Patent
1994-11-10
1997-09-30
Davis, George B.
395 23, 395 24, 395903, 395906, G05B 1302
Patent
active
056733682
ABSTRACT:
In known processes for conducting a process in an automatically controlled system, the system is preset at the beginning of each process run based on at least one process parameter. The at least one process parameter is precomputed with a model of the process, containing at least one model parameter and input values supplied to the model. During the process, the input values and the process parameter are measured and used to adaptively improve the precomputed process parameter after the process run. A neural network is used to determine the model parameters whose dependence on the input values is unknown or insufficiently known. Network parameters of the neural network are modified after each process run to adapt the model to the actual process events.
REFERENCES:
patent: 5513097 (1996-04-01), Gramckow et al.
Silvestrini, et al., "Autoadaptive process control of a Sendzimir mill at ILVA," Iron and Steel Engineer, pp. 50-55 (Aug. 1993).
Sun, et al., "A Hybrid Neural Network Model for Solving Optimization Problems," IEEE Transactions on Computers, vol. 42, No. 2, pp. 218-227 (Feb. 1993).
Psaltis et al, "A Multilayered Neural Network Controller", IEEE Control System Magazine, 1988.
Broese Einar
Gramckow Otto
Martinetz Thomas
Soergel Guenter
Davis George B.
Siemens Aktiengesellschaft
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