Adaptive control using a grey box neural model: An experimental application
Keywords: temperature, model, systems, energy, combustion, balance, networks, control, chambers, function, dryer, chamber, box, adaptive, Neural, Predictive, radial, Fluidized, grey, basis, vibrating, Phenomenological
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.
|Título de la Revista:||DESIGN, USER EXPERIENCE, AND USABILITY: UX RESEARCH, DESIGN, AND ASSESSMENT, PT I|
|Editorial:||SPRINGER INTERNATIONAL PUBLISHING AG|
|Fecha de publicación:||2007|
|Página de inicio:||311|