WO1999014642A1 - Processus d'etalonnage d'un controleur de machine - Google Patents

Processus d'etalonnage d'un controleur de machine Download PDF

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Publication number
WO1999014642A1
WO1999014642A1 PCT/GB1998/002717 GB9802717W WO9914642A1 WO 1999014642 A1 WO1999014642 A1 WO 1999014642A1 GB 9802717 W GB9802717 W GB 9802717W WO 9914642 A1 WO9914642 A1 WO 9914642A1
Authority
WO
WIPO (PCT)
Prior art keywords
machine
model
controller
mean
machine controller
Prior art date
Application number
PCT/GB1998/002717
Other languages
English (en)
Inventor
Julian David Mason
Richard Keith Stobart
Original Assignee
Cambridge Consultants Limited
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 Cambridge Consultants Limited filed Critical Cambridge Consultants Limited
Priority to EP98942860A priority Critical patent/EP1012681A1/fr
Publication of WO1999014642A1 publication Critical patent/WO1999014642A1/fr

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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

Definitions

  • the present invention relates to methods and apparati for calibrating machine controllers.
  • the present invention relates to a method for calibrating a controller which controls an internal combustion (IC) engine.
  • IC internal combustion
  • Such a known controller may have look-up tables in which each dimension of a look-up table corresponds to a particular sensor sensing some functional state of the machine, such that each particular combination of sensor values corresponds to a unique cell in the table.
  • the cells of these look-up tables contain appropriate values for the control inputs to the actuators controlling the machine, depending on the steady state condition of the machine as indicated by the sensor values . Additional compensation may be added to the actuator values when the machine is in a transient condition.
  • Fig. 1 shows a schematic depiction of a typical prior art design process for the design and prototyping of a new engine.
  • a new machine design is typically built up starting from a basis of a combination of readily bespoke parts, assemblies from third parties, components from previous models of the machine and new parts .
  • a design is drawn up and the designers may build phenomenological models of the intended design in order to allow them to predict performance of the machine. It is to be noted that although such phenomenological models are available, many designers do not use them, preferring to use more traditional approaches .
  • phenomenological models are generally based on the physical design characteristics of the machine being designed.
  • Software packages exist which help designers to build such phenomenological models such as the CPowerTM Matlab toolkit produced by Cambridge Consultants Ltd., Cambridge, U.K. Although extremely accurate (the best have resolutions down to sub-cycle periods), these models require long calculation times.
  • look-up tables of the machine controller are subsequently filled in by a manual calibration process involving skilled operators who run the machine and manually adjust actuators which control the machine in order to achieve the desired performance.
  • cell values for the look-up tables are also arrived at for adapted tables for transient machine conditions and for adapted tables which allow, for example, for ageing effects or for particular environment effects, such as for meeting the various different emissions regulations of different countries in the case of IC engines.
  • the engine may be placed on a dynamometer test bed and the skilled operating staff would adjust the various actuators (choke, throttle, ignition advance etc.) and record the appropriate values for use in the look-up table of the engine controller.
  • the prior art machine controller calibration process is very time-consuming, labour-intensive and entails the manufacture and calibration of a plurality of prototype machines.
  • the people involved in this time-consuming process are highly skilled and thus expensive.
  • the time and costs involved in the engine controller calibration process is one of the major factors limiting the introduction of new models of cars .
  • the length of the calibration process also involves opportunity cost and has implications for market share associated with any delays at this stage in the development cycle.
  • the present invention provides a machine controller calibration process for calibrating a machine controller comprising the steps of : i) constructing a phenomenological model of the machine; ii) constructing a non-parametric model of mean-value machine characteristics derived from the phenomenological model; iii) using the non-parametric model for deriving control parameters for the machine controller. whereby, a prototype controller may be derived without the need for manufacturing a physical machine prototype.
  • the present invention provides a method of producing a non-parametric model of a machine which method involves the use of a neural network acting on the mean-value machine characteristics derived from a phenomenological model of the machine.
  • the present invention provides a method for deriving control parameters for a machine controller which involves using a mean-value model of the machine, which mean- value model has been derived from a phenomenological model of the machine, in a computer optimisation scheme to derive the control parameters .
  • the present invention provides a method of automating a machine controller calibration process which involves using a mean-value model of the machine, which mean- value model has been derived from a phenomenological model of the machine, in a computer optimisation scheme to derive the control parameters of the machine controller.
  • the calibration method of the present invention allows machine manufacturers to meet, for instance, short-term emission requirements with reasonable calibration times, in use in conjunction with standard, look-up-table-based control systems.
  • the present invention uses two models to represent the machine - one faster and one slower. This approach means that, whilst the faster non-parametric model does not contatin as much detail as the phenomenological model, it allows a very substantial speeding up of processing and can therefore be used in calibrating a machine controller or designing some form of optimal controller or the like in real time.
  • FIG. 1 A schematic drawing of a prior art engine design process
  • Fig. 2 A schematic drawing of a engine design process incorporating the calibration method of the present invention.
  • Figure 1 depicts a typical prior art engine design process as described above .
  • Figure 2 depicts a typical engine design process using the calibration method of the present invention.
  • the major differences between the design processes of figures 1 and 2 are that: i) the point at which the first physical prototype is built is much later in the design process of figure 2; and ii) the building of the physical prototype is not in an iterative loop in the design process of figure 2, whilst it is in an iterative loop in the design process of figure 1.
  • This is achieved by using a phenomenological model of the engine to enable simulation in software, allowing a mean-value model to be constructed using, for example, a neural network (such as multi-layer perceptrons, Cyberko networks or radial basis function networks) .
  • the mean-value model is then fast enough to use in a computer optimisation scheme, thus enabling the semi- automation of the calibration process.
  • the constructed mean- value model may advantageously be a non-linear model.
  • a machine controller may control only a particular part of a machine and not the whole machine.
  • the current invention is also meant for use in such circumstances - a 'machine controller' is intended to be interpreted as a controller of a machine or of some sub-system thereof. Examples of such sub-system controllers might be for controlling exhaust gas recirculation or for controlling a variable geometry turbocharger or for controlling electronic fuel injection etc.

Abstract

La présente invention concerne un procédé permettant de dériver des paramètres de commande pour un contrôleur de machine, lequel procédé consiste à utiliser un modèle de valeur moyenne de la machine dans un schéma d'optimisation informatique pour dériver les paramètres de commande. Le modèle de valeur moyenne est dérivé d'un modèle phénoménologique de la machine.
PCT/GB1998/002717 1997-09-12 1998-09-11 Processus d'etalonnage d'un controleur de machine WO1999014642A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP98942860A EP1012681A1 (fr) 1997-09-12 1998-09-11 Processus d'etalonnage d'un controleur de machine

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP97307113 1997-09-12
EP97307113.7 1997-09-12

Publications (1)

Publication Number Publication Date
WO1999014642A1 true WO1999014642A1 (fr) 1999-03-25

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/GB1998/002717 WO1999014642A1 (fr) 1997-09-12 1998-09-11 Processus d'etalonnage d'un controleur de machine

Country Status (2)

Country Link
EP (1) EP1012681A1 (fr)
WO (1) WO1999014642A1 (fr)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001025863A1 (fr) * 1999-10-05 2001-04-12 Aspen Technology, Inc. Procede informatique et appareil pour determiner l'etat de proprietes physiques dans un processus chimique
WO2002003152A2 (fr) * 2000-06-29 2002-01-10 Aspen Technology, Inc. Procede informatique et appareil de contrainte d'un approximateur non lineaire d'un processus empirique
US6862562B1 (en) 1999-10-05 2005-03-01 Aspen Technology, Inc. Computer method and apparatus for determining state of physical properties in a chemical process
CN103631152A (zh) * 2013-11-26 2014-03-12 南京航空航天大学 发动机控制器硬件在环仿真扭矩/转速复合信号模拟方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1997042553A1 (fr) * 1996-05-06 1997-11-13 Pavilion Technologies, Inc. Procede et dispositif pour modeliser des processus dynamiques et statiques aux fins de prediction, commande et optimisation

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1997042553A1 (fr) * 1996-05-06 1997-11-13 Pavilion Technologies, Inc. Procede et dispositif pour modeliser des processus dynamiques et statiques aux fins de prediction, commande et optimisation

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
KRAUTH J ET AL: "SIMULATION UND KUNSTLICHE INTELLIGENZ EIN UBERBLICK", IT + TI INFORMATIONSTECHNIK UND TECHNISCHE INFORMATIK, vol. 35, no. 6, 1 December 1993 (1993-12-01), pages 5 - 9, XP000423141 *
SUNG HOON JUNG ET AL: "EVENT-BASED INTELLIGENT CONTROL OF SATURATED CHEMICAL PLANT USING ENDOMORPHIC NEURAL NETWORK MODEL", PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL, COLUMBUS, AUG. 16 - 18, 1994, 16 August 1994 (1994-08-16), INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages 279 - 284, XP000549590 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001025863A1 (fr) * 1999-10-05 2001-04-12 Aspen Technology, Inc. Procede informatique et appareil pour determiner l'etat de proprietes physiques dans un processus chimique
US6862562B1 (en) 1999-10-05 2005-03-01 Aspen Technology, Inc. Computer method and apparatus for determining state of physical properties in a chemical process
WO2002003152A2 (fr) * 2000-06-29 2002-01-10 Aspen Technology, Inc. Procede informatique et appareil de contrainte d'un approximateur non lineaire d'un processus empirique
WO2002003152A3 (fr) * 2000-06-29 2002-07-25 Aspen Technology Inc Procede informatique et appareil de contrainte d'un approximateur non lineaire d'un processus empirique
US7330804B2 (en) 2000-06-29 2008-02-12 Aspen Technology, Inc. Computer method and apparatus for constraining a non-linear approximator of an empirical process
US7630868B2 (en) 2000-06-29 2009-12-08 Aspen Technology, Inc. Computer method and apparatus for constraining a non-linear approximator of an empirical process
US8296107B2 (en) 2000-06-29 2012-10-23 Aspen Technology, Inc. Computer method and apparatus for constraining a non-linear approximator of an empirical process
CN103631152A (zh) * 2013-11-26 2014-03-12 南京航空航天大学 发动机控制器硬件在环仿真扭矩/转速复合信号模拟方法

Also Published As

Publication number Publication date
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