The Nonlinear System Identification for the Engine of Automated Automobiles Using Neural Networks Harbin Institute of Technology

Format:

Conference/Event

Author/Creator:

Wu, Guangqiang, author.

Conference Name:

International Off-Highway & Powerplant Congress & Exposition (1996-08-26 : Indianapolis, Indiana, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 1996

Summary:

In this paper the nonlinear system identification theory and method using neural networks are presented, the multilayer feedforward networks employed, the backpropagation learning algorithm proposed. The inputs of the networks are consisted of angular velocity and throttle angle, and outputs torque of the engine, finally the comparision of simulation result with that of experiment and other results that embody the effect of system identification are given. Relative studies revealed that the nonlinear system identification for the engine of automated automobiles using neural networks can be effective

Notes:

Vendor supplied data

Publisher Number:

961825

Access Restriction:

Restricted for use by site license