Vieira, José BarrosDias, FernandoMota, Alexandre2013-12-022013-12-022004VIEIRA, 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. 265–2730952-1976http://hdl.handle.net/10400.11/2135This 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 caseengTemperature controlFuzzy hybridsystemsArtificial neural networksApplied neuro-fuzzy controlModel-based controlReal-time controljournal article