WO2024013465A3 - Pid tuning - Google Patents

Pid tuning Download PDF

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Publication number
WO2024013465A3
WO2024013465A3 PCT/GB2023/051677 GB2023051677W WO2024013465A3 WO 2024013465 A3 WO2024013465 A3 WO 2024013465A3 GB 2023051677 W GB2023051677 W GB 2023051677W WO 2024013465 A3 WO2024013465 A3 WO 2024013465A3
Authority
WO
WIPO (PCT)
Prior art keywords
pid
terms
determining
physical parameter
pid tuning
Prior art date
Application number
PCT/GB2023/051677
Other languages
French (fr)
Other versions
WO2024013465A2 (en
Inventor
Zacharaya Omar SHABKA
Georgios ZERVAS
Original Assignee
Ucl Business 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 Ucl Business Ltd filed Critical Ucl Business Ltd
Publication of WO2024013465A2 publication Critical patent/WO2024013465A2/en
Publication of WO2024013465A3 publication Critical patent/WO2024013465A3/en

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
    • 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
    • G05B11/00—Automatic controllers
    • G05B11/01—Automatic controllers electric
    • G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/092—Reinforcement learning
    • 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
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/42—Servomotor, servo controller kind till VSS
    • G05B2219/42018—Pid learning controller, gains adapted as function of previous error
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Automation & Control Theory (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Biomedical Technology (AREA)
  • Feedback Control In General (AREA)

Abstract

A method for determining proportional-integral-derivative, PID, terms for use in a PID-controlled system comprising a device, a sensor configured to sense information associated with the device, and a controller configured to control the device based on closed-loop control using the sensed information and the PID terms, the method comprising: obtaining a physical parameter indicative of a physical property of the device; and determining, based on applying a machine learning technique to the physical parameter, the PID terms.
PCT/GB2023/051677 2022-07-15 2023-06-27 Pid tuning WO2024013465A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB2210433.5A GB2620635A (en) 2022-07-15 2022-07-15 PID tuning
GB2210433.5 2022-07-15

Publications (2)

Publication Number Publication Date
WO2024013465A2 WO2024013465A2 (en) 2024-01-18
WO2024013465A3 true WO2024013465A3 (en) 2024-02-29

Family

ID=84540290

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/GB2023/051677 WO2024013465A2 (en) 2022-07-15 2023-06-27 Pid tuning

Country Status (2)

Country Link
GB (1) GB2620635A (en)
WO (1) WO2024013465A2 (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0907909B1 (en) * 1996-06-28 2000-05-03 Honeywell Inc. Nonlinear-approximator-based automatic tuner
US20190187631A1 (en) * 2017-12-15 2019-06-20 Exxonmobil Research And Engineering Company Adaptive pid controller tuning via deep reinforcement learning
US20210132587A1 (en) * 2019-11-04 2021-05-06 Honeywell International Inc. Application of simple random search approach for reinforcement learning to controller tuning parameters

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3551410A4 (en) * 2016-12-12 2020-08-19 Services Petroliers Schlumberger Automated cement mixing
JP6680756B2 (en) * 2017-12-26 2020-04-15 ファナック株式会社 Control device and machine learning device
WO2020137802A1 (en) * 2018-12-28 2020-07-02 株式会社荏原製作所 Pad temperature adjusting device, pad temperature adjusting method, polishing device, and polishing system
US11796977B2 (en) * 2020-04-29 2023-10-24 Honeywell International Inc. PID controller autotuner using machine learning approaches

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0907909B1 (en) * 1996-06-28 2000-05-03 Honeywell Inc. Nonlinear-approximator-based automatic tuner
US20190187631A1 (en) * 2017-12-15 2019-06-20 Exxonmobil Research And Engineering Company Adaptive pid controller tuning via deep reinforcement learning
US20210132587A1 (en) * 2019-11-04 2021-05-06 Honeywell International Inc. Application of simple random search approach for reinforcement learning to controller tuning parameters

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
DANIEL Y ABRAMOVITCH ET AL: "Semi-automatic tuning of PID gains for atomic force microscopes", ASIAN JOURNAL OF CONTROL, CHINESE AUTOMATIC CONTROL SOCIETY, HOBOKEN, USA, vol. 11, no. 2, 27 April 2009 (2009-04-27), pages 188 - 195, XP072336443, ISSN: 1561-8625, DOI: 10.1002/ASJC.95 *

Also Published As

Publication number Publication date
GB2620635A (en) 2024-01-17
WO2024013465A2 (en) 2024-01-18
GB202210433D0 (en) 2022-08-31

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