Approximation and control of the engine torque using neural networks

SAE Technical Papers

Volumn , Issue , 2000, Pages

  Müller, Rainer ^a   Schneider, Bernd ^a  

^a DAIMLER AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; ENGINES; TORQUE;

DIRECT MEASUREMENT; DYNAMIC NEURAL NETWORKS; ENGINE CONTROL UNIT; ENGINE TORQUE; FAST AND ACCURATE ALGORITHMS; HIGH COSTS; SENSOR SIGNALS; SI ENGINES;

RECURRENT NEURAL NETWORKS;

EID: 85072458040     PISSN: 01487191     EISSN: 26883627     Source Type: Journal    
DOI: 10.4271/2000-01-0929     Document Type: Conference Paper

References (6)

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3. [NP90], Narendra K.S., and Parthasarathy K.,. Identification and control of dynamical systems using neural networks. IEEE Transactions on Neural Networks, 1 (1): 4-27, 1990.
4. [PF94], Puskorius G.V., and Feldkamp L.A.,. Neurocontrol of nonlinear dynamical systems with kalman filter trained recurrent networks. IEEE Transactions on Neural Networks, 5 (2): 279-297, 1994.
5. [Rie97], Riedmiller M.,. Selbständige lernende neuronale Steuerungen. VDI Fortschrittsberichte Nr. 626, 1997. In german.
6. [WP90], Williams R.J., and Peng J.,. An efficient gradient-based algorithm for on-line training of recurrent network trajectories. Neural Computation, 2: 490-501, 1990.