CA2079147A1 - Simulator using a neural network - Google Patents

Simulator using a neural network

Info

Publication number
CA2079147A1
CA2079147A1 CA2079147A CA2079147A CA2079147A1 CA 2079147 A1 CA2079147 A1 CA 2079147A1 CA 2079147 A CA2079147 A CA 2079147A CA 2079147 A CA2079147 A CA 2079147A CA 2079147 A1 CA2079147 A1 CA 2079147A1
Authority
CA
Canada
Prior art keywords
neural network
simulator
controlled
real
simulate
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.)
Granted
Application number
CA2079147A
Other languages
French (fr)
Other versions
CA2079147C (en
Inventor
Kazuteru Ono
Tadahiro Yanagisawa
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.)
Toshiba Corp
Original Assignee
Toshiba Corp
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 Toshiba Corp filed Critical Toshiba Corp
Publication of CA2079147A1 publication Critical patent/CA2079147A1/en
Application granted granted Critical
Publication of CA2079147C publication Critical patent/CA2079147C/en
Anticipated expiration legal-status Critical
Expired - Fee Related 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
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • 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

Abstract

A simulator includes a modelling simulate section in which properties of an apparatus to be controlled are modelled. In addition, this simulator includes a neural network in which learning is performed depending on a real control quantity for the apparatus to be controlled. A
correction value relative to a simulation control quantity for the modeling simulate section is calculated in the neural network based on a process quantity output from a controlling unit. Thereafter, the simulation control quantity is corrected depending on the calculated correction value. In practice, learning is performed in the neural network by changing a synapse load based on a real quantity for the apparatus to be controlled. As a result of the foregoing correction, the simulator can simulate the real apparatus more accurately.
CA002079147A 1991-10-31 1992-09-25 Simulator using a neural network Expired - Fee Related CA2079147C (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP3-286804 1991-10-31
JP3286804A JPH05127706A (en) 1991-10-31 1991-10-31 Neural network type simulator

Publications (2)

Publication Number Publication Date
CA2079147A1 true CA2079147A1 (en) 1993-05-01
CA2079147C CA2079147C (en) 1996-04-16

Family

ID=17709266

Family Applications (1)

Application Number Title Priority Date Filing Date
CA002079147A Expired - Fee Related CA2079147C (en) 1991-10-31 1992-09-25 Simulator using a neural network

Country Status (5)

Country Link
US (1) US5418710A (en)
EP (1) EP0540168B1 (en)
JP (1) JPH05127706A (en)
CA (1) CA2079147C (en)
DE (1) DE69228517T2 (en)

Families Citing this family (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE69425100T2 (en) * 1993-09-30 2001-03-15 Koninkl Philips Electronics Nv Dynamic neural network
EP0712262A1 (en) * 1994-11-10 1996-05-15 Siemens Audiologische Technik GmbH Hearing aid
EP0712263B1 (en) * 1994-11-10 2003-01-29 Siemens Audiologische Technik GmbH Programmable hearing aid
DE19516426A1 (en) * 1995-05-04 1996-11-07 Siemens Ag Arrangement for modeling a dynamic process
US5917730A (en) * 1995-08-17 1999-06-29 Gse Process Solutions, Inc. Computer implemented object oriented visualization system and method
US6178393B1 (en) * 1995-08-23 2001-01-23 William A. Irvin Pump station control system and method
DE19715503A1 (en) 1997-04-14 1998-10-15 Siemens Ag Integrated computer and communication system for the plant area
KR100552579B1 (en) * 2001-04-20 2006-02-15 혼다 기켄 고교 가부시키가이샤 Plant control apparatus
JP4064159B2 (en) * 2002-06-06 2008-03-19 本田技研工業株式会社 Plant control equipment
US6947870B2 (en) * 2003-08-18 2005-09-20 Baker Hughes Incorporated Neural network model for electric submersible pump system
US8065022B2 (en) * 2005-09-06 2011-11-22 General Electric Company Methods and systems for neural network modeling of turbine components
JP5239686B2 (en) * 2008-09-25 2013-07-17 横河電機株式会社 Process estimation system and process estimation method
US8682630B2 (en) * 2009-06-15 2014-03-25 International Business Machines Corporation Managing component coupling in an object-centric process implementation
JP6497367B2 (en) * 2016-08-31 2019-04-10 横河電機株式会社 PLANT CONTROL DEVICE, PLANT CONTROL METHOD, PLANT CONTROL PROGRAM, AND RECORDING MEDIUM
DE102016224207A1 (en) * 2016-12-06 2018-06-07 Siemens Aktiengesellschaft Method and control device for controlling a technical system
EP3506026A1 (en) * 2017-12-29 2019-07-03 Siemens Aktiengesellschaft Method for the computer-assisted prediction of at least one global operating variable of a technical system
TWI734059B (en) 2018-12-10 2021-07-21 財團法人工業技術研究院 Dynamic prediction model establishment method, electric device, and user interface
US20190138848A1 (en) * 2018-12-29 2019-05-09 Intel Corporation Realistic sensor simulation and probabilistic measurement correction
CN111542135B (en) * 2020-05-18 2022-06-10 湖南双达机电有限责任公司 Heater control method, heater and deicing vehicle

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4858147A (en) * 1987-06-15 1989-08-15 Unisys Corporation Special purpose neurocomputer system for solving optimization problems
US4874963A (en) * 1988-02-11 1989-10-17 Bell Communications Research, Inc. Neuromorphic learning networks
US4943931A (en) * 1988-05-02 1990-07-24 Trw Inc. Digital artificial neural processor
JP2595051B2 (en) * 1988-07-01 1997-03-26 株式会社日立製作所 Semiconductor integrated circuit
JPH02136904A (en) * 1988-11-18 1990-05-25 Hitachi Ltd Motion controller containing its own producing function for action series
US5016204A (en) * 1989-02-28 1991-05-14 Digital Equipment Corporation Expert system for performing diagnostic and redesign operations incorporating multiple levels of simulation detail
JP2533942B2 (en) * 1989-03-13 1996-09-11 株式会社日立製作所 Knowledge extraction method and process operation support system
JPH0314002A (en) * 1989-06-12 1991-01-22 Toshiba Corp Process characteristic simulator
US5056037A (en) * 1989-12-28 1991-10-08 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Analog hardware for learning neural networks
US5161110A (en) * 1990-02-27 1992-11-03 Atlantic Richfield Company Hierarchical process control system and method
US5142612A (en) * 1990-08-03 1992-08-25 E. I. Du Pont De Nemours & Co. (Inc.) Computer neural network supervisory process control system and method
US5349541A (en) * 1992-01-23 1994-09-20 Electric Power Research Institute, Inc. Method and apparatus utilizing neural networks to predict a specified signal value within a multi-element system

Also Published As

Publication number Publication date
EP0540168B1 (en) 1999-03-03
EP0540168A3 (en) 1994-08-03
JPH05127706A (en) 1993-05-25
DE69228517D1 (en) 1999-04-08
CA2079147C (en) 1996-04-16
DE69228517T2 (en) 1999-08-26
US5418710A (en) 1995-05-23
EP0540168A2 (en) 1993-05-05

Similar Documents

Publication Publication Date Title
CA2079147A1 (en) Simulator using a neural network
CA2066278A1 (en) Computer neural network supervisory process control system and method
CA2066237A1 (en) Computer neural network regulatory process control system and method
Chen Back-propagation neural networks for nonlinear self-tuning adaptive control
WO2003068327A3 (en) System and method for verifying the calibration of an exercise apparatus
CA2105842A1 (en) Neural Network Based Control System
WO1999031654A3 (en) Method of determining model-specific factors for pattern recognition, in particular for speech patterns
CA2241710A1 (en) Off-line teaching method
CA2236426A1 (en) Method and apparatus for generating a model of an industrial production
DE69333215D1 (en) Training method and device for setting a neuron
JPH07287695A (en) Computer system and robot system able to learn and grow autonomously
CN112933551B (en) Terrain matching control method and device of virtual reality treadmill
AU1788700A (en) Combat pilot aid system
KR910018910A (en) Equipment operation control software development support method and device
DE69030812D1 (en) METHOD AND DEVICE FOR CONTROLLING A PROCESS WITH THE AID OF A TRAINED PARALLEL DISTRIBUTED PROCESSING NETWORK
DE50201271D1 (en) Programmable device with a gravimetric measuring instrument, method for programming such a device and software for performing the method
Chen et al. High-order iterative learning control of functional neuromuscular stimulation systems
DE59601347D1 (en) ARRANGEMENT FOR MODELING A DYNAMIC PROCESS
Kraft et al. Comparison of convergence properties of CMAC neural networks and traditional adaptive controllers
Jansen et al. Globally stable neural robot control capable of payload adaptation
Ananthakrishnan et al. Experimental adaptive control of a four-axis hydraulically actuated robot.
MOODY New neural algorithms for self-organized learning(Interim Report, Dec. 1988- Nov. 1991)
WO1996009573A3 (en) Arrangement for the adaptive control of a section
CN114528947A (en) Operator motor skill training method based on generation confrontation imitation learning
JPS647203A (en) Locus control method

Legal Events

Date Code Title Description
EEER Examination request
MKLA Lapsed