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WO1996009573A3 - Dispositif pour la commande adaptative d'une section - Google Patents

Dispositif pour la commande adaptative d'une section Download PDF

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Publication number
WO1996009573A3
WO1996009573A3 PCT/DE1995/001223 DE9501223W WO9609573A3 WO 1996009573 A3 WO1996009573 A3 WO 1996009573A3 DE 9501223 W DE9501223 W DE 9501223W WO 9609573 A3 WO9609573 A3 WO 9609573A3
Authority
WO
WIPO (PCT)
Prior art keywords
section
neural network
parameters
sampled values
arrangement
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.)
Ceased
Application number
PCT/DE1995/001223
Other languages
German (de)
English (en)
Other versions
WO1996009573A2 (fr
Inventor
Hans-Peter Preuss
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.)
Siemens AG
Siemens Corp
Original Assignee
Siemens AG
Siemens 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 Siemens AG, Siemens Corp filed Critical Siemens AG
Publication of WO1996009573A2 publication Critical patent/WO1996009573A2/fr
Publication of WO1996009573A3 publication Critical patent/WO1996009573A3/fr
Anticipated expiration legal-status Critical
Ceased 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
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Feedback Control In General (AREA)

Abstract

L'invention concerne un dispositif pour la commande adaptative d'une section (3), comprenant un système de prétraitement de signal (4), au moyen duquel, à partir de la variation, dans le temps, de la grandeur contrôlée (x), des valeurs échantillonnées (a) peuvent être produites, et un réseau neuronal (5) calculant les paramètres (Kp, Tn, Tv) de l'unité de régulation (2) en fonction des valeurs échantillonnées (a). Le réseau neuronal (5) est entraîné au moyen des données apprises des paramètres (Kp, Tn, Tv) et des valeurs échantillonnées (a) de la réponse transitoire de section qui sont générées par des régulateurs de paramètres calculés analytiquement ou par une simulation de circuit de commande ou une optimisation numérique pour un ou plusieurs modèles de la section. Le réseau neuronal (5) fournit ainsi aux données apprises, des paramètres de contrôle optimum qui sont bien appropriés aux valeurs intermédiaires en raison de ses propriétés de généralisation. L'invention est appliquée dans la technologie d'automatisation.
PCT/DE1995/001223 1994-09-19 1995-09-07 Dispositif pour la commande adaptative d'une section Ceased WO1996009573A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19944433332 DE4433332A1 (de) 1994-09-19 1994-09-19 Einrichtung zur adaptiven Regelung einer Strecke
DEP4433332.3 1994-09-19

Publications (2)

Publication Number Publication Date
WO1996009573A2 WO1996009573A2 (fr) 1996-03-28
WO1996009573A3 true WO1996009573A3 (fr) 1996-05-30

Family

ID=6528585

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/DE1995/001223 Ceased WO1996009573A2 (fr) 1994-09-19 1995-09-07 Dispositif pour la commande adaptative d'une section

Country Status (2)

Country Link
DE (1) DE4433332A1 (fr)
WO (1) WO1996009573A2 (fr)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5847952A (en) * 1996-06-28 1998-12-08 Honeywell Inc. Nonlinear-approximator-based automatic tuner
DE10302585B4 (de) * 2003-01-22 2004-12-30 Endress + Hauser Wetzer Gmbh + Co Kg Verfahren zum Einstellen eines Reglers
EP3825788B1 (fr) * 2019-11-19 2022-11-09 Asco Numatics GmbH Dispositif de réglage, système de réglage et procédé de réglage d'une grandeur physique d'un fluide

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03201008A (ja) * 1989-12-28 1991-09-02 Toshiba Corp ゲインスケジューリング制御装置
WO1993012476A1 (fr) * 1991-12-18 1993-06-24 Honeywell Inc. Syntoniseur automatique a reseau neuronal en boucle fermee

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03201008A (ja) * 1989-12-28 1991-09-02 Toshiba Corp ゲインスケジューリング制御装置
WO1993012476A1 (fr) * 1991-12-18 1993-06-24 Honeywell Inc. Syntoniseur automatique a reseau neuronal en boucle fermee

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
PATENT ABSTRACTS OF JAPAN vol. 015, no. 469 (P - 1281) 27 November 1991 (1991-11-27) *
SWINIARSKI R W: "NOVEL NEURAL NETWORK BASED SELF-TUNING PID CONTROLLER WHICH USES PATTERN RECOGNITION TECHNIQUE", PROCEEDINGS OF THE AMERICAN CONTROL CONFERENCE, SAN DIEGO, MAY 23 - 25, 1990, vol. 3, 23 May 1990 (1990-05-23), INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages 3023 - 3024, XP000170168 *

Also Published As

Publication number Publication date
DE4433332A1 (de) 1996-03-21
WO1996009573A2 (fr) 1996-03-28

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