JPS6415808A - Process identifying method - Google Patents

Process identifying method

Info

Publication number
JPS6415808A
JPS6415808A JP62171054A JP17105487A JPS6415808A JP S6415808 A JPS6415808 A JP S6415808A JP 62171054 A JP62171054 A JP 62171054A JP 17105487 A JP17105487 A JP 17105487A JP S6415808 A JPS6415808 A JP S6415808A
Authority
JP
Japan
Prior art keywords
probability
post
model
optimum
process model
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
JP62171054A
Other languages
Japanese (ja)
Other versions
JPH0677215B2 (en
Inventor
Toru Nagaseko
Ryuichi Kuwabara
Takeshi Okita
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.)
Idemitsu Petrochemical Co Ltd
Original Assignee
Idemitsu Petrochemical Co Ltd
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 Idemitsu Petrochemical Co Ltd filed Critical Idemitsu Petrochemical Co Ltd
Priority to JP62171054A priority Critical patent/JPH0677215B2/en
Publication of JPS6415808A publication Critical patent/JPS6415808A/en
Publication of JPH0677215B2 publication Critical patent/JPH0677215B2/en
Anticipated expiration legal-status Critical
Expired - Lifetime legal-status Critical Current

Links

Landscapes

  • Testing And Monitoring For Control Systems (AREA)
  • Feedback Control In General (AREA)

Abstract

PURPOSE:To realize the optimum control of a process by selecting a process model having the maximum post-probability among plural models and identifying the selected model as an optimum process model. CONSTITUTION:A data sampling part 2 samples N pieces of input/output data on a process 1. These sampled data are supplied to a parameter deciding part 3 and the parameters of plural process models are obtained by a nonlinear optimizing method. Then a post-probability arithmetic part 4 obtains a probability density function based on the dispersed and observed values obtained from the parameter estimating value decided by the part 3. Then said probability density function is operated by Bayes theorem for acquisition of the post- probability of the process model. Thus the optimum process control is attained by identifying a process model that has the maximum post-probability.
JP62171054A 1987-07-10 1987-07-10 Process identification method Expired - Lifetime JPH0677215B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP62171054A JPH0677215B2 (en) 1987-07-10 1987-07-10 Process identification method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP62171054A JPH0677215B2 (en) 1987-07-10 1987-07-10 Process identification method

Publications (2)

Publication Number Publication Date
JPS6415808A true JPS6415808A (en) 1989-01-19
JPH0677215B2 JPH0677215B2 (en) 1994-09-28

Family

ID=15916220

Family Applications (1)

Application Number Title Priority Date Filing Date
JP62171054A Expired - Lifetime JPH0677215B2 (en) 1987-07-10 1987-07-10 Process identification method

Country Status (1)

Country Link
JP (1) JPH0677215B2 (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08101710A (en) * 1994-09-30 1996-04-16 Babcock Hitachi Kk Operation controller for plant
JP2004199655A (en) * 2002-10-22 2004-07-15 Fisher Rosemount Syst Inc Smart process module and smart process object in process plant
US8427644B2 (en) 2009-07-16 2013-04-23 Mitutoyo Corporation Optical displacement meter
JP2018116441A (en) * 2017-01-17 2018-07-26 富士通株式会社 Processing device, estimation method of adjustment parameter prediction model, and estimation program of adjustment parameter prediction model
WO2018181093A1 (en) * 2017-03-29 2018-10-04 三菱重工業株式会社 Information processing device, information processing method, and program

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08101710A (en) * 1994-09-30 1996-04-16 Babcock Hitachi Kk Operation controller for plant
JP2004199655A (en) * 2002-10-22 2004-07-15 Fisher Rosemount Syst Inc Smart process module and smart process object in process plant
US8427644B2 (en) 2009-07-16 2013-04-23 Mitutoyo Corporation Optical displacement meter
JP2018116441A (en) * 2017-01-17 2018-07-26 富士通株式会社 Processing device, estimation method of adjustment parameter prediction model, and estimation program of adjustment parameter prediction model
WO2018181093A1 (en) * 2017-03-29 2018-10-04 三菱重工業株式会社 Information processing device, information processing method, and program
JP2018169748A (en) * 2017-03-29 2018-11-01 三菱重工業株式会社 Information processing apparatus, information processing method, and program
CN110462539A (en) * 2017-03-29 2019-11-15 三菱重工业株式会社 Information processing unit, information processing method and program
US11429693B2 (en) 2017-03-29 2022-08-30 Mitsubishi Heavy Industries, Ltd. Information processing device, information processing method, and program
US20220366012A1 (en) * 2017-03-29 2022-11-17 Mitsubishi Heavy Industries, Ltd. Information processing device, information processing method, and program

Also Published As

Publication number Publication date
JPH0677215B2 (en) 1994-09-28

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