Title :
System identification using neural networks
Author :
Zhang, Chang Q. ; Moore, Kevin L.
Author_Institution :
Coll. of Eng., Idaho State Univ., Pocatello, ID, USA
Abstract :
A recent result by S.R. Chu et al. (1989) shows the use of a Hopfield neural network to identify the A and B matrices of a linear system using state measurements. The authors extend this result to the identification of the complete (A, B, C, D) description using output measurements. They develop a convenient state-space representation for the identification, and describe how the identification problem can be mapped onto the Hopfield network. A computer simulation to illustrate the technique is presented
Keywords :
Hopfield neural nets; parameter estimation; state-space methods; (A, B, C, D) description; Hopfield neural network; state-space representation; system identification; Computer simulation; Educational institutions; Equations; Hopfield neural networks; Linear systems; Matrix converters; Neural networks; Observability; State-space methods; System identification;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261443
