CN202257107U - Simplified fuzzy PID (Proportion Integration Differentiation) controller - Google Patents
Simplified fuzzy PID (Proportion Integration Differentiation) controller Download PDFInfo
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- CN202257107U CN202257107U CN2011203511208U CN201120351120U CN202257107U CN 202257107 U CN202257107 U CN 202257107U CN 2011203511208 U CN2011203511208 U CN 2011203511208U CN 201120351120 U CN201120351120 U CN 201120351120U CN 202257107 U CN202257107 U CN 202257107U
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Abstract
The utility model discloses a simplified fuzzy PID (Proportion Integration Differentiation) controller, comprising a PID regulating unit, and further comprising a sampling module, a data processing module and a control parameter storage module, wherein the data processing module selects a corresponding control parameter value from the control parameter storage module according to data acquired from the sampling module and sends the corresponding control parameter value to the PID regulating unit, and the PID regulating unit is used for carrying out regulation according to the received control parameter value. According to the simplified fuzzy PID controller provided by the utility model, a PID formula is simplified to be only one control parameter, the control parameter value under various working conditions can be determined according to a fuzzy control rule and fuzzy inference, so that the control parameter value corresponding to current working condition can be inquired according to the actual working condition and regulation can be performed by using the the control parameter value; and therefore, the PID controller has an online self-adaptive function and overcomes the affect of change in a controlled process on the control result.
Description
Technical field
The utility model relates to the PID controller, relates in particular to a kind of fuzzy controller of simplification.
Background technology
PID controller (proportional-integral derivative controller) is made up of ratio unit P, integral unit I and differentiation element D, comes the realization system to regulate through the setting to Kp, Ki and three parameters of Kd.The PID controller mainly is applicable to substantially linear and dynamic perfromance time invariant system.
In the prior art, fuzzy controller is on the basis of conventional PID control device, adds a fuzzy control link and constitutes.Wherein, the fuzzy control link is according to the real-time status of system, online three parameters of regulating the PID controller respectively.Because this kind control mode needs three parameters of simultaneously online adjusting PID controller, fuzzy inference rule is too complicated, and expressed expertise knowledge is rough often and incomplete.
The utility model content
The utility model provides a kind of fuzzy controller of simplification to the drawback of prior art.
The fuzzy controller of the described simplification of the utility model comprises the PID regulon, also comprises sampling module, data processing module and controlled variable storage module; Wherein, choose corresponding control parameter value in the image data Self Control parameter storage module of said data processing module according to sampling module and be sent to the PID regulon, said PID regulon is regulated according to the control parameter value that this receives.
In the fuzzy controller of the described simplification of the utility model; With the PID simplified formula for having only a controlled variable; And confirm the value of this controlled variable under various operating modes according to fuzzy control rule and fuzzy reasoning, thus can inquire control parameter value corresponding under the current working according to actual condition, and utilize this control parameter value to regulate; Make the PID controller have the online adaptive function, overcome controlled process and changed influence the control effect.
Description of drawings
Fig. 1 is the structural representation of the fuzzy controller of the said simplification of the utility model;
Fig. 2 is the controlled variable K in the fuzzy controller of the said simplification of the utility model
pValue and each factor concern synoptic diagram.
Embodiment
Below in conjunction with accompanying drawing the utility model is done further detailed description, can implement according to this with reference to the instructions literal to make those skilled in the art.
As shown in Figure 1, the fuzzy controller of the described simplification of the utility model comprises the PID regulon, also comprises sampling module, data processing module and controlled variable storage module; Wherein, choose corresponding control parameter value in the image data Self Control parameter storage module of said data processing module according to sampling module and be sent to the PID regulon, said PID regulon is regulated according to the control parameter value that this receives.
In the fuzzy controller of the described simplification of the utility model, utilize expanding critical proportion zone method with the PID simplified formula for having only a controlled variable, and confirm the value of this controlled variable under various operating modes according to fuzzy control rule and fuzzy reasoning.The value of said controlled variable under various operating modes then is stored in the controlled variable storage module.
In the utility model, controlled variable K
pValue relevant with many factors.Fig. 2 is controlled variable K
pValue and each factor concern synoptic diagram.According to shown in Figure 2, e (t) is the deviate of sampling instant controlled volume, and Δ e (t) is the deviation variation rate of sampling instant controlled volume; K
eAnd K
Δ eBe respectively the quantizing factor of deviation and deviation variation rate, K
Δ KpBe Δ K
pScale factor; I
eAnd I
Δ eBe respectively the quantized value of deviation and deviation variation rate, I
Δ KpBe Δ K
pQuantized value, u (t) is the controlled quentity controlled variable that is finally obtained by PID.Through above-mentioned quantizing factor and scale factor are done suitable adjustment, just can change controlled variable K
pValue.
In the utility model; Said data processing module is confirmed the present located operating mode through the image data of sampling module; And then can inquire the corresponding control parameter value under current working that stores in the controlled variable storage module according to current actual condition; Said PID regulon then utilizes this control parameter value to carry out system and regulates, and makes the PID controller have the online adaptive function, has overcome controlled process and has changed the influence to the control effect.The fuzzy controller of the described simplification of the utility model has overcome the defective that existing P ID controller can not online adjustment, has simplified adjustment process simultaneously again.Through the checking of contrast simulation experiment, the control performance of the fuzzy controller of the described simplification of the utility model is superior to existing P ID controller.
Although the embodiment of the utility model is open as above; But it is not restricted to listed utilization in instructions and the embodiment; It can be applied to the field of various suitable the utility model fully, for being familiar with those skilled in the art, can easily realize other modification; Therefore under the universal that does not deviate from claim and equivalency range and limited, the legend that the utility model is not limited to specific details and illustrates here and describe.
Claims (1)
1. the fuzzy controller of a simplification comprises the PID regulon, it is characterized in that, also comprises sampling module, data processing module and controlled variable storage module; Wherein,
Choose corresponding control parameter value in the image data Self Control parameter storage module of said data processing module according to sampling module and be sent to the PID regulon, said PID regulon is regulated according to the control parameter value that this receives.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011203511208U CN202257107U (en) | 2011-09-19 | 2011-09-19 | Simplified fuzzy PID (Proportion Integration Differentiation) controller |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011203511208U CN202257107U (en) | 2011-09-19 | 2011-09-19 | Simplified fuzzy PID (Proportion Integration Differentiation) controller |
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| Publication Number | Publication Date |
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| CN202257107U true CN202257107U (en) | 2012-05-30 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN2011203511208U Expired - Lifetime CN202257107U (en) | 2011-09-19 | 2011-09-19 | Simplified fuzzy PID (Proportion Integration Differentiation) controller |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104142376A (en) * | 2014-07-17 | 2014-11-12 | 上海冷杉精密仪器有限公司 | Control method for gas path system of gas chromatograph |
| CN109465775A (en) * | 2018-12-25 | 2019-03-15 | 国网江苏省电力有限公司检修分公司 | A kind of remote locking device of high-voltage electrical apparatus and method |
-
2011
- 2011-09-19 CN CN2011203511208U patent/CN202257107U/en not_active Expired - Lifetime
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104142376A (en) * | 2014-07-17 | 2014-11-12 | 上海冷杉精密仪器有限公司 | Control method for gas path system of gas chromatograph |
| CN104142376B (en) * | 2014-07-17 | 2016-05-11 | 上海冷杉精密仪器有限公司 | The air-channel system control method of gas chromatograph |
| CN109465775A (en) * | 2018-12-25 | 2019-03-15 | 国网江苏省电力有限公司检修分公司 | A kind of remote locking device of high-voltage electrical apparatus and method |
| CN109465775B (en) * | 2018-12-25 | 2023-12-22 | 国网江苏省电力有限公司检修分公司 | High-voltage electric remote locking device |
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Legal Events
| Date | Code | Title | Description |
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| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CX01 | Expiry of patent term | ||
| CX01 | Expiry of patent term |
Granted publication date: 20120530 |