AU4481900A - A neural network control system for a thermal regenerative machine - Google Patents

A neural network control system for a thermal regenerative machine

Info

Publication number
AU4481900A
AU4481900A AU44819/00A AU4481900A AU4481900A AU 4481900 A AU4481900 A AU 4481900A AU 44819/00 A AU44819/00 A AU 44819/00A AU 4481900 A AU4481900 A AU 4481900A AU 4481900 A AU4481900 A AU 4481900A
Authority
AU
Australia
Prior art keywords
control system
neural network
network control
regenerative machine
thermal regenerative
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
AU44819/00A
Inventor
Laurence B. Penswick
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Stirling Tech Co
Original Assignee
Stirling Tech Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Stirling Tech Co filed Critical Stirling Tech Co
Publication of AU4481900A publication Critical patent/AU4481900A/en
Abandoned legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/024—Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02G—HOT GAS OR COMBUSTION-PRODUCT POSITIVE-DISPLACEMENT ENGINE PLANTS; USE OF WASTE HEAT OF COMBUSTION ENGINES; NOT OTHERWISE PROVIDED FOR
    • F02G1/00—Hot gas positive-displacement engine plants
    • F02G1/04—Hot gas positive-displacement engine plants of closed-cycle type
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
AU44819/00A 1999-04-23 2000-04-19 A neural network control system for a thermal regenerative machine Abandoned AU4481900A (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US29921599A 1999-04-23 1999-04-23
US09299215 1999-04-23
PCT/US2000/010843 WO2000065413A1 (en) 1999-04-23 2000-04-19 A neural network control system for a thermal regenerative machine

Publications (1)

Publication Number Publication Date
AU4481900A true AU4481900A (en) 2000-11-10

Family

ID=23153824

Family Applications (1)

Application Number Title Priority Date Filing Date
AU44819/00A Abandoned AU4481900A (en) 1999-04-23 2000-04-19 A neural network control system for a thermal regenerative machine

Country Status (2)

Country Link
AU (1) AU4481900A (en)
WO (1) WO2000065413A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022098929A1 (en) * 2020-11-06 2022-05-12 Energy Internet Corporation Control and configuration of software-defined machines

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5371809A (en) * 1992-03-30 1994-12-06 Desieno; Duane D. Neural network for improved classification of patterns which adds a best performing trial branch node to the network
US5342176A (en) * 1993-04-05 1994-08-30 Sunpower, Inc. Method and apparatus for measuring piston position in a free piston compressor
US5552608A (en) * 1995-06-26 1996-09-03 Philips Electronics North America Corporation Closed cycle gas cryogenically cooled radiation detector
US5678409A (en) * 1996-06-21 1997-10-21 Hughes Electronics Passive three state electromagnetic motor/damper for controlling stirling refrigerator expanders

Also Published As

Publication number Publication date
WO2000065413A1 (en) 2000-11-02

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Legal Events

Date Code Title Description
MK6 Application lapsed section 142(2)(f)/reg. 8.3(3) - pct applic. not entering national phase