CN102032640A - Fuzzy proportion integration differentiation (PID) control method and device for industrial environment high-precision air conditioner - Google Patents
Fuzzy proportion integration differentiation (PID) control method and device for industrial environment high-precision air conditioner Download PDFInfo
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Abstract
The invention discloses a fuzzy proportion integration differentiation (PID) control method and a fuzzy PID control method device for an industrial environment high-precision air conditioner. The method comprises the following steps of: selecting an input quantity of a fuzzy PID controller as a deviation e between an expected value and an actual output and a deviation change rate ec, and establishing a bivariate continuous function relation between parameters Kp, Ki and Kd and the absolute value of the deviation and the absolute value of the deviation change, wherein output quantities are the correction quantities delta Kp, delta Ki and delta Kd of the PID parameters; and determining a fuzzy relation between the three PID parameters and the deviation e and the deviation change rate ec, continuously detecting e and ec in operation, adjusting the three parameters on line according to a fuzzy control theory to obtain adjusted Kp, Ki and Kd, and inputting Kp, Ki and Kd into the PID controller. The control device comprises a fuzzy control circuit on a circuit board, wherein a self-setting mechanism circuit for setting the parameters on line is also arranged on the fuzzy control circuit. The precision of the temperature, humidity and pressure difference control of the industrial environment high-precision air conditioner is improved by introducing the fuzzy control into the conventional PID controller and comprehensively using the characteristics of the conventional PID controller and the fuzzy controller.
Description
Technical field
What the present invention relates to is the air-conditioning automation control area, and what be specifically related to is the fuzzy PID control method and the device of the air-conditioning in a kind of industrial environment.
Background technology
Conventional normal temperature, humidity, the pressure reduction that adopts the PID controller to control air-conditioning of air-conditioning control.Proportional-integral-differential (PID) controller is modal a kind of controlled adjuster in industrial process control, it is the error according to system, proportion of utilization, integration, difference gauge calculate that controlled quentity controlled variable controls, and system is made up of PID controller and controlled device.
Conventional PID control principle as shown in Figure 1.The PID controller is a kind of linear controller, and it constitutes control deviation: e (t)=r (t)-u (t) according to set-point r (t) and real output value u (t)
Ratio (P), integration (I) and the differential (D) of deviation are constituted controlled quentity controlled variable by linear combination, controlled device is controlled, so be called the PID controller.Its control law is
Kp in the formula---ratio multiplication factor; Ti---the time of integration; Td---derivative time.
Conventional PID controller architecture is simple, has certain robustness, realize easily, and the stable state floating, the control accuracy height can satisfy the control requirement of most of industrial process.But there is significant limitation in conventional PID controller, and it mainly is at the field of linear control and the control system that can set up mathematical models.As the application of high accuracy air-conditioning in the chamber by experiment, the temperature controlling range of conventional control is at 21.6 ℃-24.4 ℃, and the requirement that the design of the room temperature of contrast experiment chamber is 22 ℃-24 ℃ is to satisfy.
The positive negative pressure of industrial environment high accuracy air-conditioning requirement constant temperature, constant humidity, strictness, humiture belongs to thermal object in its control object, and Mathematical Modeling can't be set up.In addition because control procedure existing in various degree is non-linear, hysteresis, parameter time varying and model uncertainty, thereby be to obtain satisfied control effect the control of the temperature of industrial environment high accuracy air-conditioning and room pressure reduction being adopted conventional PID control, so we introduce fuzzy control and realize.
Summary of the invention
The present invention seeks to be to solve the precision problem of industrial environment high accuracy air-conditioner temperature, humidity, pressure reduction control, and a kind of fuzzy control of introducing in conventional PID controller is provided, the characteristic that fully utilizes conventional PID controller and fuzzy controller improves the fuzzy PID control method and the device of the industrial environment high accuracy air-conditioning of industrial environment high accuracy air-conditioner temperature, humidity, pressure reduction control accuracy.
To achieve these goals, the present invention realizes by the following technical solutions:
The fuzzy PID control method of industrial environment high accuracy air-conditioning, its method is: the input quantity of selecting fuzzy controller is desired value and actual deviation e that exports and deviation variation rate ec (E and EC are respectively the linguistic variables after e and ec quantize through input), set up parameter K p, Ki, Kd with the relation of the binary continuous function between absolute value of the bias and deviation change absolute value, output quantity is correction amount Kp, Δ Ki, the Δ Kd of pid parameter; Determine the fuzzy relation between three parameters of PID and deviation e and the deviation variation rate ec, be in operation by continuous detection e and ec, according to fuzzy control principle three parameters are carried out online adjustment again, after making the PID controller obtain new Kp, Ki, Kd, to control object output control corresponding, satisfying the different requirements to controller parameter during with deviation variation rate ec, thereby make controlled device have the good dynamic and static performance at different system deviation e.
Further, utilize triangle membership function figure to obtain degree of membership on E and EC quantized interval, and it is regular to carry out parameter according to the degree of membership of trying to achieve, and carries out corresponding reasoning and calculation according to fuzzy control rule again, obtains the accurate adjusted value of Δ Kp, Δ Ki, Δ Kd.
Further, pid parameter obtains Δ Kp by fuzzy reasoning and Fuzzy Calculation, Δ Ki, and the accurate adjusted value of Δ Kd, and according to adjusting the constantly online adjustment of formula realization.
The adjustment formula of described pid parameter is:
Kp＝KpO+ΔKp，Ki＝KiO+ΔKi，Kd＝KdO+ΔKd
KpO, KiO, KdO are the initial values of Kp, Ki, Kd in the formula.
The fuzzy control device of industrial environment high accuracy air-conditioning, comprise the fuzzy control circuit on the wiring board, it is characterized in that, described fuzzy control circuit be provided with a parameter on-line tuning from the setting mechanism circuit, should be fuzzy from the size of setting mechanism circuit according to input signal (being deviation e), characteristic such as direction and variation tendency, apish control thought, the output state of analysis and recognition system, make corresponding decision by fuzzy reasoning, dynamically independently to Kp, Ki, Kd carries out on-line tuning, to adjust the control characteristic of different phase in the whole control process.
Further, describedly comprise obfuscation, inference machine, ambiguity solution in operation successively from the setting mechanism circuit, parameter correction operating process, described inference machine comparable data storehouse and rule base are judged.
Further, described fuzzy controller is to realize by PLC, and system draws one group of Kp, Ki, Kd parameter by detected state deviation and deviation variation rate by the mode of tabling look-up, and changes corresponding pid parameter in the PLC program.
The present invention is according to the characteristics such as size, direction and variation tendency of input signal (being deviation e), apish control thought, the output state of analysis and recognition system, make corresponding decision by fuzzy reasoning, dynamically independently Kp, Ki, Kd are carried out on-line tuning, to adjust the control characteristic of different phase in the whole control process.Introduce fuzzy control in conventional PID controller, form fuzzy controller, the characteristic that fully utilizes conventional PID controller and fuzzy controller improves the precision of industrial environment high accuracy air-conditioner temperature, humidity, pressure reduction control, makes it adjust the precision height.
Description of drawings
Describe the present invention in detail below in conjunction with the drawings and specific embodiments;
Fig. 1 is conventional PID control principle figure.
Fig. 2 is a system architecture diagram of the present invention.
Fig. 3 is fuzzy subset's of the present invention triangle membership function figure.
Fig. 4 is the fuzzy figure of adjustment of pid parameter of the present invention.
Fig. 5 is system's main program flow chart of present embodiment.
Fig. 6 is the subprogram block diagram of tabling look-up.
The specific embodiment
For technological means, creation characteristic that the present invention is realized, reach purpose and effect is easy to understand, below in conjunction with the specific embodiment, further set forth the present invention.
As shown in Figure 2, the fuzzy PID control method of industrial environment high accuracy air-conditioning, its method is: the input quantity of selecting fuzzy controller is desired value and actual deviation e that exports and deviation variation rate ec (E and EC are respectively the linguistic variables after e and ec quantize through input), set up parameter K p, Ki, Kd with the relation of the binary continuous function between absolute value of the bias and deviation change absolute value, output quantity is correction amount Kp, Δ Ki, the Δ Kd of pid parameter; Determine the fuzzy relation between three parameters of PID and deviation e and the deviation variation rate ec, be in operation by continuous detection e and ec, according to fuzzy control principle three parameters are carried out online adjustment again, after making controller obtain new Kp, Ki, Kd, to control object output control corresponding, satisfying the different requirements to controller parameter during with deviation variation rate ec, thereby make controlled device have the good dynamic and static performance at different system deviation e.
The present invention is fuzzy to be a kind of on the basis of conventional PID controller from Adjustable PID Parameter Controller, use Fuzzy Set Theory and set up parameter K p, Ki, Kd concerns with the binary continuous function between absolute value of the bias and deviation change absolute value, and according to different and online self-tuning parameter K p, Ki, the fuzzy controller of Kd, it comprises the fuzzy control circuit on the wiring board, described fuzzy control circuit be provided with a parameter on-line tuning from the setting mechanism circuit, the present invention changes EC according to linguistic variable deviation E and deviation, uses Fuzzy Set Theory and draws Kp, Ki, the fuzzy model of adjusting of Kd.And according to the performance requirement of controlled device, system adopts a kind of blur from Tuning PID Controller device different with conventional PID controllers.Described fuzzy self-regulation mechanism is according to the characteristics such as size, direction and variation tendency of input signal (being deviation e), apish control thought, the output state of analysis and recognition system, make corresponding decision by fuzzy reasoning, dynamically independently Kp, Ki, Kd are carried out on-line tuning, to adjust the control characteristic of different phase in the whole control process.
Referring to Fig. 2, describedly comprise obfuscation, inference machine, ambiguity solution in operation successively from the setting mechanism circuit, parameter correction operating process inputs to after the parameter correction in the conventional pid parameter controller; Described inference machine comparable data storehouse and rule base are judged.
For elaborating control procedure of the present invention, embodiment is as follows:
Referring to Fig. 5 and Fig. 6, the object that industrial environment high accuracy air-conditioning need be controlled has room pressure reduction, room humiture, and humiture also has close coupling, be that humiture is interactive, but because temperature variable is to big (1 ℃ of the every rising of temperature of influence of humidity variables, relative humidity (RH) descends 2%～3%), and humidity is to Temperature Influence less (can ignore), and humidity change than variations in temperature slowly many, can carry out decoupling zero by compensation fully, be the design that example is carried out the temperature-rise period fuzzy controller with the temperature therefore.
(1) determines domain and quantizing factor
Because control system is that temperature is controlled, therefore the input of this algorithmic controller is respectively temperature deviation e and temperature deviation rate of change ec, temperature deviation input language variable is elected E as, temperature deviation rate of change input voice variable is elected EC as, output quantity is increment Delta Kp, Δ Ki, the Δ Kd of pid parameter, has so selected the fuzzy controller of one two input, three export structures for temperature control system.
Determine that domain and quantizing factor are exactly the error in temperature controlling range and permission, determine domain, discrete point and the quantizing factor of deviation and rate of change, and according to domain, discrete point and the quantizing factor determined rule of thumb, measured data in the engineering practice at first determines one group of the Δ Kp corresponding with deviation and rate of change domain, discrete point and quantizing factor, Δ Ki, Δ Kd quantization parameter.
(2) fuzzy subset's chooses and fuzzy assignment
For temperature error and temperature error rate of change, the ambiguity in definition subclass is on their domain: PB (honest), PM (center), PS (just little), ZE (zero), NS (bearing), NM (in negative), NB (negative big).
The fuzzy subset of control parameter output quantity is PB, PM, PS, ZE, NS, NM, NB.
Because this fuzzy controller will apply in the actual engineering, simple shape, amount of calculation is few, but conserve storage, and the membership function of triangle has bigger sensitivity than the membership function of normal distribution is when having one during with the deviation that sets value, output that just can a corresponding regulated quantity of very fast generation, therefore in line with simplify, practical principle, the membership function of choosing the fuzzy subset is the triangle membership function, membership function as shown in Figure 3:
By top definite membership function, can obtain fuzzy variable assignment table
(3) establishment, adjustment fuzzy control rule table
Fuzzy control rules is based on manual control strategy, and manually strategy is that the people passes through study, and test and protracted experience accumulate and form gradually.At first by the adjusting of the skilled grasp fuzzy control theory of theory study and PLC control principle and pid parameter, again by constantly practice, study again, practice draws certain fuzzy control rule again.Secondly, use for reference case, and its fuzzy control rule is used in the debugging of this project after by practice test with reference to some successful implementations.
In fact the formation of fuzzy reasoning table be exactly the manual control strategy that language is concluded, and is converted to machine recognizable control law by the notion of utilizing Fuzzy Set Theory and linguistic variable.
By the research of the pid parameter of Various Seasonal, different phase, various process in the debug process, test repeatedly, and go out following control principle in conjunction with knowledge and experience and the engineering debug practice summary that the knowledge and the pid parameter of fuzzy theory are adjusted:
(1) when deviation is big, in order to accelerate the response speed of system, and when preventing because of beginning the moment of deviation become the differential supersaturation that may cause greatly and make control action exceed tolerance band, should get bigger Kp and less Kd.For preventing that integration is saturated, avoid system responses bigger overshoot to occur in addition, the Ki value is little, gets Ki=0 usually.
(2) when deviation and rate of change are median size, for the overshoot that makes system responses reduces and guarantees certain response speed, Kp should get smaller.The value of Kd is very big to systematic influence in this case, should get smallerly, and the value of Ki is wanted suitably.
(3) when deviation hour, have steady-state behaviour preferably in order to make system, should increase Kp, Ki value, vibrate for avoiding output to respond near setting value simultaneously, and the antijamming capability of taking into account system, Kd should suitably be chosen, its principle is: when deviation variation rate hour, Kd gets bigger; When deviation variation rate was big, Kd got less value, and Kd is a median size usually.
By the membership function that last joint is determined, use Fuzzy Set Theory and sum up a tackling fuzzy model of adjusting of Kp, Ki and Kd targetedly according to above principle.
(4) fuzzy reasoning and fuzzy operation
Referring to Fig. 4, at first obtain certain temperature deviation e (k) value constantly, thereby calculate the value of temperature deviation rate of change ec (k), carry out obtaining behind the fuzzy quantization fuzzy quantity E and the EC of temperature deviation and deviation variation rate according to principle nearby, obtain degree of membership on E and EC quantized interval according to triangle membership function figure, carry out corresponding reasoning and calculation according to last joint fuzzy control rule table again, obtain Kp, the degree of membership of each language value correspondence of Ki and Kd, for leg-of-mutton membership function figure (referring to Fig. 3), have only two kinds of situations, one is exactly a maximum of having only the degree of membership of an element, adopt the maximum membership degree method to carry out ambiguity solution this moment, its two be exactly the degree of membership of a plurality of elements be maximum, adopting this moment gravity model appoach to carry out ambiguity solution judges, change back to domain scope separately, just can draw Δ Kp, Δ Ki, the accurate adjusted value of Δ Kd.
Realize the constantly online adjustment of pid parameter according to adjusting formula.
The adjustment formula of pid parameter is:
Kp＝KpO+ΔKp，Ki＝KiO+ΔKi，Kd＝KdO+ΔKd
KpO, KiO, KdO are the initial values of Kp, Ki, Kd in the formula.They obtain by the method for routine.
The fuzzy control flow chart as shown in Figure 5, fuzzy controller is to realize by PLC, and system draws one group of Kp, Ki, Kd parameter by detected temperatures deviation and deviation variation rate by the mode of tabling look-up, change corresponding pid parameter in the PLC program, the subprogram of tabling look-up block diagram as shown in Figure 6.
Parameter self-tuning PID control system is applied in the high accuracy air-conditioning system project implementation of laboratory, and, obtain the initial value table of relevant pid parameter by continuous correction according to above design of Fuzzy Controller principle and field adjustable experience.According to the PID that gets laboratory high accuracy air-conditioning is controlled.
The effect of relatively more conventional for convenience control and fuzzy control has been extracted two days temperature log from historical data base, contrasted, conventional PID control as shown in table 1 and fuzzy control operation result contrast table.
Table 1
The temperature controlling range of the conventional as can be seen control of one day service data is at 21.6 ℃-24.4 ℃ from table, is to satisfy to the requirement of 22 ℃-24 ℃ of breadboard room temperature designs.And the temperature controlling range after the fuzzy control adheres to specification fully at 22.3 ℃-23.6 ℃.
More than show and described basic principle of the present invention and principal character and advantage of the present invention.The technical staff of the industry should understand; the present invention is not restricted to the described embodiments; that describes in the foregoing description and the specification just illustrates principle of the present invention; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements all fall in the claimed scope of the invention.The claimed scope of the present invention is defined by appending claims and equivalent thereof.
Claims (5)
1. the fuzzy PID control method of industrial environment high accuracy air-conditioning, its method is: the input quantity of selecting fuzzy controller is desired value and actual deviation e and the deviation variation rate ec that exports, set up parameter K p, Ki, Kd with the relation of the binary continuous function between absolute value of the bias and deviation change absolute value, output quantity is correction amount Kp, Δ Ki, the Δ Kd of pid parameter; Determine the fuzzy relation between three parameters of PID and deviation e and the deviation variation rate ec then, be in operation by continuous detection e and ec, according to fuzzy control principle three parameters are carried out online adjustment again and obtain adjusted Kp, Ki, Kd, then Kp, Ki, Kd are inputed to the PID controller.
2. the fuzzy control method of industrial environment high accuracy air-conditioning according to claim 1, it is characterized in that pid parameter is to obtain Δ Kp by fuzzy reasoning and Fuzzy Calculation, Δ Ki, the accurate adjusted value of Δ Kd, and according to adjusting the constantly online adjustment of formula realization.
The adjustment formula of described pid parameter is:
Kp＝KpO+ΔKp，Ki＝KiO+ΔKi，Kd＝KdO+ΔKd
KpO, KiO, KdO are the initial values of Kp, Ki, Kd in the formula.
3. the fuzzy control method of industrial environment high accuracy air-conditioning according to claim 1, it is characterized in that, described method is obtained degree of membership on E and EC quantized interval by triangle membership function figure, carry out corresponding reasoning and calculation according to fuzzy control rule table again, obtain the degree of membership of each language value correspondence of Kp, Ki and Kd.
4. the fuzzy control device of industrial environment high accuracy air-conditioning comprises the fuzzy control circuit on the wiring board, it is characterized in that, also be provided with on the described fuzzy control circuit parameter on-line tuning from the setting mechanism circuit.
5. the fuzzy control device of industrial environment high accuracy air-conditioning according to claim 1, it is characterized in that, describedly comprise obfuscation, inference machine, ambiguity solution and parameter correction operating process in operation successively from the setting mechanism circuit, described inference machine comparable data storehouse and rule base are judged.
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