Applying neuro-fuzzy model dFasArt in control systems

• Published in: Engineering applications of artificial intelligence Vol. 23; no. 7; pp. 1053 - 1063
• Main Authors: Cano-Izquierdo, J., Almonacid, M., Ibarrola, J.J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2010
• Subjects: Artificial neural networks; Classification; Control systems; Controller performance; Dynamic neuro-fuzzy; Dynamics; FasArt; Fuzzy sets; Identification; Mathematical models; Monitoring; Monitoring/assessment; Temporal logic; Identification; FasArt; Monitoring/assessment; Controller performance; Dynamic neuro-fuzzy

This paper presents the neuro-fuzzy dFasArt (dynamic FasArt) architecture as an extension of the FasArt model including a dynamic algorithm formulation. This allows dFasArt to deal with identification and clustering problems using the temporal information of the signals. The focus is placed on the a...