CN105955030A - Turbine and boiler coordination control method based on improved input weighted prediction controller - Google Patents
Turbine and boiler coordination control method based on improved input weighted prediction controller Download PDFInfo
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- 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
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Abstract
The invention discloses a turbine and boiler coordination control method based on an improved input weighted prediction controller. According to the method, a changing trend of a turbine and boiler coordination system load parameter is predicted and a steam turbine vale opening degree, a fuel quantity, a total water supply flow are adjusted in advance, so that defects of large inertia and large delay of the turbine and boiler coordination system can be overcome well, the response speed to a set load change of the control system is increased, and the dynamic adjustment quality of the system is improved. An input weighted factor is introduced into a prediction controller; a current time and a weighted average of a prediction control quantity on a future control time domain length are used as control quantities of an actual prediction controller, so that softening and filtering effects on a control input are realized and oscillation of the system input can be suppressed well. The method has the good control effect.
Description
Technical field
The present invention relates to a kind of boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller, belong to thermal power
Engineering and automation field.
Background technology
Fired power generating unit is towards high parameter, Large Copacity direction development, the simultaneously gentle control performance of fired power generating unit Automated water
Raising the most urgent.The main task of coordinated control system is exactly as one using steam turbine and boiler
It is controlled, makes unit meet the requirement quickly responding load instruction.Fired power generating unit Boiler-Turbine Systems is that controlled characteristic is non-
Often complicated process, has non-linear, long time delay, the feature of close coupling, its model parameter with operating mode load change and
Significantly change.Conventional control scheme based on PID control is but unable to reach gratifying regulating effect, causes
Significantly under variable working condition, Control platform is deteriorated, and affects the properly functioning economy of unit and safety.Therefore the control of advanced person is used
Method processed, the optimisation strategy that research fired power generating unit boiler-turbine coordinated controls, the integrated automation level to raising fired power generating unit,
Ensure that unit safety reliability service is significant.
PREDICTIVE CONTROL was suggested early than 1978, was built upon the model prediction on based on impulse response model
Heuristic control or referred to as Model Algorithmic contral.The starting point of PREDICTIVE CONTROL is different from traditional PID control: common PID
Control, be that current according to process and outputting measurement value in the past and setting value deviation determines current control input,
And PREDICTIVE CONTROL not only utilizes current and deviation value in the past, but also utilize forecast model to estimate following inclined of process
Difference, determines current optimum input policing to roll.Therefore, in terms of basic thought, it was predicted that control to be better than PID control.
Owing to this kind of predictive control algorithm based on nonparametric model has that modeling is simple, realizes easily and robustness is good etc. excellent
Put and be used widely, obtain significant economic benefit.
Summary of the invention
Goal of the invention: in order to overcome the deficiencies in the prior art, the present invention provides a kind of pre-based on improving weighted input
Survey controller boiler-turbine coordinated control method, the method can preferably suppression system input vibration, have preferably control effect
Really, it is possible to be effectively improved the quality of coordinated control system.
Technical scheme: for achieving the above object, the technical solution used in the present invention is:
A kind of boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller, including control system and PREDICTIVE CONTROL
Device, introduces the weighted input factor in predictive controller, uses current time and current time that future is controlled time domain length
The weighted average of PREDICTIVE CONTROL amount is as the controlled quentity controlled variable of actual prediction controller, it was predicted that controller is controlled according to this controlled quentity controlled variable
Increment processed, control system obtains prediction output according to this controlling increment and realizes the coordination control of machine stove.
Preferred: controlled quentity controlled variable u of current time k actual prediction controller1(k) be:
Wherein, NuRepresenting and control time domain length, u (k+j-1) represents the PREDICTIVE CONTROL amount in kth+j-1 moment, γ (j)
Represent and control jth weighter factor under time domain length.
Preferred: to control the size of jth weighter factor γ (j) under time domain length and be expressed as:
(1) when γ (1)=1, γ (j)=0, k=2,3 ..., NuTime, u (k)=u (k-1)+Δ u (k).When Δ u (k) represents k
Etching system will control the controlling increment of time domain length to future, and now, the Weighted Input Predictive Controller of improvement is conventional prediction
Controller.
(2) as γ (1)=1,0 < γ (j)≤1, k=2,3 ..., NuTime, the Weighted Input Predictive Controller of improvement can suppress
The vibration of u (k).
Specifically include following steps:
Step 1: according to the input and output parameter of supercritical unit featured configuration control system, input parameter includes
Steam turbine valve opening, fuel quantity, total Feedwater Flow.Output parameter includes load, separator temperature, main vapour pressure.
Under stationary conditions, respectively with steam turbine valve opening, fuel quantity, total Feedwater Flow as step amount, acquisition load,
Separator temperature, the step response value of main vapour pressure, and obtain the step-response coefficients of correspondenceWherein,
I represents i-th step response model, and N represents the time domain length of step response.
Step 2: arrange the relevant parameter of predictive controller, including optimizing time domain P, controlling time domain M, error weight matrix
Q, control matrix R.
Step 3: the prediction of control system exports by formula Ym(k)=A Δ UM(k)+YoK () can obtain, wherein, and Ym(k)
Represent the k timing control system prediction output vector to future time instance.YoWhen () will represent k timing control system to future k
The prediction initial vector carved.ΔUMThe etching system controlling increment vector to future time instance when () represents k k.A represents by step
The dynamic matrix of the step response response coefficient composition in rapid 1.
Step 4: under stationary conditions, acquisition control system current time load, separator temperature, the survey of main vapour pressure
Value y (k).Prediction initial value and prediction that measured value is assigned to control system export as original state, it may be assumed that
Ym(k)=[ym(k+1)ym(k+2)…ym(k+P)]T=y (k) I1×P。
Yo(k)=[yo(k+1)yo(k+2)…yo(k+P)]T=y (k) I1×P。
Wherein, ym(k+P) the prediction output of the control system in k+P moment, y are representedo(k+P) when representing k+P
Carve the control system prediction initial value to future time instance, I1×PRepresent all 1's matrix of 1 × P.
Step 5: the k moment that the relevant parameter of predictive controller arranged according to step 2 and step 4 obtain controls be
System prediction output vector Y to future time instancem(k) and the k timing control system prediction initial vector to future time instance
YoK () chooses performance indications:
Minimum, J (k) represents performance
Index, i.e.Try to achieve predictive controller controlling increment vector Δ UM(k)。
Wherein, W (k) represents the target set point vector of future time instance, is set in advance.
Controlling increment vector: Δ UM(k)=[Δ u (k) Δ u (k+1) ... Δ u (k+M-1)]T。
The following controlled quentity controlled variable controlling time domain length is tried to achieve according to formula u (k)=u (k-1)+Δ u (k)
U (k+j-1), j=1,2 ... M.
Wherein, when Δ u (k) represents k, etching system will control the controlling increment of time domain length to future, and u (k+j-1) represents k
Time etching system future is controlled the controlled quentity controlled variable of time domain length.
Current time and current time will be controlled the weighted average of time domain length PREDICTIVE CONTROL amount as actual prediction to future
The controlled quentity controlled variable of controller.Calculate according to the prediction output formula in step 3 and update the prediction output of control system
Ym(k+1)。
Step 6: the acquisition control system actual output y (k+1) and system prediction in the k+1 moment exports Ym(k+1) compare
Obtain output bias e (k+1), and export Y with the prediction of output bias Correction and Control systemm(k+1).Will be revised
Prediction output valve initializes control system prediction initial value Y during k+1 momento(k+1), repeatedly perform step 5 and arrive step 6,
It is controlled prediction and the correction of system output, revised prediction output is fed back to control system and realizes the coordination of machine stove
Control.
The dynamic matrix A of step response response coefficient composition in described step 3:
Wherein, the dynamic matrix inscribed during kth:
Wherein, m represents m-th control variable, each row vector of above-mentioned matrixRepresent the k moment
System output is to the i-th step-response coefficients controlling input.
Preferred: the time domain length N of described step response takes 20～50.
Preferred: to optimize time domain P and select to reach the half of transit time needed for its steady-state value equal to process per unit step response
Required sampling number.
Preferred: to control time domain length M and take less than 10.
Preferred: controlling time domain length M system of selection is.
Beneficial effect: a kind of based on improvement Weighted Input Predictive Controller the boiler-turbine coordinated control method that the present invention provides,
Compared to existing technology, have the advantages that
Use dynamic matrix control can preferably overcome the big inertia of Boiler-Turbine Systems, the big feature postponed, improve and control
The response speed that unit load is changed by system, improves the dynamic regulation quality of system.Input is introduced in predictive controller
Weighter factor, uses current time and current time to control the weighted average of time domain length PREDICTIVE CONTROL amount as reality future
The controlled quentity controlled variable of border predictive controller, to control input play softening and filter action, can preferably suppression system input shake
Swing, have and preferably control effect.
Accompanying drawing explanation
Fig. 1 is based on improving weighted input PREDICTIVE CONTROL block diagram.
Detailed description of the invention
Below in conjunction with the accompanying drawings and specific embodiment, it is further elucidated with the present invention, it should be understood that these examples are merely to illustrate this
Bright rather than limit the scope of the present invention, after having read the present invention, various to the present invention of those skilled in the art
The amendment of the equivalent form of value all falls within the application claims limited range.
A kind of boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller, cannot solve for traditional PID control
The big inertia of turbine-boiler coordinated control system certainly, the big problem postponed, use dynamic matrix control strategy, and to PREDICTIVE CONTROL
Device adds the weighted input factor, has advance, and practical, robustness is good.As it is shown in figure 1, include control system
And predictive controller, predictive controller introduces the weighted input factor, uses current time and current time that future is controlled
The weighted average of time domain length PREDICTIVE CONTROL amount processed is as the controlled quentity controlled variable of actual prediction controller, it was predicted that controller is according to this control
System measures controlling increment, and control system obtains prediction output according to this controlling increment and realizes the coordination control of machine stove.
Specifically include following steps:
Step 1: according to the input and output parameter of supercritical unit featured configuration control system, input parameter includes
Steam turbine valve opening, fuel quantity, total Feedwater Flow.Output parameter includes load, separator temperature, main vapour pressure.
Under stationary conditions, respectively with steam turbine valve opening, fuel quantity, total Feedwater Flow as step amount, acquisition load,
Separator temperature, the step response value of main vapour pressure, and obtain the step-response coefficients of correspondenceWherein,
I represents i-th step response model, and N represents the time domain length of step response.Step-response coefficients ai(i=1,2 ..., N)
Smooth change as far as possible, so N takes 20～50.
Step 2: arrange the relevant parameter of predictive controller, including optimizing time domain P, controlling time domain M, error weight matrix
Q, control matrix R.
Optimize time domain P to select to reach needed for its steady-state value needed for the half of transit time equal to process per unit step response
Sampling number.
Control time domain length M takes and is advisable less than 10, and being typically chosen rule is
Relation ratio between system output and input quantity
Better simply process；The process that Relationship Comparison between system output and input quantity is complicated.
Described error weight matrix Q=diag (q1,q2,…qP)。q1,q2,…qPRepresent error weight parameter.
Described control matrix R=diag (r1,r2,…rM)。r1,r2,…rMRepresent control parameter.
Step 3: the prediction of control system exports by formula Ym(k)=A Δ UM(k)+YoK () can obtain, wherein, and Ym(k)
Represent the k timing control system prediction output vector to future time instance.YoWhen () will represent k timing control system to future k
The prediction initial vector carved.ΔUMThe etching system controlling increment vector to future time instance when () represents k k.A represents by step
The dynamic matrix of the step response response coefficient composition in rapid 1.
Wherein, the dynamic matrix inscribed during kth:
Wherein, m represents m-th control variable, each row vector of above-mentioned matrixRepresent the k moment
System output is to the i-th step-response coefficients controlling input.
Step 4: under stationary conditions, acquisition control system current time load, separator temperature, the survey of main vapour pressure
Value y (k), because being that multi-variable system y (k) uses vector form.Measured value is assigned to the prediction initial value of control system
And prediction output is as original state, it may be assumed that
Ym(k)=[ym(k+1)ym(k+2)…ym(k+P)]T=y (k) I1×P。
Yo(k)=[yo(k+1)yo(k+2)…yo(k+P)]T=y (k) I1×P。
Wherein, ym(k+P) the prediction output of the control system in k+P moment, y are representedo(k+P) when representing k+P
Carve the control system prediction initial value to future time instance, I1×PRepresent all 1's matrix of 1 × P.
Step 5: the k moment that the relevant parameter of predictive controller arranged according to step 2 and step 4 obtain controls be
System prediction output vector Y to future time instancem(k) and the k timing control system prediction initial vector to future time instance
YoK () chooses performance indications:
Minimum, J (k) represents performance
Index, i.e.Try to achieve predictive controller controlling increment vector Δ UM(k)。
Wherein, W (k) represents the target set point vector of future time instance, is set in advance.
Controlling increment vector: Δ UM(k)=[Δ u (k) Δ u (k+1) ... Δ u (k+M-1)]T。
Try to achieve according to formula u (k)=u (k-1)+Δ u (k) and control the controlled quentity controlled variable of time domain length future:
U (k+j-1), j=1,2 ... M.
Wherein, when Δ u (k) represents k, etching system will control the controlling increment of time domain length to future, and u (k+j-1) represents k
Time etching system future is controlled the controlled quentity controlled variable of time domain length.
Then use the weighted input method of following improvement, current time and current time are controlled time domain length to future pre-
Survey the weighted average controlled quentity controlled variable as actual prediction controller of controlled quentity controlled variable.
Controlled quentity controlled variable u of current time k actual prediction controller1(k) be:
Wherein, NuRepresenting and control time domain length, u (k+j-1) represents the PREDICTIVE CONTROL amount in kth+j-1 moment, γ (j)
Represent and control jth weighter factor under time domain length.
Control the size of jth weighter factor γ (j) under time domain length to be expressed as:
(1) when γ (1)=1, γ (j)=0, k=2,3 ..., NuTime, u (k)=u (k-1)+Δ u (k).When Δ u (k) represents k
Etching system will control the controlling increment of time domain length to future, and now, the Weighted Input Predictive Controller of improvement is conventional prediction
Controller.
(2) as γ (1)=1,0 < γ (j)≤1, k=2,3 ..., NuTime, the Weighted Input Predictive Controller of improvement can suppress
The vibration of u (k).
The controlled quentity controlled variable of actual prediction controller is obtained by improvement weighted input method.Formula is exported according to the prediction in step 3
Calculate and update the prediction output Y of control systemm(k+1)。
Step 6: the acquisition control system actual output y (k+1) and system prediction in the k+1 moment exports Ym(k+1) compare
Obtain output bias e (k+1), and export Y with the prediction of output bias Correction and Control systemm(k+1).Will be revised
Prediction output valve initializes control system prediction initial value Y during k+1 momento(k+1), repeatedly perform step 5 and arrive step 6,
It is controlled prediction and the correction of system output, revised prediction output is fed back to control system and realizes the coordination of machine stove
Control.
The present invention is by predicting the variation tendency of Boiler-Turbine Systems load parameter and adjusting steam turbine valve opening, fuel in advance
Amount and total Feedwater Flow, it is possible to preferably overcome the big inertia of Boiler-Turbine Systems, the big feature postponed, improve control system
Response speed to unit load change, improves the dynamic regulation quality of system；In order to improve coordinated control
The Control platform of system, introduces the weighted input factor in predictive controller, uses current time and current time to future
Control the weighted average controlled quentity controlled variable as actual prediction controller of time domain length PREDICTIVE CONTROL amount, play soft to controlling input
Change and filter action, can preferably suppression system input vibration, have and preferably control effect.
The above is only the preferred embodiment of the present invention, it should be pointed out that: for those skilled in the art
For, under the premise without departing from the principles of the invention, it is also possible to make some improvements and modifications, these improvements and modifications are also
Should be regarded as protection scope of the present invention.
Claims (8)
1. a boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller, it is characterised in that: include controlling system
System and predictive controller, introduce the weighted input factor in predictive controller, use current time and current time pair
The following weighted average controlled quentity controlled variable as actual prediction controller controlling time domain length PREDICTIVE CONTROL amount, it was predicted that control
Device obtains controlling increment according to this controlled quentity controlled variable, and control system obtains prediction output according to this controlling increment and realizes machine stove
Coordinate to control.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 1, its feature
It is: controlled quentity controlled variable u of current time k actual prediction controller1(k) be:
Wherein, NuRepresenting and control time domain length, u (k+j-1) represents the PREDICTIVE CONTROL amount in kth+j-1 moment,
γ (j) represents jth weighter factor under control time domain length.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 2, its feature
It is: control the size of jth weighter factor γ (j) under time domain length and be expressed as:
(1) when γ (1)=1, γ (j)=0, k=2,3 ..., NuTime, u (k)=u (k-1)+Δ u (k)；Δ u (k) represents
During k, etching system will control the controlling increment of time domain length to future, and now, the Weighted Input Predictive Controller of improvement is normal
Rule predictive controller；
(2) as γ (1)=1,0 < γ (j)≤1, k=2,3 ..., NuTime, the Weighted Input Predictive Controller of improvement can press down
The vibration of u (k) processed.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 1, its feature
It is, comprises the following steps:
Step 1: according to the input and output parameter of supercritical unit featured configuration control system, inputs parameter bag
Include steam turbine valve opening, fuel quantity, total Feedwater Flow；Output parameter includes load, separator temperature, main vapour pressure
Power；
Under stationary conditions, respectively with steam turbine valve opening, fuel quantity, total Feedwater Flow as step amount, obtain negative
Lotus, separator temperature, the step response value of main vapour pressure, and obtain the step-response coefficients of correspondence
Wherein, i represents i-th step response model, and N represents the time domain length of step response；
Step 2: arrange the relevant parameter of predictive controller, including optimizing time domain P, controlling time domain M, error power
Matrix Q, control matrix R；
Step 3: the prediction of control system exports by formula Ym(k)=A Δ UM(k)+YoK () can obtain, wherein,
YmK () represents the k timing control system prediction output vector to future time instance；YoK () represents k timing control system
Prediction initial vector to future time instance；ΔUMThe etching system controlling increment vector to future time instance when () represents k k；
A represents the dynamic matrix being made up of the step response response coefficient in step 1；
Step 4: under stationary conditions, acquisition control system current time load, separator temperature, main vapour pressure
Measured value y (k)；Prediction initial value and prediction that measured value is assigned to control system export as original state, it may be assumed that
Ym(k)=[ym(k+1)ym(k+2)…ym(k+P)]T=y (k) I1×P；
Yo(k)=[yo(k+1)yo(k+2)…yo(k+P)]T=y (k) I1×P；
Wherein, ym(k+P) the prediction output of the control system in k+P moment, y are representedo(k+P) represent
The k+P timing control system prediction initial value to future time instance, I1×PRepresent all 1's matrix of 1 × P；
Step 5: the k moment that the relevant parameter of predictive controller arranged according to step 2 and step 4 obtain controls
System prediction output vector Y to future time instancem(k) and k timing control system to the prediction initial value of future time instance to
Amount YoK () chooses performance indications:
Minimum, J (k) represents
Performance indications, i.e.Try to achieve predictive controller controlling increment vector Δ UM(k)；
Wherein, W (k) represents the target set point vector of future time instance, is set in advance；
Controlling increment vector: Δ UM(k)=[Δ u (k) Δ u (k+1) ... Δ u (k+M-1)]T；
The following controlled quentity controlled variable controlling time domain length is tried to achieve according to formula u (k)=u (k-1)+Δ u (k)
U (k+j-1), j=1,2 ... M；
Wherein, when Δ u (k) represents k, etching system will control the controlling increment of time domain length to future, and u (k+j-1) represents
During k, etching system will control the controlled quentity controlled variable of time domain length to future；
The weighted average that future is controlled time domain length PREDICTIVE CONTROL amount by current time and current time is pre-as reality
Survey the controlled quentity controlled variable of controller；Calculate according to the prediction output formula in step 3 and update the prediction output of control system
Ym(k+1)；
Step 6: the acquisition control system actual output y (k+1) and system prediction in the k+1 moment exports Ym(k+1)
Relatively obtain output bias e (k+1), and export Y with the prediction of output bias Correction and Control systemm(k+1)；Will
Revised prediction output valve initializes control system prediction initial value Y during k+1 momento(k+1), step is repeatedly performed
Rapid 5 arrive step 6, be controlled prediction and the correction of system output, revised prediction output feeds back to control system
System realizes the coordination of machine stove and controls.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 4, its feature
It is: the dynamic matrix A of step response response coefficient composition in described step 3:
Wherein, the dynamic matrix inscribed during kth:
Wherein, m represents m-th control variable, each row vector of above-mentioned matrixWhen representing k
Etching system output is to the i-th step-response coefficients controlling input.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 4, its feature
It is: the time domain length N of described step response takes 20～50.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 4, its feature
It is: optimize time domain P and select to reach the half institute of transit time needed for its steady-state value equal to process per unit step response
The sampling number needed.
Boiler-turbine coordinated control method based on improvement Weighted Input Predictive Controller the most according to claim 4, its feature
It is: control time domain length M and take less than 10.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106094524A (en) * | 2016-07-07 | 2016-11-09 | 西北工业大学 | The rapid model prediction control method compensated based on input trend |
| CN108717260A (en) * | 2018-03-07 | 2018-10-30 | 国网浙江省电力有限公司电力科学研究院 | Band based on dull integral coefficient disturbs Predictive function control design method |
| CN113139291A (en) * | 2021-04-23 | 2021-07-20 | 广东电网有限责任公司电力科学研究院 | Method and device for obtaining optimal sliding window filtering model of controlled process |
| CN113835342A (en) * | 2021-09-18 | 2021-12-24 | 国网河北能源技术服务有限公司 | Disturbance rejection prediction control method of superheated steam temperature system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5279263A (en) * | 1993-02-05 | 1994-01-18 | Elsag International B.V. | Cascaded steam temperature control applied to a universal pressure boiler |
| JP2011021758A (en) * | 2009-07-13 | 2011-02-03 | Jfe Engineering Corp | Method of correcting fuel charging amount for boiler |
| CN101509656B (en) * | 2008-12-17 | 2011-03-23 | 中国电力科学研究院 | Supercritical DC furnace synthesis type coordinating control method |
| CN101761917B (en) * | 2010-01-11 | 2012-07-04 | 重庆大学 | Boiler overheating steam temperature fuzzy control method |
| JP5197299B2 (en) * | 2008-10-20 | 2013-05-15 | 中国電力株式会社 | Coal calorie control system in boiler equipment. |
| CN102563599B (en) * | 2012-02-07 | 2014-04-30 | 云南电力试验研究院（集团）有限公司电力研究院 | Coordinative control method for supercritical unit boilers quickly adaptive to change of heat value of fire coal |
| CN102608911B (en) * | 2012-03-14 | 2014-09-10 | 东南大学 | Fossil power plant coordination control method based on multi-parameter prediction |
-
2016
- 2016-06-08 CN CN201610406076.3A patent/CN105955030A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5279263A (en) * | 1993-02-05 | 1994-01-18 | Elsag International B.V. | Cascaded steam temperature control applied to a universal pressure boiler |
| JP5197299B2 (en) * | 2008-10-20 | 2013-05-15 | 中国電力株式会社 | Coal calorie control system in boiler equipment. |
| CN101509656B (en) * | 2008-12-17 | 2011-03-23 | 中国电力科学研究院 | Supercritical DC furnace synthesis type coordinating control method |
| JP2011021758A (en) * | 2009-07-13 | 2011-02-03 | Jfe Engineering Corp | Method of correcting fuel charging amount for boiler |
| CN101761917B (en) * | 2010-01-11 | 2012-07-04 | 重庆大学 | Boiler overheating steam temperature fuzzy control method |
| CN102563599B (en) * | 2012-02-07 | 2014-04-30 | 云南电力试验研究院（集团）有限公司电力研究院 | Coordinative control method for supercritical unit boilers quickly adaptive to change of heat value of fire coal |
| CN102608911B (en) * | 2012-03-14 | 2014-09-10 | 东南大学 | Fossil power plant coordination control method based on multi-parameter prediction |
Non-Patent Citations (5)
| Title |
|---|
| 丁元欣: "新型输入加权预测控制器", 《控制与决策》 * |
| 刘士荣等: "《计算机控制系统》", 30 April 2013, 机械工业出版社 * |
| 舒迪前: "《预测控制系统及其应用》", 31 March 1996, 机械工业出版社 * |
| 陈虹: "《模型预测控制》", 31 July 2013, 科学出版社 * |
| 马述军: "单元机组负荷控制系统的动态矩阵方法研究", 《工业控制与应用》 * |
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| CN106094524A (en) * | 2016-07-07 | 2016-11-09 | 西北工业大学 | The rapid model prediction control method compensated based on input trend |
| CN108717260A (en) * | 2018-03-07 | 2018-10-30 | 国网浙江省电力有限公司电力科学研究院 | Band based on dull integral coefficient disturbs Predictive function control design method |
| CN108717260B (en) * | 2018-03-07 | 2021-05-18 | 国网浙江省电力有限公司电力科学研究院 | Disturbance-based prediction function control design method based on single integer coefficient |
| CN113139291A (en) * | 2021-04-23 | 2021-07-20 | 广东电网有限责任公司电力科学研究院 | Method and device for obtaining optimal sliding window filtering model of controlled process |
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