CN111506029B - Industrial control method and device - Google Patents
Industrial control method and device Download PDFInfo
- Publication number
- CN111506029B CN111506029B CN202010279172.2A CN202010279172A CN111506029B CN 111506029 B CN111506029 B CN 111506029B CN 202010279172 A CN202010279172 A CN 202010279172A CN 111506029 B CN111506029 B CN 111506029B
- Authority
- CN
- China
- Prior art keywords
- control
- parameter
- limit
- basic value
- base value
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000003068 static effect Effects 0.000 claims abstract description 8
- 238000012937 correction Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 9
- 230000007246 mechanism Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 abstract description 14
- 230000008859 change Effects 0.000 description 19
- 239000007788 liquid Substances 0.000 description 5
- 230000004048 modification Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 4
- 238000003745 diagnosis Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000012502 risk assessment Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008033 biological extinction Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 239000000969 carrier Substances 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000010485 coping Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41885—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by modeling, simulation of the manufacturing system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/06—Asset management; Financial planning or analysis
-
- 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
- G05B2219/32—Operator till task planning
- G05B2219/32339—Object oriented modeling, design, analysis, implementation, simulation language
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
An industrial control method and device comprises a control base value and a control module, wherein the control module enables the control base value to fluctuate within a control upper limit and/or a control lower limit, and the control module at least comprises a set fluctuation parameter and a preset fluctuation parameter; the set fluctuation parameters are obtained according to static analysis, and the preset fluctuation parameters are obtained according to dynamic analysis. The application can take the existence of the preference of the control system into consideration in the control process by acquiring the preset fluctuation parameters, and can play a certain prediction role by taking the existence of the preference carried by the control system into consideration, so as to avoid excessive fluctuation of the control base value.
Description
Technical Field
The application relates to an industrial control method and device.
Background
In order to better configure the resources, excessive expenditure of the resources and damage to carriers of the resources or secondary disasters are avoided, so that the fluctuation degree of the resources needs to be controlled. Such control is embodied not only in the industrial field but also in the investment and financing field.
The existing industrial field generally adopts a mode such as PLC control to control specific parameters, the control is unidirectional control in nature, and a method for observing and controlling static parameters is adopted, so that the method has great limitation, is poor in stability and has poor predictive control performance. In the field of financing and financial management, a static observation and control mode is adopted at the present stage, and the coping and control strategy for the change is lacking.
Disclosure of Invention
In order to solve the above problems, the present application proposes an industrial control method, which includes a control base value and a control module, wherein the control module makes the control base value fluctuate within a control upper limit and/or a control lower limit, and the control module at least includes a set fluctuation parameter and a predetermined fluctuation parameter; the set fluctuation parameters are obtained according to static analysis, and the preset fluctuation parameters are obtained according to dynamic analysis. The application can take the existence of the preference of the control system into consideration in the control process by acquiring the preset fluctuation parameters, and can play a certain prediction role by taking the existence of the preference carried by the control system into consideration, so as to avoid excessive fluctuation of the control base value. The control base value y, the initial value x of the control base value, the fluctuation parameter a is set, and a function relationship of y=f (x, a, b) exists between the predetermined fluctuation parameters b, and more specific function relationship can be set as y=x (1+a) (1+b).
Preferably, the static analysis is an analysis performed according to a control parameter at an analysis time point.
Preferably, the dynamic analysis is a predictive analysis based on control base fluctuation preferences.
Specifically, the static analysis of the present application is an effect that can be achieved or expected to be achieved by the original control parameters, and the dynamic analysis is a control parameter of a tendency property obtained by historical data, control preferences of the control system itself, and the like. For example, in the process of controlling the liquid level, static control is a relatively fixed control process, such as overhigh liquid level, and can be obtained by reducing feeding or increasing discharging; dynamic control is also a situation in which the liquid level is reduced from fluctuating by means of historical data, including the speed of the fluctuation and the time frequency of the downlift or uplift, etc.
Preferably, the system also comprises an early warning mechanism, and when the control base value is not in the upper control limit and/or the lower control limit range, early warning processing is carried out; and gives the time for the control base value to return to the upper control limit and/or the lower control limit range according to the control method of the current control module. The early warning mechanism refers to a processing mode when the control base value is not in a preset range, and a general control system is essentially a parameter adjustment system, but the application does not enable the control base value to be fluctuated or fluctuated little, but keeps a stability, and enables the control process to be relatively smooth and relatively controllable as far as possible regardless of whether the control base value exceeds the upper control limit and/or the lower control limit.
Preferably, the control system further includes a base value correction parameter for correcting a variation in the control base value itself. The basic value correction parameter is mainly used for carrying out invasive form modification on the control basic value after the control basic value is changed, so that the existing condition is better represented. If the control basic value needs to change itself in the control process, or in the asset allocation, problems such as retirement, loss of business, investment failure and the like are generated.
Preferably, the predetermined fluctuation parameter is set with the base value correction parameter.
Preferably, the control base value is a physical control parameter, the set fluctuation parameter is a fluctuation condition obtained according to an external control parameter set in advance, and the predetermined fluctuation parameter is obtained according to a history analysis of fluctuation of the physical control parameter.
Preferably, the control base value is a total asset, the set fluctuation parameter is expected fluctuation generated by configuration of the existing total asset, and the predetermined fluctuation parameter is a fluctuation parameter obtained by prediction of investment trend formation of the total asset; the total asset comprises a plurality of sub-assets, and the sub-assets are added to obtain the total asset.
Preferably, the system also comprises an early warning mechanism, and when the control base value is not in the upper control limit and/or the lower control limit range, early warning processing is carried out; and giving the time for returning the control base value to the upper control limit and/or the lower control limit range or giving a new preset fluctuation parameter according to the control method of the current control module, and giving the time for returning the control base value to the upper control limit and/or the lower control limit range according to the new preset fluctuation parameter. The application adopts a mode of setting new preset fluctuation parameters to reduce fluctuation after early warning, and aims to provide an entry for redistributing assets for secondary redistribution.
In another aspect, an industrial control device includes a base value acquisition module configured to obtain a control base value;
the control module is used for acquiring the set fluctuation parameters and the preset fluctuation parameters and enabling the control base value to fluctuate within the upper control limit and/or the lower control limit;
the early warning module is used for carrying out early warning processing when the control basic value is not in the upper control limit and/or the lower control limit range; and give the time that the control basic value returns to the upper control limit and/or the lower control limit range according to the control method of the current control module;
and the base value correction module is used for correcting the control base value.
On the other hand, an industrial control device is also provided,
the application has the following beneficial effects:
1. the application can take the existence of the preference of the control system into consideration in the control process by acquiring the preset fluctuation parameters, and can play a certain prediction role by taking the existence of the preference carried by the control system into consideration, so as to avoid excessive fluctuation of the control base value;
2. the early warning mechanism refers to a processing mode when the control base value is not in a preset range, and a general control system is essentially a parameter adjustment system, but the application does not lead the control base value to not fluctuate or to fluctuate little, but keeps a stability, and enables the control process to carry out relatively smooth and relatively controllable transition as far as possible no matter whether the control base value exceeds the upper control limit and/or the lower control limit;
3. the basic value correction parameter is mainly used for carrying out invasive form modification on the control basic value after the control basic value is changed, so that the existing condition is better represented. If the control basic value needs to be changed in the control process, or in the asset allocation, the problems of retirement, loss of business, investment failure and the like are generated;
4. in the aspect of asset allocation, the application adopts a mode of setting new preset fluctuation parameters to reduce fluctuation after early warning, so as to provide an entry for asset redistribution and carry out secondary redistribution.
Detailed Description
In order to clearly illustrate the technical characteristics of the scheme, the application is explained in detail by the following specific embodiments.
In the first embodiment, the application is used for liquid level control, firstly, a control base value, namely a liquid level height, to be controlled is obtained, and then, a set fluctuation parameter is obtained according to the existing control mode, namely a PLC control mode or other types of control modes; then analyzing the change rule of the control parameter of the original control to obtain a preset fluctuation parameter, a control base value y, an initial value x of the control base value, a set fluctuation parameter a and a preset fluctuation parameter b, and calculating the control base value y according to the following formula: y=x (1+a) (1+b), the upper control limit L1 and the lower control limit L2, if y is greater than L1 or less than L2, according to the setting, starting an early warning mechanism, and two processing modes exist, wherein the first mode is to continue to execute the control mode of y=x (1+a) (1+b), and predict the time when y reaches L1-L2; it is of course also possible to change the evolutionary path of y by changing the predetermined fluctuation parameter b, and then predict the time between the new arrival at LI-L2.
If the initial value x of the control base value is changed, such as the water container itself is changed, if the control base value is to be kept unchanged, the first option is to change the predetermined fluctuation parameter b, but the predetermined fluctuation parameter b is a parameter which follows the preference of the system, so that the change mode is to enhance and change the preference, or reverse twist the preference. Of course, the stability of y can be ensured by changing the set fluctuation parameter a, and the control mode of changing a is equivalent to adopting PLC negative feedback control.
In a second embodiment, applying the application to a home asset configuration, the client can collect four sets of data by filling in the asset configuration assessment questionnaire module, respectively: investment risk assessment data, household asset income data, household insurance guarantee data and household consumption expenditure data.
1. Collecting and analyzing investment risk assessment data: the basic data M is obtained by collecting answers to questions such as customer age, investment preference, investment time, investment experience, investment purpose, risk bearing capacity and the like, respectively giving a certain score (value 1-10) to each answer option, and then adding and summing the assigned scores.
(1) Evaluation to determine customer investment risk attributes (data M)
Setting "0, m1, m2, m3, m4, 100" as "the fractional scores of the five investment styles of conservation, robustness, balance, growth and advance", then:
m=if (and (M > M4, M < =100), "aggressive" if (and (M > M3, M < =m4), "growing" if (and (M > M2, M < =m3), "balanced" if (and (M > M1, M < =m2), "robust" if (and (M >0, M < =m1), "conservative", "data error")));
thereby calculating the investment risk attribute category of the client.
(2) And according to the client investment risk attribute category M, carrying out evaluation analysis on the product category suitable for the investment of the client.
The product category is set as follows: the method comprises the steps of carrying out detailed diagnosis and explanation on the existing investment structure and product category of a client after carrying out weight assignment on n1-n5, wherein the detailed diagnosis and explanation comprises two parts of characteristic description and specific product suggestion of different product types, and reasonable correction suggestion is provided.
2. Household asset income data acquisition and analysis: by counting the different classes of assets existing in a customer's home, e.g. financial assets (category x 1 1、x 1 2、x 1 3 … … x 19), physical class asset (class x 1 10、x 1 11、x 1 12……x 1 18 Intangible asset (category x) 1 19、x 1 20 And other assets (x) 1 21 Plus customer household income (category x) 1 22、x 1 23 Together with the final x 1 I.e. x 1 1、x 1 2、x 1 3……x 1 23. According to x 1 1、x 1 2、x 1 3 … … the average yield of the existing market can obtain the set fluctuation parameter a 1 。
In the process, x is due to depreciation of the asset itself and change of market trend 1 Is itself a variable value, this is mainly achieved by a 1 The variation with time is shown in a 1 Simultaneously with the change, a change in y is caused;
in this process, with the continuous change of market, the continuous change of x, the change of the structural proportion of x1, x2, x3 … … x23, the change of investment style M, the growth period of clients on x and x1, x2, x3 …, investment warpThe profits will also change appropriately, this change being manifested as a predetermined fluctuation parameter b 1 。
In this process, x 1 1、x 1 2、x 1 3……x 1 23, which is embodied as a basic value correction parameter c 1 。
3. Household consumption expenditure data acquisition and analysis: statistics is performed through the classification of consumer expenditure items of different types existing in the families of customers, such as clothes, foods, lives, rows, usages and medical care … … insurance class (classification x 2 1、x 2 2、x 2 3……x 2 27 Together with the final x 2 I.e. x 2 1、x 2 2、x 2 3……x 2 27. According to the existing x 2 1、x 2 2、x 2 3……x 2 27, the set fluctuation parameter a can be obtained 2 。
In the process, due to family structure, family member age, consumption habit, accident, x 1 Factor influence such as variation of x 2 1、x 2 2、x 2 3……x 2 27 may also change to some extent, thereby causing the customer to respond to x 2 1、x 2 2、x 2 3……x 2 27, which also causes a change in y, as reflected by a predetermined fluctuation parameter b 2 。
In this process, x 2 1、x 2 2、x 2 3……x 2 27 as a base value correction parameter c 2 。
At this time, y=x (1+a) (1+b) can be expressed as:
y＝x 1 (c 1 )(1+a 1 )(1+b 1 )-x 2 (c 2 )(1+a 2 )(1+b 2 )。
4. if the asset is destroyed directly by a sub-category of income and expense due to the occurrence of extinction, retirement, emergency, etc., the parameter c (c 1 /c 2 ) To correct x, where the calculated y will be mutated, and testedWhether it is between L1 and L2. If it is not between L1 and L2, b (b) is adjusted 1 /b 2 ) That is, the personal preference is adjusted to bring about a change in return on investment to cause y to fall between L1-L2, of course, since a is also time-varying, in combination with its effect on y, b is adjusted so that y falls smoothly between L1-L2 or b is not adjusted, but only dependent on a so that y falls into L1-L2, and the time required to revert to the L1-L2 interval is calculated.
In a third embodiment, an industrial control device includes a base value acquisition module for acquiring a control base value; the control module is used for acquiring the set fluctuation parameters and the preset fluctuation parameters and enabling the control base value to fluctuate within the upper control limit and/or the lower control limit; the early warning module is used for carrying out early warning processing when the control basic value is not in the upper control limit and/or the lower control limit range; and give the time that the control basic value returns to the upper control limit and/or the lower control limit range according to the control method of the current control module; and the base value correction module is used for correcting the control base value.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (3)
1. An industrial control method, characterized in that: the control system comprises a control base value and a control module, wherein the control module enables the control base value to fluctuate within a control upper limit and/or a control lower limit range, and the control module at least comprises a set fluctuation parameter and a preset fluctuation parameter; the set fluctuation parameters are obtained according to static analysis, and the preset fluctuation parameters are obtained according to dynamic analysis;
the system further comprises a basic value correction parameter, wherein the basic value correction parameter is used for correcting the variation of the control basic value when the initial value of the control basic value is changed;
the preset fluctuation parameter is set along with a basic value correction parameter, so that the control basic value fluctuates within the upper control limit and/or the lower control limit;
the control base value is a physical control parameter, the set fluctuation parameter is obtained according to the control mode type, and the preset fluctuation parameter is obtained according to the analysis of the history of fluctuation of the physical control parameter.
2. An industrial control method according to claim 1, wherein: the system also comprises an early warning mechanism, and when the control basic value is not in the upper control limit and/or the lower control limit range, early warning processing is carried out; and gives the time for the control base value to return to the upper control limit and/or the lower control limit range according to the control method of the current control module.
3. An apparatus for implementing the industrial control method of claim 1 or claim 2, characterized in that: the system comprises a basic value acquisition module, a control basic value acquisition module and a control basic value acquisition module, wherein the basic value acquisition module is used for acquiring a control basic value;
the control module is used for acquiring the set fluctuation parameters and the preset fluctuation parameters and enabling the control base value to fluctuate within the upper control limit and/or the lower control limit;
the early warning module is used for carrying out early warning processing when the control basic value is not in the upper control limit and/or the lower control limit range; and give the time that the control basic value returns to the upper control limit and/or the lower control limit range according to the control method of the current control module;
and the base value correction module is used for correcting the control base value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010279172.2A CN111506029B (en) | 2020-04-10 | 2020-04-10 | Industrial control method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010279172.2A CN111506029B (en) | 2020-04-10 | 2020-04-10 | Industrial control method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111506029A CN111506029A (en) | 2020-08-07 |
| CN111506029B true CN111506029B (en) | 2023-11-24 |
Family
ID=71869257
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010279172.2A Active CN111506029B (en) | 2020-04-10 | 2020-04-10 | Industrial control method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111506029B (en) |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4543565A (en) * | 1981-06-12 | 1985-09-24 | Siemens Aktiengesellschaft | Method and apparatus for monitoring an alarm system |
| US20030217019A1 (en) * | 2002-04-04 | 2003-11-20 | Weiss Gary Allen | System and method for increasing yield from performance contracts |
| CN203118160U (en) * | 2012-12-14 | 2013-08-07 | 中电投远达环保工程有限公司 | Flue gas desulfurization system operation monitoring and pre-warning instrument |
| CN204256388U (en) * | 2014-11-19 | 2015-04-08 | 中国石油天然气股份有限公司 | Frequency converter PID controller |
| CN105579320A (en) * | 2013-09-05 | 2016-05-11 | 李斯特内燃机及测试设备公司 | Method and device for optimizing driver assistance systems |
| CN106685228A (en) * | 2017-03-08 | 2017-05-17 | 合肥海峰汽车配件有限公司 | Closed loop control method and direct current method and direct current converter |
| CN107168412A (en) * | 2017-05-26 | 2017-09-15 | 国网天津市电力公司 | Power transformer cooling system control apparatus and method |
| CN107171969A (en) * | 2016-03-07 | 2017-09-15 | 华为技术有限公司 | A kind of data transmission method, apparatus and system |
| CN107834574A (en) * | 2017-07-31 | 2018-03-23 | 上海电气分布式能源科技有限公司 | A kind of distributed energy resource system exchanges the control method of power with power network |
| CN109143840A (en) * | 2018-09-18 | 2019-01-04 | 湖南柿竹园有色金属有限责任公司 | A kind of mine tailing wastewater processing dosing closed loop uniform recipe design technology |
| CN109787260A (en) * | 2019-01-31 | 2019-05-21 | 中国电力科学研究院有限公司 | A kind of energy storage system control method and system of the photovoltaic power generation short-term fluctuation of smooth distribution formula |
| CN110033378A (en) * | 2019-01-29 | 2019-07-19 | 阿里巴巴集团控股有限公司 | A kind of resource allocation method, device and electronic equipment |
| CN110363664A (en) * | 2019-07-23 | 2019-10-22 | 上海金融期货信息技术有限公司 | A kind of option stability bandwidth automatic Matching Method and system |
| CN110428335A (en) * | 2019-08-09 | 2019-11-08 | 深圳前海微众银行股份有限公司 | Cost resource allocation method, device, equipment and computer readable storage medium |
| CN110454372A (en) * | 2019-08-19 | 2019-11-15 | 蘑菇物联技术（深圳）有限公司 | A kind of method of air compression station predictability control |
| CN110472889A (en) * | 2019-08-22 | 2019-11-19 | 泰康保险集团股份有限公司 | Resource allocation method, device for allocating resources, storage medium and electronic equipment |
-
2020
- 2020-04-10 CN CN202010279172.2A patent/CN111506029B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4543565A (en) * | 1981-06-12 | 1985-09-24 | Siemens Aktiengesellschaft | Method and apparatus for monitoring an alarm system |
| US20030217019A1 (en) * | 2002-04-04 | 2003-11-20 | Weiss Gary Allen | System and method for increasing yield from performance contracts |
| CN203118160U (en) * | 2012-12-14 | 2013-08-07 | 中电投远达环保工程有限公司 | Flue gas desulfurization system operation monitoring and pre-warning instrument |
| CN105579320A (en) * | 2013-09-05 | 2016-05-11 | 李斯特内燃机及测试设备公司 | Method and device for optimizing driver assistance systems |
| CN204256388U (en) * | 2014-11-19 | 2015-04-08 | 中国石油天然气股份有限公司 | Frequency converter PID controller |
| CN107171969A (en) * | 2016-03-07 | 2017-09-15 | 华为技术有限公司 | A kind of data transmission method, apparatus and system |
| CN106685228A (en) * | 2017-03-08 | 2017-05-17 | 合肥海峰汽车配件有限公司 | Closed loop control method and direct current method and direct current converter |
| CN107168412A (en) * | 2017-05-26 | 2017-09-15 | 国网天津市电力公司 | Power transformer cooling system control apparatus and method |
| CN107834574A (en) * | 2017-07-31 | 2018-03-23 | 上海电气分布式能源科技有限公司 | A kind of distributed energy resource system exchanges the control method of power with power network |
| CN109143840A (en) * | 2018-09-18 | 2019-01-04 | 湖南柿竹园有色金属有限责任公司 | A kind of mine tailing wastewater processing dosing closed loop uniform recipe design technology |
| CN110033378A (en) * | 2019-01-29 | 2019-07-19 | 阿里巴巴集团控股有限公司 | A kind of resource allocation method, device and electronic equipment |
| CN109787260A (en) * | 2019-01-31 | 2019-05-21 | 中国电力科学研究院有限公司 | A kind of energy storage system control method and system of the photovoltaic power generation short-term fluctuation of smooth distribution formula |
| CN110363664A (en) * | 2019-07-23 | 2019-10-22 | 上海金融期货信息技术有限公司 | A kind of option stability bandwidth automatic Matching Method and system |
| CN110428335A (en) * | 2019-08-09 | 2019-11-08 | 深圳前海微众银行股份有限公司 | Cost resource allocation method, device, equipment and computer readable storage medium |
| CN110454372A (en) * | 2019-08-19 | 2019-11-15 | 蘑菇物联技术（深圳）有限公司 | A kind of method of air compression station predictability control |
| CN110472889A (en) * | 2019-08-22 | 2019-11-19 | 泰康保险集团股份有限公司 | Resource allocation method, device for allocating resources, storage medium and electronic equipment |
Non-Patent Citations (2)
| Title |
|---|
| Honeywell先进控制在常减压装置上的控制策略;王勇等;《化工自动化及仪表》;20031231;全文 * |
| 杨鑫等.第四节营销控制5.统计控制图法.《市场学教程》.西安：陕西人民出版社,1989,第92-93页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111506029A (en) | 2020-08-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhao et al. | Pricing decision for substitutable products with retail competition in a fuzzy environment | |
| Zu-Jun et al. | Managing channel profits of different cooperative models in closed-loop supply chains | |
| Woodford | Information-constrained state-dependent pricing | |
| Leijonhufvud | Agent-based macro | |
| CN110163427A (en) | A kind of method of shops's inventory optimization | |
| Otsu et al. | Population aging and potential growth in Asia | |
| Besanko et al. | On the role of demand and strategic uncertainty in capacity investment and disinvestment dynamics | |
| Chen et al. | Pricing policies of a dynamic green supply chain with strategies of retail service | |
| CN111506029B (en) | Industrial control method and device | |
| Tilson et al. | Monopoly production and pricing of finitely durable goods with strategic consumers׳ fluctuating willingness to pay | |
| Khin et al. | Critical factors of the natural rubber price instability in the world market | |
| Lin et al. | Market size, productivity and product quality regarding firm heterogeneity | |
| Duan et al. | Optimal pricing and deteriorating inventory control when inventory stimulates stochastic demand with reference price effect | |
| Peachavanish | Dual time frame relative strength stock selection using fuzzy logic | |
| Heer et al. | Automation, Economic Growth, and the Labor Share-A Comment on Prettner (2019) | |
| Angyridis et al. | Negative income taxes, inequality and poverty | |
| Wang et al. | Could the e-commerce platform’s big data analytics ease the channel conflict from manufacturer encroachment? an analysis based on information sharing and risk preference | |
| US20210158271A1 (en) | Determining seasonality in intermittent inventory demand | |
| Casson | Women's landownership in England in the nineteenth century | |
| Putra et al. | Determinants of Price Fluctuation for Cooking Oil Commodity in Aceh Province, Indonesia | |
| Rudolph et al. | B. ESSAY I | |
| Hamamura et al. | Over-investment and product market competition | |
| Oh et al. | The effect of performance measurement systems on productive performance: an empirical study of Italian manufacturing firms | |
| Zhang | GOVERNMENTS’DEBTS AND PUBLIC GOODS IN A MULTICOUNTRY GROWTH MODEL WITH TRADABLE AND NON-TRADABLE GOODS | |
| Shenoy | The integration of the indian wheat sector into the global market |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 160 Waishi Village, Liubu Town, Licheng District, Jinan City, Shandong Province Applicant after: Wang Sisheng Address before: 160 Waishi Village, Liubu Town, Licheng District, Jinan City, Shandong Province, 250000 Applicant before: Wang Shibo |
|
| CB02 | Change of applicant information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Wang Sisheng Inventor before: Wang Shibo |
|
| CB03 | Change of inventor or designer information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |