Patent
1996-07-11
1998-04-14
Davis, George B.
395 23, 395902, 395903, 395906, G06F 1518, G06F 1546
Patent
active
057403244
ABSTRACT:
The method of making the tool, for process system identification that is based on the general purpose learning capabilities of neural networks. The method can be used for a wide variety of system identification problems with little or no analytic effort. A neural network is trained using a process model to approximate a function which relates process input and output data to process parameter values. Once trained, the network can be used as a system identification tool. In principle, this approach can be used for linear or nonlinear processes, for open or closed loop identification, and for identifying any or all process parameters.
REFERENCES:
patent: 5111531 (1992-05-01), Grayson et al.
patent: 5119468 (1992-06-01), Owens
patent: 5159660 (1992-10-01), Lu et al.
patent: 5175678 (1992-12-01), Frerichs et al.
patent: 5372015 (1994-12-01), Suzuki et al.
patent: 5394322 (1995-02-01), Hansen
patent: 5408586 (1995-04-01), Sheirik
patent: 5467883 (1995-11-01), Frye et al.
patent: 5471381 (1995-11-01), Khan
patent: 5486998 (1996-01-01), Corso
patent: 5513098 (1996-04-01), Spall et al.
patent: 5586221 (1996-12-01), Isik et al.
patent: 5608843 (1997-03-01), Baird, III
Fu-Chuang Chen, "Back-Propagation Neural Networks for Nonlinear Self-Tuning Adaptive Control", 1990 IEEE Control System Magazine.
Mathur Anoop
Samad Tariq
Davis George B.
Honeywell
MacKinnon Ian D.
LandOfFree
Method for process system identification using neural network does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method for process system identification using neural network, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method for process system identification using neural network will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-645026