Application research on the model identification with neural networks

Author

Feng, Wu Jun ; Ben, Chen Shan

Author_Institution

Harbin Inst. of Technol., China

fYear

1999

fDate

1999

Firstpage

311

Abstract

A method to identify the efficiency factor of the automobile motor is described based on the principle of neural networks. It is supposed that this factor depends on the angle velocity of the motor axis and the pressure in the collector. The data measured is divided into two groups, one is used for the identification, the other for the validation determining the capacity predictive of this model. By comparing the two models built up with a common method and neural networks, it is possible to conclude that the latter is effective and the result is good

Keywords

automobiles; internal combustion engines; mechanical engineering computing; parameter estimation; radial basis function networks; angle velocity; automobile; collector pressure; efficiency factor identification; identification; model identification; motor axis; neural networks; radial basis function networks; validation; Artificial neural networks; Automobiles; Brain modeling; Control system synthesis; Costs; Neural networks; Neurofeedback; Nonlinear control systems; Predictive models; Radial basis function networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicle Electronics Conference, 1999. (IVEC '99) Proceedings of the IEEE International

Conference_Location

Changchun

Print_ISBN

0-7803-5296-3

Type

conf

DOI

10.1109/IVEC.1999.830693

Filename

830693