Title :
Neural identification of systems with linear dynamics and static nonlinear elements
Author :
Oliveira, R.C.L. ; Azevedo, F.M. ; Barreto, J.M. ; da Costa, C.T.
Author_Institution :
Dept. of Electr. Eng. - DEE, Fed. Univ. of Para - UFPA, Belem, Brazil
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
Identification of nonlinear systems represented by a combination of linear dynamics and static nonlinear elements is achieved by a new model of locally recurrent globally feedforward neural network and uses only input/output measurements.
Keywords :
feedforward neural nets; identification; linear systems; neurocontrollers; nonlinear control systems; recurrent neural nets; input-output measurements; linear dynamics; locally recurrent globally feedforward neural network; neural identification; nonlinear systems; static nonlinear elements; Adaptation models; Artificial neural networks; Feedforward neural networks; Heuristic algorithms; Mathematical model; Neurons; Nonlinear dynamical systems; dynamic neurons; identification; interconnected subsystems; neural networks;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5
