Generic neural network training and processing system

Details Generic neural network training and processing system Generic neural network training and processing system

1996-02-05

1998-04-28

Hafiz, Tariq R.

G06E 100, G06E 300

Patent

active

057456534

ABSTRACT:
A electronic engine control (EEC) module executes a generic neural network processing program to perform one or more neural network control funtions. Each neural network funtion is defined by a unitary data structure which defines the network architecture, including the number of node layers, the number of nodes per layer, and the interconnections between nodes. In addition, the data structure holds weight values which determine the manner in which network signals are combined. The network definition data structures are created by a network training system which utilizes an external training processor which employs gradient methods to derive network weight values in accordance with a cost function which quantitatively defines system objectives and an identification network which is pretrained to provide gradient signals representative the behavior of the physical plant. The training processor executes training cycles asynchronously with the operation of the EEC module in a representative test vehicle.

REFERENCES:
patent: 5200898 (1993-04-01), Yahara et al.
patent: 5247445 (1993-09-01), Miyano et al.
patent: 5361213 (1994-11-01), Fujieda et al.
patent: 5434783 (1995-07-01), Pal et al.
patent: 5479573 (1995-12-01), Keeler et al.
patent: 5598509 (1997-01-01), Takahashi et al.
patent: 5625750 (1997-04-01), Pusrorius et al.
Feldkamp et al, "Neural Control Systems Trained by Dynamic Gradient Methods for Automotive Applications", IEEE ICNN, 1992.
Puskorius et al, "Neurocontrol of Nonlinear Dynamical Systems with Kalman Filter Trained Recurrent Networks," IEEE Transactions on Neural Networks, 1994.
Narendra et al, "Gradient Methods for the Optimization of Dynamical Systems Containing Neural Networks," IEEE Transactions of Neural Networks, 1991.
Narendra et al, "Identification and Control of Dynamical Systems Using Neural Networks," IEEE Transactions on Neural Networks, 1990.
"Automotive Engine Idle Speed Control with Recurrent Neural Networks" by G. V. Puskorius and L. A. Feldkamp, Research Laboratory, Ford Motor Company; In Proceedings of the 1993 American Control Conference; pp. 311 to 316.

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