CN103116283A - Method for controlling dynamic matrix of non-self-balance object - Google Patents

Method for controlling dynamic matrix of non-self-balance object Download PDF

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Publication number
CN103116283A
CN103116283A CN 201310018116 CN201310018116A CN103116283A CN 103116283 A CN103116283 A CN 103116283A CN 201310018116 CN201310018116 CN 201310018116 CN 201310018116 A CN201310018116 A CN 201310018116A CN 103116283 A CN103116283 A CN 103116283A
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constantly
matrix
model
value
controlled device
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张日东
吴胜
陈霄
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Hangzhou Dianzi University
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Hangzhou Dianzi University
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Abstract

The invention relates to a method for controlling a dynamic matrix of a non-self-balance object. A traditional matrix control algorithm cannot directly be used on the non-self-balance object. On the base of the traditional matrix control algorithm, the method combines a method for changing and transferring a matrix for the non-self-balance object and a novel error rectification method, guarantees that control is highly precise and highly stable, and at the same time guarantees simple forms, and meets demands in actual industrial process. The method is adopted to firstly establish a matrix model for the non-self-balance object based on step response data of the object and excavate out a basic object character; and then combines the novel method for transferring the matrix and the method for compensating error to calculate out a parameter of a dynamic matrix controller; and at last complements dynamic matrix control for the non-self-balance object. Means like data collection, model establishment, and mechanism forecasting are adopted in the method for controlling the dynamic matrix of the non-self-balance object, and the method is adopted to effectively improve precision and stability of the control.

Description

A kind of non-dynamic matrix control method from the object that weighs
Technical field
The invention belongs to technical field of automation, relate to a kind of non-dynamic matrix control method from the object that weighs.
Background technology
Exist many non-from weighing object, as a part of storage tank, boiler drum level, rectification column liquid level etc. in actual industrial production.During industrial process is controlled, contain typical integral element due to non-in the transport function of the object that weighs, cause the response of controlled device under the definite value step to be tending towards infinite, this just makes traditional Dynamic array control algorithm directly to use on the object that weighs non-.In existing control method, the interference that on the one hand a lot of algorithms can not allow the controlled device opposing continue; A part of algorithm modeling process too complex on the other hand, these all make non-control from the object that weighs have certain difficulty.
Summary of the invention
The objective of the invention is the weak point for existing some algorithm, a kind of non-dynamic matrix control method from the object that weighs is provided, the method is on the basis of conventional dynamic matrix control algolithm, combine a kind of method and a kind of new error calibration method that is directed to the change transition matrix of the non-object that certainly weighs, guarantee to control have higher precision and stability in, the form that also guarantees is simple and satisfy the needs of actual industrial process.
The at first object-based step response data of the inventive method is set up a kind of non-matrix model from the object that weighs that is directed to, and excavates basic plant characteristic; Then the parameter of removing to calculate the dynamic matrix control device in conjunction with a kind of new transition matrix and error compensation way; Implement dynamic matrix control to non-from the object that weighs at last.
Technical scheme of the present invention is to set up, predict the means such as mechanism, optimization by data acquisition, model, has established a kind of non-dynamic matrix control method from the object that weighs, and utilizes the method can effectively improve the precision and stability of control.
The step of the inventive method comprises:
Step (1). set up corresponding dynamic matrix model vector by non-real-time step response data from the object that weighs, concrete grammar is:
I. give step input signal of controlled device, record the step response curve of controlled device.
II. the step response curve of correspondence is carried out the filtering processing, then fit to a smooth curve, record step response data corresponding to each sampling instant on smooth curve, first sampling instant is
Figure 2013100181163100002DEST_PATH_IMAGE002
, adjacent two sampling instant interludes are
Figure 307902DEST_PATH_IMAGE002
, sampling instant is sequentially
Figure 590985DEST_PATH_IMAGE002
, 2
Figure 240272DEST_PATH_IMAGE002
, 3
Figure 105460DEST_PATH_IMAGE002
Find out data and begin to be the starting point that constant-slope rises in the step response data of record
Figure 2013100181163100002DEST_PATH_IMAGE004
, data are before remembered respectively and are done
Figure 2013100181163100002DEST_PATH_IMAGE006
, set up the model vector of object
Figure 2013100181163100002DEST_PATH_IMAGE008
:
Figure 2013100181163100002DEST_PATH_IMAGE010
Figure 2013100181163100002DEST_PATH_IMAGE012
Wherein
Figure 2013100181163100002DEST_PATH_IMAGE014
Be the transpose of a matrix symbol;
Figure 2013100181163100002DEST_PATH_IMAGE016
Be step response data constant difference between adjacent two data after being constant slope and rising;
Figure DEST_PATH_IMAGE018
Be the model length of setting,
Step (2). design non-dynamic matrix control device from the object that weighs, concrete grammar is:
A. utilize the model vector that obtains above
Figure 431268DEST_PATH_IMAGE008
Set up the dynamic matrix of controlled device, form is as follows:
Figure DEST_PATH_IMAGE022
Wherein,
Figure DEST_PATH_IMAGE024
It is the step response data by controlled device
Figure DEST_PATH_IMAGE026
Form
Figure DEST_PATH_IMAGE028
Dynamic matrix;
Figure DEST_PATH_IMAGE030
The optimization time domain of Dynamic array control algorithm,
Figure DEST_PATH_IMAGE032
The control time domain of Dynamic array control algorithm,
Figure DEST_PATH_IMAGE034
B. set up controlled device current
Figure DEST_PATH_IMAGE036
Model prediction free response value constantly
Wherein,
Figure DEST_PATH_IMAGE044
Figure DEST_PATH_IMAGE046
For
Figure DEST_PATH_IMAGE048
Constantly right
Figure DEST_PATH_IMAGE050
Model prediction free response value constantly,
Figure DEST_PATH_IMAGE052
For
Figure 198717DEST_PATH_IMAGE048
Input control increment size constantly,
Figure DEST_PATH_IMAGE054
For The real output value of the controlled device that constantly detects,
Figure DEST_PATH_IMAGE056
For
Figure 558340DEST_PATH_IMAGE036
The model predictive error value of moment controlled device,
Figure DEST_PATH_IMAGE058
Be the error correction coefficient,
Figure DEST_PATH_IMAGE060
Figure DEST_PATH_IMAGE062
Be the matrix of step response data foundation,
Figure DEST_PATH_IMAGE064
Be constant matrices,
Figure DEST_PATH_IMAGE066
With
Figure DEST_PATH_IMAGE068
Be the weight matrix of error compensation;
Figure DEST_PATH_IMAGE070
For
Figure DEST_PATH_IMAGE072
New transition matrix;
Figure DEST_PATH_IMAGE074
For
Figure 428950DEST_PATH_IMAGE048
Moment access control increment
Figure 437358DEST_PATH_IMAGE052
After model predication value, be also Initial model predicted value constantly; Wherein
Figure DEST_PATH_IMAGE076
Be illustrated respectively in Constantly right
Figure 437303DEST_PATH_IMAGE050
Initial model predicted value constantly;
Figure DEST_PATH_IMAGE078
For
Figure 916695DEST_PATH_IMAGE036
Constantly through the optimization model predicted value after error correction; Wherein
Figure DEST_PATH_IMAGE080
Be illustrated respectively in
Figure 420399DEST_PATH_IMAGE036
Constantly right
Figure 239319DEST_PATH_IMAGE050
Optimization model predicted value is constantly namely passed through error correction model predication value afterwards;
For
Figure 686929DEST_PATH_IMAGE036
Constantly right
Figure DEST_PATH_IMAGE082
Model prediction free response value constantly; Wherein
Figure DEST_PATH_IMAGE084
Be illustrated respectively in
Figure 456040DEST_PATH_IMAGE036
Constantly right
Figure 67150DEST_PATH_IMAGE082
Model prediction free response value constantly.
C. the dynamic matrix of setting up according to step a calculates controlled device and exists
Figure 778360DEST_PATH_IMAGE032
Individual continuous controlling increment
Figure DEST_PATH_IMAGE086
Under prediction output
Figure DEST_PATH_IMAGE088
, concrete grammar is:
Wherein,
Figure DEST_PATH_IMAGE092
Be
Figure 668562DEST_PATH_IMAGE038
Before
Figure 493561DEST_PATH_IMAGE030
,
Figure DEST_PATH_IMAGE094
Figure DEST_PATH_IMAGE096
For
Figure 769297DEST_PATH_IMAGE036
Constantly right
Figure DEST_PATH_IMAGE098
Model prediction output valve constantly.
D. set up non-reference locus from the object dynamic matrix control device that weighs
Figure DEST_PATH_IMAGE100
And objective function
Figure DEST_PATH_IMAGE102
Wherein,
Figure DEST_PATH_IMAGE108
Be each output reference locus constantly; Be
Figure DEST_PATH_IMAGE112
Respectively the weight matrix of error and controlling increment, And
Figure DEST_PATH_IMAGE116
Be respectively the coefficient of corresponding weight matrix the inside.
E. the objective function according to steps d obtains current controlling increment value
Figure DEST_PATH_IMAGE118
F. will
Figure 962994DEST_PATH_IMAGE118
In first Consist of the working control amount
Figure DEST_PATH_IMAGE124
Act on object.
Wherein,
Figure DEST_PATH_IMAGE126
With
Figure DEST_PATH_IMAGE128
Be respectively Constantly and
Figure 142751DEST_PATH_IMAGE048
Constantly act on the working control amount of controlled device.
G. arrive next constantly, continue to find the solution to the step of f according to b
Figure DEST_PATH_IMAGE130
, circulation successively.
A kind of non-dynamic matrix control method from the object that weighs that the present invention proposes has made up the deficiency of traditional control algolithm, can resist fast and effectively various interference when satisfying system performance.
The control technology that the present invention proposes can be applied to traditional Dynamic array control algorithm non-on the object that weighs, when object is subject to unpredictable and lasting interference, can effectively utilize non-error compensation of carrying out correspondence from the Properties of Objects that weighs, system stability is effectively moved.
Embodiment
Take general predictive control as example:
Boiler drum level is typical non-from the object that weighs with integral element, and steam water-level is also one of important parameter that characterizes safe operation of the boiler.
Step (1). obtain the model vector of boiler drum level.
The first step: under manual mode, in the situation that the constant step response curve that obtains steam water-level by regulating feed-regulating valve of steam load, the step response curve of correspondence is carried out the filtering processing, then fit to a smooth curve, record step response data corresponding to each sampling instant on smooth curve, first sampling instant is , adjacent two sampling instant interludes are
Figure 906100DEST_PATH_IMAGE002
, sampling instant is sequentially , 2 , 3
Figure 190953DEST_PATH_IMAGE002
Find out data and begin to be the starting point that constant-slope rises in the step response data of record
Figure 463803DEST_PATH_IMAGE004
, data are before remembered respectively and are done
Figure 881140DEST_PATH_IMAGE006
Second step: choose a suitable model length
Figure 897638DEST_PATH_IMAGE018
,
Figure 582566DEST_PATH_IMAGE020
, the step response data that obtains according to the first step is set up the model vector of boiler drum level ,
Figure 951458DEST_PATH_IMAGE012
, wherein Be the transpose of a matrix symbol,
Figure 124130DEST_PATH_IMAGE016
For data be constant slope and rise after a constant difference between adjacent two step response data.
Step (2). the dynamic matrix control device of design boiler drum level, concrete grammar is:
A. utilize the model vector that obtains in (1) to set up the dynamic matrix of boiler drum level, form is as follows:
Figure 253629DEST_PATH_IMAGE022
Wherein,
Figure 629247DEST_PATH_IMAGE024
It is the step response data by boiler drum level Form Dynamic matrix;
Figure 335483DEST_PATH_IMAGE030
The optimization time domain of Dynamic array control algorithm,
Figure 121036DEST_PATH_IMAGE032
The control time domain of Dynamic array control algorithm,
Figure 46267DEST_PATH_IMAGE034
B. set up boiler drum level current
Figure 956060DEST_PATH_IMAGE036
Model prediction free response value constantly
Figure 220820DEST_PATH_IMAGE038
Figure 692121DEST_PATH_IMAGE040
Wherein,
Figure 674749DEST_PATH_IMAGE046
For
Figure 254635DEST_PATH_IMAGE048
Constantly right
Figure 154458DEST_PATH_IMAGE050
The model prediction free response value of boiler drum level constantly,
Figure 658251DEST_PATH_IMAGE052
For
Figure 379826DEST_PATH_IMAGE048
The input control increment size of the water-supply valve valve opening that the moment is corresponding,
Figure 943663DEST_PATH_IMAGE054
For
Figure 517732DEST_PATH_IMAGE036
The real output value of the boiler drum level that constantly detects, For
Figure 715813DEST_PATH_IMAGE036
The model predictive error value of moment boiler drum level,
Figure 201283DEST_PATH_IMAGE058
Be the error correction coefficient,
Figure 747802DEST_PATH_IMAGE060
Figure 108245DEST_PATH_IMAGE062
Be the matrix of step response data foundation,
Figure 56609DEST_PATH_IMAGE064
Be constant matrices,
Figure 710051DEST_PATH_IMAGE066
With
Figure 806183DEST_PATH_IMAGE068
Be the weight matrix of error compensation;
Figure 189891DEST_PATH_IMAGE070
For
Figure 507609DEST_PATH_IMAGE072
New transition matrix;
For
Figure 855993DEST_PATH_IMAGE048
Moment access control increment
Figure 43392DEST_PATH_IMAGE052
After the model predication value of boiler drum level, be also
Figure 215616DEST_PATH_IMAGE036
The initial model predicted value of boiler drum level constantly; Wherein
Figure 525375DEST_PATH_IMAGE076
Be illustrated respectively in Constantly right
Figure 272674DEST_PATH_IMAGE050
Initial model predicted value constantly;
Figure 50137DEST_PATH_IMAGE078
For
Figure 717748DEST_PATH_IMAGE036
The optimization model predicted value of the boiler drum level after process error correction constantly; Wherein Be illustrated respectively in Constantly right
Figure 187672DEST_PATH_IMAGE050
Optimization model predicted value is constantly namely passed through error correction model predication value afterwards;
Figure 776916DEST_PATH_IMAGE038
For
Figure 9183DEST_PATH_IMAGE036
Constantly right
Figure 342076DEST_PATH_IMAGE082
Model prediction free response value constantly; Wherein
Figure 576354DEST_PATH_IMAGE084
Be illustrated respectively in
Figure 664396DEST_PATH_IMAGE036
Constantly right
Figure 869113DEST_PATH_IMAGE082
Model prediction free response value constantly.
C. the dynamic matrix of setting up according to step a calculates boiler drum level and exists
Figure 989384DEST_PATH_IMAGE032
Individual continuous controlling increment
Figure 595946DEST_PATH_IMAGE086
Under prediction output
Figure 543305DEST_PATH_IMAGE088
, concrete grammar is:
Figure 969738DEST_PATH_IMAGE090
Wherein,
Figure 159280DEST_PATH_IMAGE092
Be
Figure 682665DEST_PATH_IMAGE038
Before
Figure 784613DEST_PATH_IMAGE030
,
Figure 711724DEST_PATH_IMAGE094
Figure 190110DEST_PATH_IMAGE096
For
Figure 754953DEST_PATH_IMAGE036
Constantly right
Figure 293381DEST_PATH_IMAGE098
Model prediction output valve constantly.
D. set up the reference locus of boiler drum level dynamic matrix control device
Figure 756724DEST_PATH_IMAGE100
And objective function
Figure 789533DEST_PATH_IMAGE102
Figure 225193DEST_PATH_IMAGE104
Wherein,
Figure 72113DEST_PATH_IMAGE108
Be each output reference locus constantly;
Figure 640104DEST_PATH_IMAGE110
Be
Figure 992588DEST_PATH_IMAGE112
Respectively the weight matrix of error and controlling increment,
Figure 607240DEST_PATH_IMAGE114
And
Figure 232125DEST_PATH_IMAGE116
Be respectively the coefficient of corresponding weight matrix the inside.
E. the objective function according to steps d obtains current controlling increment value
F. will
Figure 864860DEST_PATH_IMAGE118
In first
Figure 727774DEST_PATH_IMAGE122
Consist of the working control amount
Figure 139032DEST_PATH_IMAGE124
Act on the feed-regulating valve of boiler.Wherein,
Figure 112715DEST_PATH_IMAGE126
With
Figure 397066DEST_PATH_IMAGE128
Be respectively
Figure 481696DEST_PATH_IMAGE036
Constantly and
Figure 696646DEST_PATH_IMAGE048
Constantly act on the working control amount of feed-regulating valve.
G. arrive next constantly, repetition b continues to find the solution to the step of f
Figure 815912DEST_PATH_IMAGE130
, circulation successively.

Claims (1)

  1. One kind non-from weighing the dynamic matrix control method of object, it is characterized in that the concrete steps of the method are:
    Step (1). set up corresponding dynamic matrix model vector by non-real-time step response data from the object that weighs, concrete grammar is:
    I. give step input signal of controlled device, record the step response curve of controlled device;
    II. the step response curve of correspondence is carried out the filtering processing, then fit to a smooth curve, record step response data corresponding to each sampling instant on smooth curve, first sampling instant is
    Figure 266624DEST_PATH_IMAGE001
    , adjacent two sampling instant interludes are
    Figure 168721DEST_PATH_IMAGE001
    , sampling instant is sequentially
    Figure 649381DEST_PATH_IMAGE001
    , 2 , 3
    Figure 674286DEST_PATH_IMAGE001
    Find out data and begin to be the starting point that constant-slope rises in the step response data of record
    Figure 181622DEST_PATH_IMAGE002
    , data are before remembered respectively and are done
    Figure 161079DEST_PATH_IMAGE003
    , set up the model vector of object
    Figure 940816DEST_PATH_IMAGE004
    :
    Figure 146145DEST_PATH_IMAGE005
    Figure 22834DEST_PATH_IMAGE006
    Wherein
    Figure 658346DEST_PATH_IMAGE007
    Be the transpose of a matrix symbol;
    Figure 987696DEST_PATH_IMAGE008
    Be step response data constant difference between adjacent two data after being constant slope and rising;
    Figure 999646DEST_PATH_IMAGE009
    Be the model length of setting,
    Figure 730841DEST_PATH_IMAGE010
    Step (2). design non-dynamic matrix control device from the object that weighs, concrete grammar is:
    A. utilize the model vector that obtains above
    Figure 724205DEST_PATH_IMAGE004
    Set up the dynamic matrix of controlled device, form is as follows:
    Wherein,
    Figure 90913DEST_PATH_IMAGE012
    It is the step response data by controlled device
    Figure 424417DEST_PATH_IMAGE013
    Form
    Figure 916579DEST_PATH_IMAGE014
    Dynamic matrix;
    Figure 971253DEST_PATH_IMAGE015
    The optimization time domain of Dynamic array control algorithm,
    Figure 308694DEST_PATH_IMAGE016
    The control time domain of Dynamic array control algorithm,
    Figure 952165DEST_PATH_IMAGE017
    B. set up controlled device current Model prediction free response value constantly
    Figure 891619DEST_PATH_IMAGE019
    Figure 783483DEST_PATH_IMAGE020
    Wherein,
    Figure 281460DEST_PATH_IMAGE021
    Figure 115424DEST_PATH_IMAGE022
    Figure 876182DEST_PATH_IMAGE023
    For
    Figure 758687DEST_PATH_IMAGE024
    Constantly right
    Figure 173488DEST_PATH_IMAGE025
    Model prediction free response value constantly,
    Figure 929086DEST_PATH_IMAGE026
    For
    Figure 367020DEST_PATH_IMAGE024
    Input control increment size constantly,
    Figure 849954DEST_PATH_IMAGE027
    For
    Figure 135573DEST_PATH_IMAGE018
    The real output value of the controlled device that constantly detects,
    Figure 311340DEST_PATH_IMAGE028
    For
    Figure 236570DEST_PATH_IMAGE018
    The model predictive error value of moment controlled device,
    Figure 273928DEST_PATH_IMAGE029
    Be the error correction coefficient,
    Figure 397741DEST_PATH_IMAGE030
    Figure 682092DEST_PATH_IMAGE031
    Be the matrix of step response data foundation,
    Figure 904739DEST_PATH_IMAGE032
    Be constant matrices,
    Figure 932738DEST_PATH_IMAGE033
    With
    Figure 176637DEST_PATH_IMAGE034
    Be the weight matrix of error compensation;
    Figure 366310DEST_PATH_IMAGE035
    For
    Figure 79182DEST_PATH_IMAGE036
    New transition matrix;
    Figure 707610DEST_PATH_IMAGE037
    For
    Figure 9278DEST_PATH_IMAGE024
    Moment access control increment
    Figure 182902DEST_PATH_IMAGE026
    After model predication value, be also
    Figure 570020DEST_PATH_IMAGE018
    Initial model predicted value constantly; Wherein
    Figure 2139DEST_PATH_IMAGE038
    Be illustrated respectively in
    Figure 892734DEST_PATH_IMAGE024
    Constantly right Initial model predicted value constantly;
    Figure 111674DEST_PATH_IMAGE039
    For
    Figure 347484DEST_PATH_IMAGE018
    Constantly through the optimization model predicted value after error correction; Wherein
    Figure 358165DEST_PATH_IMAGE040
    Be illustrated respectively in
    Figure 159678DEST_PATH_IMAGE018
    Constantly right
    Figure 255810DEST_PATH_IMAGE025
    Optimization model predicted value is constantly namely passed through error correction model predication value afterwards;
    Figure 29731DEST_PATH_IMAGE019
    For
    Figure 894919DEST_PATH_IMAGE018
    Constantly right Model prediction free response value constantly; Wherein
    Figure 305620DEST_PATH_IMAGE042
    Be illustrated respectively in
    Figure 555336DEST_PATH_IMAGE018
    Constantly right
    Figure 602926DEST_PATH_IMAGE041
    Model prediction free response value constantly;
    C. the dynamic matrix of setting up according to step a calculates controlled device and exists
    Figure 725734DEST_PATH_IMAGE016
    Individual continuous controlling increment
    Figure 796458DEST_PATH_IMAGE043
    Under prediction output
    Figure 912182DEST_PATH_IMAGE044
    , concrete grammar is:
    Figure 751962DEST_PATH_IMAGE045
    Wherein,
    Figure 232622DEST_PATH_IMAGE046
    Be
    Figure 335182DEST_PATH_IMAGE019
    Before
    Figure 192280DEST_PATH_IMAGE015
    ,
    Figure 948883DEST_PATH_IMAGE047
    Figure 600444DEST_PATH_IMAGE048
    For Constantly right
    Figure 854019DEST_PATH_IMAGE049
    Model prediction output valve constantly;
    D. set up non-reference locus from the object dynamic matrix control device that weighs And objective function
    Figure 553171DEST_PATH_IMAGE052
    Figure 633254DEST_PATH_IMAGE053
    Wherein,
    Figure 297770DEST_PATH_IMAGE055
    Be each output reference locus constantly;
    Figure 369763DEST_PATH_IMAGE056
    Be
    Figure 124092DEST_PATH_IMAGE057
    Respectively the weight matrix of error and controlling increment,
    Figure 923421DEST_PATH_IMAGE058
    And
    Figure 446806DEST_PATH_IMAGE059
    Be respectively the coefficient of corresponding weight matrix the inside;
    E. the objective function according to steps d obtains current controlling increment value
    Figure 686770DEST_PATH_IMAGE060
    Figure 662816DEST_PATH_IMAGE061
    F. will
    Figure 265836DEST_PATH_IMAGE060
    In first
    Figure 909307DEST_PATH_IMAGE062
    Consist of the working control amount
    Figure 57522DEST_PATH_IMAGE063
    Act on object;
    Wherein,
    Figure 786444DEST_PATH_IMAGE064
    With
    Figure 927575DEST_PATH_IMAGE065
    Be respectively
    Figure 238602DEST_PATH_IMAGE018
    Constantly and
    Figure 744670DEST_PATH_IMAGE024
    Constantly act on the working control amount of controlled device;
    G. arrive next constantly, continue to find the solution to the step of f according to b
    Figure 23204DEST_PATH_IMAGE066
    , circulation successively.
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CN104483837A (en) * 2014-11-25 2015-04-01 华中科技大学 Adaptive control method for reversible machinery group
CN103760931B (en) * 2014-01-22 2016-09-14 杭州电子科技大学 The oil gas water horizontal three-phase separator compress control method that dynamic matrix control optimizes
CN106200379A (en) * 2016-07-05 2016-12-07 杭州电子科技大学 A kind of distributed dynamic matrix majorization method of Nonself-regulating plant
CN108181804A (en) * 2017-11-28 2018-06-19 黑龙江省科学院自动化研究所 MPEC three-level liquid level control system control algolithms
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CN103336437B (en) * 2013-07-19 2015-11-25 杭州电子科技大学 Based on the integrating plant control method that Predictive function control is optimized
CN103336437A (en) * 2013-07-19 2013-10-02 杭州电子科技大学 Predictive function control optimization-based integrating plant control method
CN103616815A (en) * 2013-11-14 2014-03-05 杭州电子科技大学 Control method for waste plastic oil refining cracking furnace chamber temperature based on dynamic matrix control optimization
CN103616815B (en) * 2013-11-14 2016-06-01 杭州电子科技大学 The waste plastic oil-refining pyrolyzer fire box temperature control method that dynamic matrix control is optimized
CN103760931B (en) * 2014-01-22 2016-09-14 杭州电子科技大学 The oil gas water horizontal three-phase separator compress control method that dynamic matrix control optimizes
CN104483837A (en) * 2014-11-25 2015-04-01 华中科技大学 Adaptive control method for reversible machinery group
CN104483837B (en) * 2014-11-25 2017-04-12 华中科技大学 Adaptive control method for reversible machinery group
CN106200379A (en) * 2016-07-05 2016-12-07 杭州电子科技大学 A kind of distributed dynamic matrix majorization method of Nonself-regulating plant
CN106200379B (en) * 2016-07-05 2018-11-16 杭州电子科技大学 A kind of distributed dynamic matrix majorization method of Nonself-regulating plant
CN109725525A (en) * 2017-10-31 2019-05-07 中国石油化工股份有限公司 The method that a kind of pair of plate distillation column is controlled
CN108181804A (en) * 2017-11-28 2018-06-19 黑龙江省科学院自动化研究所 MPEC three-level liquid level control system control algolithms
CN112204547A (en) * 2020-05-26 2021-01-08 深圳市智物联网络有限公司 Data processing method, device and equipment based on industrial object model
CN112204547B (en) * 2020-05-26 2023-06-16 深圳市智物联网络有限公司 Data processing method, device and equipment based on industrial object model
CN113359460A (en) * 2021-06-24 2021-09-07 杭州司南智能技术有限公司 Integral object control method for constrained dynamic matrix control optimization
CN113419432A (en) * 2021-07-23 2021-09-21 珠海捷创华自科技有限公司 Sewage treatment system accurate dosing method based on dynamic matrix control algorithm
CN113419432B (en) * 2021-07-23 2022-04-08 珠海捷创华自科技有限公司 Sewage treatment system accurate dosing method based on dynamic matrix control algorithm

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Application publication date: 20130522