DK0771441T3 - Method and device for applying fuzzy logic to automation systems - Google Patents

Method and device for applying fuzzy logic to automation systems

Info

Publication number
DK0771441T3
DK0771441T3 DK95924845T DK95924845T DK0771441T3 DK 0771441 T3 DK0771441 T3 DK 0771441T3 DK 95924845 T DK95924845 T DK 95924845T DK 95924845 T DK95924845 T DK 95924845T DK 0771441 T3 DK0771441 T3 DK 0771441T3
Authority
DK
Denmark
Prior art keywords
membership function
fuzzy
changed
fuzzy logic
automation systems
Prior art date
Application number
DK95924845T
Other languages
Danish (da)
Inventor
Thomas Wolf
Herbert Furumoto
Original Assignee
Siemens Ag
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 Siemens Ag filed Critical Siemens Ag
Application granted granted Critical
Publication of DK0771441T3 publication Critical patent/DK0771441T3/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/02—Computing arrangements based on specific mathematical models using fuzzy logic
    • G06N7/023—Learning or tuning the parameters of a fuzzy system
    • 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
    • G05B13/0275—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 fuzzy logic only
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00—Climate change mitigation technologies for sector-wide applications
    • Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier

Landscapes

  • Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Automation & Control Theory (AREA)
  • Fuzzy Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Evolutionary Computation (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Pure & Applied Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Biomedical Technology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Computational Mathematics (AREA)
  • Algebra (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Feedback Control In General (AREA)
  • Logic Circuits (AREA)
  • Control Of Non-Electrical Variables (AREA)

Abstract

Fuzzy systems normally assume a predetermined and invariable membership function for the individual linguistic variables, the form and value range of the membership function being prescribed. According to the invention, individual elements in the fuzzy system such as membership functions, rules, rule weightings and the like can be changed by the automation system itself. Preferably at least one membership function is changed on-line during the operation of the automation system. In the associated arrangement with at least one fuzzy system with inputs and outputs, the software module (1, 2) responsible for fuzzyfication receives at least one additional input (30, 40-50). The proposed method and associated arrangement can be used advantageously to optimize energy consumption in factories or to control water circulation systems.
DK95924845T 1994-07-20 1995-07-07 Method and device for applying fuzzy logic to automation systems DK0771441T3 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE4425674 1994-07-20
PCT/DE1995/000894 WO1996002880A1 (en) 1994-07-20 1995-07-07 Method and arrangement for using fuzzy logic in automation systems

Publications (1)

Publication Number Publication Date
DK0771441T3 true DK0771441T3 (en) 1999-07-12

Family

ID=6523677

Family Applications (1)

Application Number Title Priority Date Filing Date
DK95924845T DK0771441T3 (en) 1994-07-20 1995-07-07 Method and device for applying fuzzy logic to automation systems

Country Status (9)

Country Link
EP (1) EP0771441B1 (en)
JP (1) JPH10504121A (en)
CN (1) CN1152964A (en)
AT (1) ATE172801T1 (en)
DE (1) DE59504092D1 (en)
DK (1) DK0771441T3 (en)
ES (1) ES2123999T3 (en)
FI (1) FI970180A0 (en)
WO (1) WO1996002880A1 (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5774630A (en) * 1995-11-21 1998-06-30 Samsung Electronics Co., Ltd. Parameter set up method of membership functions for fuzzy control of washing machine motor
US6112301A (en) * 1997-01-15 2000-08-29 International Business Machines Corporation System and method for customizing an operating system
CN102622000B (en) * 2012-03-30 2015-04-15 齐鲁工业大学 Fuzzy neural network-based slurry supply system flow control method
US10838376B2 (en) * 2015-09-10 2020-11-17 I.Systems Automação Industrial S.A Method of generating fuzzy knowledge base for a programmable fuzzy controller
DE102016009257A1 (en) * 2016-07-29 2018-02-01 Lucas Automotive Gmbh Fuzzy-based control system in a motor vehicle for controlling a speed of the motor vehicle or a brake pressure of a brake of the motor vehicle
CN108388121B (en) * 2018-03-06 2020-11-10 辽宁天安科技有限公司 Fuzzy logic control method of mechanical movable sieve jig
CN113700533B (en) * 2021-07-19 2022-05-20 西安交通大学 Double-extraction steam turbine decoupling adjusting system and control method thereof
CN113762932B (en) * 2021-09-14 2024-04-12 南京林洋电力科技有限公司 Automatic configuration APP management method based on fuzzy algorithm

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2110826C1 (en) * 1989-08-31 1998-05-10 Омрон Корпорейшн Method for generation of fuzzy control, device which implements said method, control method and system which implements said method
JP2763369B2 (en) * 1990-03-12 1998-06-11 富士通株式会社 How to tune fuzzy control rules
US5295061A (en) * 1990-04-20 1994-03-15 Sanyo Electric Co., Ltd. Control parameter tuning unit and a method of tuning parameters for a control unit

Also Published As

Publication number Publication date
FI970180A (en) 1997-01-16
JPH10504121A (en) 1998-04-14
ES2123999T3 (en) 1999-01-16
FI970180A0 (en) 1997-01-16
WO1996002880A1 (en) 1996-02-01
CN1152964A (en) 1997-06-25
EP0771441A1 (en) 1997-05-07
EP0771441B1 (en) 1998-10-28
DE59504092D1 (en) 1998-12-03
ATE172801T1 (en) 1998-11-15

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