CN101561661B - Fuzzy control method and fuzzy controller - Google Patents
Fuzzy control method and fuzzy controller Download PDFInfo
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Abstract
The invention discloses a fuzzy control method and a fuzzy controller, wherein the fuzzy control method comprises the following steps: receiving detection input quantity input by a detection device, and mapping a deviation value of the detection input quantity and a set value to an input discourse domain to obtain fuzzy input quantity; performing fuzzy reasoning and fuzzy decision according to thefuzzy input quantity to obtain fuzzy control output quantity of a corresponding output discourse domain; and converting the fuzzy control output quantity into control output quantity, outputting the control output quantity to an actuating mechanism, and controlling the controlled object by the actuating mechanism according to the control output quantity. Through fuzzy control method and the fuzzycontroller, the chlorination in a water plant can reach optimal control effect.
Description
Technical field
The present invention relates to the fuzzy control field, relate in particular to a kind of fuzzy control method and fuzzy controller.
Background technology
The application of control technology is very extensive, and for example, China is the main sanitizer that uses in the drinking water disinfection with chlorine for a long time, in the drinking water disinfection process, needs the addition of control chlorine.Can remove ammonia nitrogen, stink and pathogenic microorganisms by chlorination on the one hand, and algal grown in settling basin and the filter tank is played control action; On the other hand also can be by in the distribution system of water supply, keeping residual chlorine, preventing microbial re-growth, so chlorination is the key link in the conventional water treatment procedure of water factory.In process conditions one regularly, the dosage of chlorine directly has influence on the result of sterilization.Realize adding chlorine process with best feed rate,, save the consumption of chlorine simultaneously, become the major subjects that people study always aspect chlorination control to meet water quality requirement.
But, mainly there is following technological deficiency in the chlorination control of prior art: the traditional control method and the design of controller all need to be based upon on the basis of the mathematical model that controlled device is accurately controlled, but in practice, a lot of influence factors in water factory's chlorination make and are difficult for drawing precise math model.For example, the influence factor that experimental studies have found that chlorination is a lot, time, hydraulics of the classification of pH value, basicity, conductivity, water temperature, suspended impurity of former water and chlorination etc. are arranged, this with regard to make this process exist non-linear, the time problem such as stickiness, ambiguity, add the also unified mathematical model of neither one of chlorine process, brought sizable difficulty for on-the-spot chlorination.
Summary of the invention
The purpose of this invention is to provide a kind of fuzzy control method and fuzzy controller, solve non-linear in the control procedure, strong coupling, time and become and hysteresis characteristic causes can not realize the accurately problem of control to controlled device, make this fuzzy control method and fuzzy controller to reach best control effect controlled device.
For achieving the above object, the invention provides a kind of fuzzy control method, comprising:
The detection input quantity that receiving detection device sends, described detection input quantity is the residual chlorine amount of water factory's sampling spot, and the deviate of described detection input quantity and setting value is mapped on the input domain, obtains bluring input quantity;
Carry out fuzzy reasoning and decision-making by described fuzzy input quantity, obtain the fuzzy control output quantity of corresponding output domain;
Described fuzzy control output quantity defuzzification is the control output quantity, and exports described control output quantity to topworks, according to described control output quantity controlled device is controlled by described topworks.
The invention provides a kind of fuzzy controller, comprising:
Load module is used for the detection input quantity that receiving detection device sends, and described detection input quantity is the residual chlorine amount of water factory's sampling spot, and the deviate of described detection input quantity and setting value is mapped on the input domain, obtains bluring input quantity;
Processing module is used for carrying out fuzzy reasoning and decision-making by the fuzzy input quantity that described load module obtains, and obtains the fuzzy control output quantity of corresponding output domain;
Output module, the fuzzy control output quantity defuzzification that is used for described processing module is obtained is the control output quantity, and exports described control output quantity to topworks, controlled device is controlled according to described control output quantity by described topworks.
As shown from the above technical solution, the present invention is by adopting fuzzy control method, the detection input quantity of pick-up unit input is obtained fuzzy control quantity according to fuzzy theory, and controlled device is controlled according to the control output quantity behind the ambiguity solution, having overcome non-linear, strong coupling in the existing control procedure, time becomes and hysteresis characteristic causes does not have uniform mathematical model, control inaccurate problem, make control procedure more accurate, reached better control effect.
Description of drawings
Fig. 1 is the schematic flow sheet of fuzzy control method first embodiment of the present invention;
Fig. 2 is the schematic flow sheet of fuzzy control method second embodiment of the present invention;
Fig. 3 is the structural representation of fuzzy controller first embodiment of the present invention;
Fig. 4 is the structural representation of fuzzy controller second embodiment of the present invention;
Fig. 5 is applied to the system architecture diagram of water factory's chlorination Fuzzy control system for fuzzy controller of the present invention.
Embodiment
Below by drawings and Examples, technical scheme of the present invention is described in further detail.
Fig. 1 is the schematic flow sheet of fuzzy control method first embodiment of the present invention, and as shown in Figure 1, the fuzzy control method of present embodiment comprises:
The detection input quantity that step 101, receiving detection device send is mapped to the deviate of this detections input quantity and setting value and imports on the domain, obtains bluring input quantity.
After the fuzzy controller of present embodiment receives the detection input quantity that pick-up unit sends, should detect input quantity and setting value compares, obtain deviate; Wherein, setting value is equivalent to a control target of this control system.Fuzzy controller carries out Fuzzy processing with the above-mentioned deviate that obtains, and is mapped on the corresponding input domain, obtains fuzzy input quantity.
With the fuzzy input quantity and the fuzzy control rule that obtain is fuzzy relation, makes fuzzy decision according to the composition rule of fuzzy reasoning, just can obtain the fuzzy control output quantity.
For controlled device being applied accurate control, needing that also the fuzzy control output quantity that obtains according to fuzzy control rule is carried out defuzzification handles, the control output quantity that obtains determining should be controlled output quantity by fuzzy controller again and export to topworks, and controlled device is controlled.
The present embodiment fuzzy control method is by adopting fuzzy control method, the detection input quantity of pick-up unit input is obtained fuzzy control quantity according to fuzzy theory, and controlled device is controlled according to the control output quantity behind the ambiguity solution, having overcome non-linear, strong coupling in the existing control procedure, time becomes and hysteresis characteristic causes does not have uniform mathematical model, control inaccurate problem, make control procedure more accurate, reached better control effect.
Fig. 2 is the schematic flow sheet of fuzzy control method second embodiment of the present invention, present embodiment is that example is elaborated to fuzzy control method of the present invention with control water factory chlorination, the main thought of present embodiment is, fuzzy control theory is applied to water factory's chlorination control.And need to prove, below each step in the fuzzy control method be not limited to order in the present embodiment, its concrete order of implementing can change, as long as can finish each function in this method.As shown in Figure 2, this method comprises:
The detection input quantity of step 201, receiving detection device input is mapped to the deviate of this detections input quantity and setting value and imports on the domain, obtains bluring input quantity.
Fuzzy controller can comprise programmable logic controller (PLC) (Programmable logic Controller, hereinafter to be referred as: PLC) and PC, PLC wherein promptly detects input quantity through the signal numerical value that obtains the input of chlorine residue analyser that interrupts sampling, this value and setting value are relatively obtained deviate, wherein, setting value is represented control target; Fuzzy controller as input quantity, and carries out Fuzzy processing with this deviate with the deviate of this chlorine residue, and it is mapped on the corresponding input domain, obtains the promptly fuzzy input quantity of a fuzzy subset.
Wherein, detecting input quantity is the sampling spot chlorinty input domain E corresponding with the deviation e of setting value, and the control output quantity is that the output domain U of the frequency variation u correspondence of variable-frequence governor output determines according to fuzzy theory.If the range ability of deviation e is-15---+15MG/L (mg/litre), i.e. [15 ,+15]; Fuzzy controller is-20 to the frequency variation u range ability of variable-frequence governor output---+20Hz, i.e. [20,20].Input domain E and output domain U are decided to be 7 grades and 9 grades respectively, promptly for discrete limited domain
E＝{-3，-2，-1，0，1，2，3}
U＝{-4，-3，-2，-1，0，1，2，3，4}
Deviation e range ability [15, + 15] Nei numerical value can shine upon and be transformed into input domain E, frequency variation u range ability [20,20] Nei numerical value can shine upon and be transformed into output domain U, each grade among input domain E and the output domain U corresponding respectively the numerical value of the certain limit in e and the u range ability.In the present embodiment, deviation e transforms to input domain E by quantizing factor k, and k is 0.2.Be specially by each the grade value corresponding scope among the definite input of the following rule domain E, comprise 3 kinds of situations:
Situation 1:m≤ke≤m+1, m＜n
Situation 2:ke＜-n
Situation 3:ke＞n
For situation 2 and situation 3, respectively e is quantified as-n and n.For situation 1, if m≤ke≤m+0.5 then is quantified as m with e; If m+0.5≤ke≤m+1, then e is quantified as m+1, wherein m is a certain integer, and n is the shelves number that is divided into after the continuous deviation discretize (or quantification) in 0～e scope, constitute the element of input domain E, this paper for example gets n=3., and deviation e is+5 o'clock, ke=0.2 * (+5)=1, grade " 1 " in the corresponding input domain E, deviation e is+7 o'clock, and ke=0.2 * (+7)=1.4＜1+0.5 also should the interior grade " 1 " of corresponding input domain E.The Fuzzy processing of deviation e is lifted with next example: for example, be+10MG/L if to detect input quantity be deviation e, then it is mapped to input domain E just can obtain fuzzy input quantity be 0,0,0,0,0,1,0}.
Determine that selected detection input quantity is that sampling spot chlorinty deviation e and control output quantity are promptly exported the control fuzzy language value that u got and be: { PB (honest), PS (just little), ZO (0), NS (negative little), NB (negative big).
Each fuzzy language value of this linguistic variable of chlorinty deviation e, promptly each fuzzy subset is defined on the input domain E, and its subordinate function is by normal distyribution function
(the x value is the element value (representative value of process mapping back deviation also is the different brackets value in the domain) in the domain in the formula, μ
XValue is then represented the degree of membership of each fuzzy language value corresponding to domain).Parameter a is for fuzzy set PB in the formula, and PS, ZO, NS, NB get respectively+and 3 ,+1,0 ,-1,3; Parameter b is rule of thumb got (b gets 2.1 in the present embodiment).Each fuzzy language value of this linguistic variable of chlorinty deviation e, promptly each fuzzy subset is defined on the input domain E, and its membership function value is listed in table one; Each fuzzy language value of this linguistic variable of output control u, promptly each fuzzy subset is defined on the output domain U, and its membership function value is listed in table two.Wherein, in table one and table two, first row is representative input domain E and the different brackets of exporting among the domain U respectively, first row are represented each fuzzy language value of chlorinty deviation e and each fuzzy language value of output control u respectively, and the center section of form is represented the degree of membership of each fuzzy language value corresponding to domain.Table one and table two are as follows respectively:
The subordinate function of table one chlorinty deviation e language value
Table two output frequency changes the subordinate function of u language value
Determine the fuzzy rule base of chlorination based on the experience of manual operator long-term accumulation and expert's relevant knowledge, it comprises following 5 rules:
If E is NB, then U is PB, otherwise
If E is NS, then U is PS, otherwise
If E is ZO, then U is ZO, otherwise
If E is PS, then U is NS, otherwise
If E is PB, then U is NB.
As above 5 rules constitute one 5 sections fuzzy condition statement, and the fuzzy relation R of its expression should be so
R＝∪Ri(i＝1-5)..........................................(1)
In the formula: Ri is the cartesian product of 5 sections corresponding fuzzy vectors of fuzzy condition statement, i=1-5.
R1＝(1.0，0.8，0.4，0，0，0，0)×(0，0，0，0，0，0，0.4，0.8，1.0)
R2, R3, R4, R5 ask the same R1 of method, behind the branch fuzzy relation matrix of obtaining R1, R2, R3, R4, R5 correspondence respectively, again to each minute fuzzy relation matrix ask union, just can obtain fuzzy relationship matrix r.
By the fuzzy reasoning composition rule, carry out fuzzy decision by the fuzzy relation of E and R is synthetic, the fuzzy value that obtains the output variable of fuzzy control is that fuzzy control output quantity U is
U＝E·R..........................................(2)
The fuzzy control output quantity is carried out defuzzification to be handled, the control output quantity that obtains determining, pass to PLC by the PC in this fuzzy controller by RS-485 communication protocol again, export to variable-frequence governor by PLC at last, by adding of variable-frequence governor output frequency variable quantity control chlorine.
The fuzzy control method that facts have proved present embodiment have need not know controlled device (or) mathematical model of process, be easy to realize control with object with strong nonlinearity to having probabilistic object, interference for control system has stronger advantages such as inhibition ability, has obtained good effect in the control at the scene.
The present embodiment fuzzy control method is by adopting fuzzy control method, the detection input quantity of pick-up unit input is obtained fuzzy control quantity according to fuzzy theory, and controlled device is controlled according to the control output quantity behind the ambiguity solution, having overcome non-linear, strong coupling in the existing control procedure, time becomes and hysteresis characteristic causes does not have uniform mathematical model, control inaccurate problem, make control procedure more accurate, reached better control effect.
Fig. 3 is the structural representation of fuzzy controller first embodiment of the present invention, and as shown in Figure 3, the fuzzy controller of present embodiment comprises load module 31, processing module 32 and the output module 33 that connects successively.
Concrete, the fuzzy controller of present embodiment is in application, after load module 31 receives the detection input quantity of pick-up unit detection transmission, should detect input quantity and setting value compares and obtains deviate, and deviate carried out Fuzzy processing, be mapped to and obtain fuzzy input quantity on the corresponding input domain, as the input quantity of processing module 32.The fuzzy input quantity that processing module 32 sends load module 31 carries out fuzzy reasoning and decision-making obtains the fuzzy control output quantity, and exports it to output module 33.Precisely controlled output quantity after the fuzzy control output quantity defuzzification that output module 33 obtains processing module 32 will be controlled output quantity and export topworks to, controlled device be controlled according to this control output quantity by topworks.
The present embodiment fuzzy controller is by adopting fuzzy control method, the detection input quantity of pick-up unit input is obtained fuzzy control quantity according to fuzzy theory, and controlled device is controlled according to the control output quantity behind the ambiguity solution, having overcome non-linear, strong coupling in the existing control procedure, time becomes and hysteresis characteristic causes does not have uniform mathematical model, control inaccurate problem, make control procedure more accurate, reached better control effect.
Fig. 4 is the structural representation of fuzzy controller second embodiment of the present invention, and as shown in Figure 4, the fuzzy controller of present embodiment is on the basis of first embodiment, and processing module 32 further comprises function unit 321, regular unit 322 and synthesis unit 323.
Wherein, function unit 321 is used for respectively determining described detection input quantity and the fuzzy language value of control output quantity and the subordinate function of described fuzzy language value, and described subordinate function comprises the subordinate function of the corresponding described output domain of fuzzy language value of the subordinate function of the corresponding described input domain of fuzzy language value of described detection input quantity and described control output quantity.Rule unit 322 is used for the subordinate function according to described fuzzy language value, the fuzzy vector of each the fuzzy condition statement correspondence in the fuzzy rule base is done cartesian product obtains the branch fuzzy relation matrix, and with described each minute fuzzy relation matrix do union and obtain fuzzy relation matrix.Synthesis unit 323 is used for according to the fuzzy reasoning composition rule, by described fuzzy input quantity and the synthetic fuzzy control output quantity that obtains of described fuzzy relation matrix.
Below in conjunction with Fig. 5 the application of the fuzzy controller of present embodiment is described, Fig. 5 is applied to the system architecture diagram of water factory's chlorination Fuzzy control system for fuzzy controller of the present invention.The structure of present embodiment system is composed as follows: as shown in Figure 5, the fuzzy controller 4 of present embodiment is the core of this control system, also be the outstanding feature that Fuzzy control system is different from other automatic control systems, it can be a simple single-point fuzzy controller in the present embodiment.The Fuzzy control system of present embodiment also comprises pick-up unit 5 and topworks 6 outside fuzzy controller 4.
The concrete application of present embodiment Fuzzy control system is as follows: pick-up unit 5 adopts the chlorine residue analyser that water quality is detected in real time.Input interface in the fuzzy controller 4 is connected with pick-up unit 5, suppose that a certain moment i pick-up unit 5 to the detection input quantity ei of fuzzy controller 4 inputs is+5MG/L, input interface is converted to computer system to detection signal and can discerns the digital signal of handling and send load module 31 to, load module 31 is mapped to this input signal on the input domain E, is the point " 1 " on the E.Press the method for single-point obfuscation, the fuzzy set E of ei obfuscation then is E=(0,0,0,0,1,0,0).The subordinate function of the fuzzy language value that rule unit 322 can obtain according to function unit 321 is done cartesian product with the fuzzy vector of each the fuzzy condition statement correspondence in the fuzzy rule base and is done union again and obtain fuzzy relationship matrix r.Then, synthesis unit 323 synthesizes the fuzzy value that obtains the fuzzy control output quantity with E and R:
U＝E·R＝(0，0，0，0，1，0，0)·R＝(0.4，0.8，1.0，0.8，0.8，0.8，0.4，0.4，0.4)
Grade " 2 " among the corresponding output in " 1.0 " in the The above results domain U, then according to minimum degree of membership principle, choose controlled quentity controlled variable and be-2 grades, it is mapped to output domain [20,20] on, output frequency variable quantity ui when obtaining corresponding to a certain moment i input signal ei to+5MG/L be-2 * 20/4=-10Hz, promptly requires the frequency minimizing 10Hz of variable-frequence governor.Then, the output interface of fuzzy controller 4 is converted to for example desired simulating signal of variable-frequence governor of topworks 6 to fuzzy control output quantity U; System adopts S7-224PLC to include mould/number conversion and D/A switch function, has solved interface problem well.To be fuzzy controllers apply the device of control action to controlled device in topworks 6, and the present embodiment Fuzzy control system has adopted the extra small variable-frequence governor of the VFO of Panasonic.It can be the power supply output of corresponding frequencies with the power source conversion of fixed frequency of input, supplies with the dosing pump motor, regulates the rotating speed of pump, and then adding by chlorinating machine 7 control chlorine.
In addition, the Fuzzy control system of present embodiment can comprise feedforward and feedback two parts, wherein, feedback fraction promptly adopts above-mentioned fuzzy controller to carry out fuzzy control, the feedforward part can adopt the Fuzzy Expert Control method, according to a large amount of in the past historical datas, set up the rule database of raw water flow, raw water turbidity and unit water chlorine dosage.Above-mentioned according to fuzzy control method chlorine dosage is accurately controlled after, can bring in constant renewal in according to the controlled quentity controlled variable data that accurately obtain, the data in the rule database of correcting feedforward part.
Need to prove, fuzzy control method of the present invention and fuzzy controller are equally applicable to other technologies outside water factory's chlorination, for example, coagulation process also will be controlled coagulant charging quantity in the water factory, this moment also can fuzzy control method of the present invention and fuzzy controller, only corresponding parameters need be carried out corresponding modify and get final product, as: the chlorinty deviation need change turbidity deviation etc. into.
The present embodiment fuzzy controller is by adopting fuzzy control method, the detection input quantity of pick-up unit input is obtained fuzzy control quantity according to fuzzy theory, and controlled device is controlled according to the control output quantity behind the ambiguity solution, having overcome non-linear, strong coupling in the existing control procedure, time becomes and hysteresis characteristic causes does not have uniform mathematical model, control inaccurate problem, make control procedure more accurate, reached better control effect.
It should be noted that at last: above embodiment is only in order to technical scheme of the present invention to be described but not limit it, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that: it still can make amendment or be equal to replacement technical scheme of the present invention, and these modifications or be equal to replacement and also can not make amended technical scheme break away from the spirit and scope of technical solution of the present invention.
Claims (7)
1. a fuzzy control method is characterized in that, comprising:
The detection input quantity that receiving detection device sends, described detection input quantity is the residual chlorine amount of water factory's sampling spot, and the deviate of described detection input quantity and setting value is mapped on the input domain, obtains bluring input quantity;
Carry out fuzzy reasoning and decision-making by described fuzzy input quantity, obtain the fuzzy control output quantity of corresponding output domain;
Described fuzzy control output quantity defuzzification is the control output quantity, and exports described control output quantity to topworks, according to described control output quantity controlled device is controlled by described topworks.
2. fuzzy control method according to claim 1 is characterized in that, described deviate with described detection input quantity and setting value also comprises before being mapped on the input domain:
Determine the input domain of described deviate correspondence and the output domain of described fuzzy control output quantity correspondence according to fuzzy theory.
3. fuzzy control method according to claim 1 and 2 is characterized in that, describedly carries out fuzzy reasoning and decision-making by described fuzzy input quantity, and the fuzzy control output quantity that obtains corresponding output domain comprises:
Determine described detection input quantity and the fuzzy language value of control output quantity and the subordinate function of described fuzzy language value respectively, described subordinate function comprises the subordinate function of the corresponding described output domain of fuzzy language value of the subordinate function of the corresponding described input domain of fuzzy language value of described detection input quantity and described control output quantity;
According to the subordinate function of described fuzzy language value, the fuzzy vector of each the fuzzy condition statement correspondence in the fuzzy rule base is done cartesian product obtains the branch fuzzy relation matrix, and with described each minute fuzzy relation matrix do union and obtain fuzzy relation matrix;
According to the fuzzy reasoning composition rule, by described fuzzy input quantity and the synthetic fuzzy control output quantity that obtains of described fuzzy relation matrix.
4. fuzzy control method according to claim 3 is characterized in that, the fuzzy language value of described detection input quantity and control output quantity includes:
PB-is honest, PS-is just little, ZO-zero, NS-bear little and NB-is negative big.
5. fuzzy control method according to claim 4 is characterized in that, the fuzzy condition statement in the described fuzzy rule base comprises:
If fuzzy input quantity is for negative big, then fuzzy control output quantity is honest, otherwise
If fuzzy input quantity is for negative little, then fuzzy control output quantity is for just little, otherwise
If fuzzy input quantity is zero, then fuzzy control output quantity is zero, otherwise
If fuzzy input quantity is for just little, then fuzzy control output quantity is little for bearing, otherwise
If fuzzy input quantity is honest, then fuzzy control output quantity is for negative big.
6. a fuzzy controller is characterized in that, comprising:
Load module is used for the detection input quantity that receiving detection device sends, and described detection input quantity is the residual chlorine amount of water factory's sampling spot, and the deviate of described detection input quantity and setting value is mapped on the input domain, obtains bluring input quantity;
Processing module is used for carrying out fuzzy reasoning and decision-making by the fuzzy input quantity that described load module obtains, and obtains the fuzzy control output quantity of corresponding output domain;
Output module, the fuzzy control output quantity defuzzification that is used for described processing module is obtained is the control output quantity, and exports described control output quantity to topworks, controlled device is controlled according to described control output quantity by described topworks.
7. fuzzy controller according to claim 6 is characterized in that, described processing module comprises:
Function unit, be used for respectively determining described detection input quantity and the fuzzy language value of control output quantity and the subordinate function of described fuzzy language value, described subordinate function comprises the subordinate function of the corresponding described output domain of fuzzy language value of the subordinate function of the corresponding described input domain of fuzzy language value of described detection input quantity and described control output quantity;
The rule unit, the subordinate function that is used for the fuzzy language value that obtains according to described function unit, the fuzzy vector of each the fuzzy condition statement correspondence in the fuzzy rule base is done cartesian product obtains the branch fuzzy relation matrix, and with described each minute fuzzy relation matrix do union and obtain fuzzy relation matrix;
Synthesis unit is used for according to the fuzzy reasoning composition rule, the synthetic fuzzy control output quantity that obtains of the fuzzy relation matrix that is obtained by described fuzzy input quantity and described regular unit.
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| CN105159075B (en) * | 2015-08-20 | 2018-04-17 | 河南科技大学 | A kind of fuzzy controller |
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