The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 18, 2020

Filed:

Dec. 30, 2016
Applicant:

General Electric Company, Schenectady, NY (US);

Inventors:

Stephen William Piche, Austin, TX (US);

Fred Francis Pickard, Norfolk, MA (US);

Assignee:

General Electric Company, Schenectady, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01); G06F 17/50 (2006.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06F 17/16 (2006.01); G06N 7/00 (2006.01); G06F 17/11 (2006.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G05B 13/027 (2013.01); G05B 13/0265 (2013.01); G05B 13/041 (2013.01); G06F 17/11 (2013.01); G06F 17/16 (2013.01); G06F 17/5009 (2013.01); G06F 17/5018 (2013.01); G06N 3/0445 (2013.01); G06N 3/0472 (2013.01); G06N 3/08 (2013.01); G06N 3/084 (2013.01); G06N 7/005 (2013.01); G06F 2217/16 (2013.01);
Abstract

A method for modeling an operation of a system that may include a disturbance rejection model that is configured to generate a predicted value for a system output at a future time. The disturbance rejection model may include a neural network for mapping system inputs to the system output. The method may include the steps of: training the disturbance rejection model per a training dataset; and calculating a confidence metric for the disturbance rejection model. The confidence metric is configured to indicate a probability that a predicted sign of a gain in the system output at the future time made by the disturbance rejection model is correct.


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