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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1489

Title: Design of Multivariable Neural Controllers Using a Classical Approach
Authors: Damarla, S K
Kundu, M
Keywords: MVSISO
DINN
FFNN
NN-controller
MIMO
IMC
PI
decoupled process
decoupled disturbance
Issue Date: Aug-2010
Publisher: IJCEA
Citation: International Journal of Chemical Engineering and Applications, Vol. 1, No. 2, August 2010
Abstract: In the present study, the neural network (NN) based multivariable controllers were designed as a series of single input-single output (SISO) controllers or multi variable SISO (MVSISO) controllers utilizing the classical decoupled process models. Multilayer feed forward networks (FFNN) were used as direct inverse neural network (DINN) controllers, which used the inverse dynamics of the decoupled process. To address the disturbance rejection problems, the IMC based neural control architecture was proposed with suitable choice of filter and disturbance transfer function. Multi input – multi output (MIMO) non-linear processes like interacting tank systems, temperature and level control of a mixing tank with hot and cold input streams & a (2×2) distillation process were considered as case studies for that purpose. Simplified as well as ideally decoupled process as well as disturbance transfer functions was used for neural controller design. DINN/IMC based NN controllers performed effe...
Description: Copyright belongs to International Journal of Chemical Engineering and Applications (IJCEA)
URI: http://hdl.handle.net/2080/1489
ISSN: 2010-0221
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