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Title: Self-organizing sensing and actuation for automatic control

Abstract

A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

Inventors:
Issue Date:
Research Org.:
CYBOMEDICAL, INC. Rancho Cordova, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1368192
Patent Number(s):
9696699
Application Number:
14/082,059
Assignee:
CYBOMEDICAL, INC.
Patent Classifications (CPCs):
G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
DOE Contract Number:  
SC0008235
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Nov 15
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Cheng, George Shu-Xing. Self-organizing sensing and actuation for automatic control. United States: N. p., 2017. Web.
Cheng, George Shu-Xing. Self-organizing sensing and actuation for automatic control. United States.
Cheng, George Shu-Xing. Tue . "Self-organizing sensing and actuation for automatic control". United States. https://www.osti.gov/servlets/purl/1368192.
@article{osti_1368192,
title = {Self-organizing sensing and actuation for automatic control},
author = {Cheng, George Shu-Xing},
abstractNote = {A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {7}
}

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