. Finally, real-time control results using internal model control strategy are resented. Using available Matlab software for both algorithms, the objective is to show the implementation steps for modelling and controlling a real system. Finally, the performances of the two solutions were comparedthrough different parameters for a specific real didactic case
Peer review: yes
URI: http://hdl.handle.net/10400.11/2135
ISSN: 0952-1976
Versão do Editor: http://www.sciencedirect.com/science/article/pii/S0952197604000211
Aparece nas colecções:ESTCB - Artigos em revistas com arbitragem científica

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