Adaptive control using a grey box neural model: An experimental application

Cubillos, F. A.; Acuna, G.

Keywords: temperature, model, systems, energy, combustion, balance, networks, control, chambers, function, dryer, chamber, box, adaptive, Neural, Predictive, radial, Fluidized, grey, basis, vibrating, Phenomenological

Abstract

This paper presents the application of a Grey Box Neural Model (GNM) in adaptive-predictive control of the combustion chamber temperature of a pilot-scale vibrating fluidized dryer. The GNM is based upon a phenomenological model of the process and a neural network that estimates uncertain parameters. The GNM was synthesized considering the energy balance and a radial basis function neural network (RBF) trained on-line to estimate heat losses. This predictive model was then incorporated into a predictive control strategy with one step look-ahead. The proposed system shows excellent results with regard to adaptability, predictability and control when subject to setpoint and disturbances changes. © Springer-Verlag Berlin Heidelberg 2007.

Más información

Título de la Revista: HCI INTERNATIONAL 2023 LATE BREAKING PAPERS, HCII 2023, PT III
Volumen: 4491
Número: PART 1
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2007
Página de inicio: 311
Página final: 318
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-37249063769&partnerID=q2rCbXpz