CN1393746A - Self-adaptive fuzzy controller for PID parameters - Google Patents
Self-adaptive fuzzy controller for PID parameters Download PDFInfo
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Abstract
A self-adaptive PID fuzzy controller is composed of a PID self-setting unit and a PID fuzzy self-regulating unit. The PID self-setting unit consists of improved PID controller, critical parameter detecting module and PID parameter calculating module. The fuzzy self-regulating unit comprises fuzzy self-regulation module and self-adaptive module to fuzzy PID parameters.
Description
The present invention relates to a kind of pid parameter fuzzy adaptive controller and belong to field of industrial automatic control.
The PID controller is owing to have advantages such as simple in structure, cheap, still widespread use on industrial various opertaing devices now.Can the control system that be made of it drop into automatically smoothly, and can the system that drop into operation automatically guarantee to move under the Optimal Control state, is to be engaged in industrial process automatic control technology personnel and managerial personnel's stubborn problem always.Key on the PID controller is used is exactly parameter tuning and online adjustment thereof.Its parameter tuning of past is default by the experience value, does manual adjustment according to the response wave shape of trial run again, this way often experience more than science, both time-consuming, be difficult to the setting valve that reaches best again.Especially for the control system of complexity, adjusting of P, I, D controlled variable is more difficult.Though people have summed up some systems open loops debugging rule, as the Ziegle-Nichol rule etc., owing to be difficult to accurately obtain the dynamic characteristic parameter of object in advance, thereby the application of these rules is still very difficult.Various closed loop setting methods has been proposed again thus.Present various effective setting methods comprise the method or the like of adjusting of adjusting the Ziegler-Nichols that improves algorithm method, Cohen-Coon adjusting method, Astrom, bring into play great function aspect the automatic control system improving.But because the PID controller of preset parameter adopts compromise method to solve static and the dynamic contradiction between contradiction, rapidity and the robustness between the contradiction between the controlling performance, tracking setting value and the disturbance suppression etc., this just makes the system of single controlled variable can not obtain best control effect.Work as working conditions change, and controlling object exists characteristics such as time variation, non-linear, large time delay, strong jamming, implement control with one group of pid parameter of adjusting in advance and be difficult to reach excellent control effect, especially when the image parameter variation surpasses certain scope, system performance is variation obviously, even exceeds tolerance band.Along with development of computer, people's adjustment experience that operating personnel are long-term is made rule with the method for artificial intelligence, deposits in people's computing machine, makes the calculating function adjust pid parameter automatically, intelligent PID controller so just occurred.Sort controller combines classic PID control with advanced person's expert system, the appearance of intelligent PID controller is a a progressive step the PID control technology.But owing to operator's experience is difficult for accurately describing, various semaphores and evaluation index are difficult for quantificational expression in the control procedure, and this quasi-controller also fails well the knowledge and the adjustment experience formation control corresponding of useful control to be restrained.
Purpose of the present invention: a kind of pid parameter fuzzy adaptive controller is provided.It can not need set up the controlled system mathematical model, just can be automatically in closed-loop control by desired stability margin adjust out P, I, D parameter; And according to the variation of surveying operating condition signal and deviation signal, automatically, infer best P, I, D parameter in real time, shorten the transit time of control system to greatest extent, reduce its dynamic deviation and static deviation, and make system have robustness (Robust) preferably.
Purpose of the present invention is realized by following manner: the pid parameter fuzzy adaptive controller that the present invention adopts comprises improved PID controller (1), critical parameters detection module (2), pid parameter computing module (3), fuzzy self-adjusting module (4), fuzzy parameter adaptive module (5).It is characterized in that former PID controller is improved, make it increase ring relay type switch control (i.e. two controls) mode that stagnates, use so that control system produces threshold oscillation by a small margin; Detection module (2) is used for being under two state of a controls in system, obtains critical parameters; Pid parameter computing module (3) utilization calculates the proportional band (P), integration (I), the differential controlled variable such as (D) that are suitable for the stability margin requirement from the critical parameters that module (2) obtains; Fuzzy self-adjusting module (4) matches with fuzzy parameter adaptive module (5), finish jointly according to the variation of deviation signal and operating mode and adjust P automatically, I, the task of D parameter, fuzzy self-adjusting module (4) is by the deviation signal of being sent here by module (1) and the variation of deviation variation rate thereof, extrapolate the adjustment coefficient of controlled variable by means of fuzzy regulation rule, be transferred to parameter adaptive module (5) by data telecommunication line, the parameter adaptive module is by the minimum stability margin of input, moderate stability margin, the P of maximum stable nargin, I, D parameter and actual measurement operating condition signal, the parameter adjustment coefficient, adjust P, I, the D parameter, via controller (1) control controlled system is so that system obtains desirable sound attitude controlling performance.Improved PID controller (1) is on former PID controller (23), adding adjustable two-position controller (24) of the ring that stagnates and control model change-over switch (25) constitutes, the A end of change-over switch (25) is received in the output of controller (24), and the B end of change-over switch (25) is received in the output of controller (23).Detection module (2) is connected on the PID controller (1) after the improvement by data telecommunication line, obtains the switch state of a control (open or close) of controller and the measured value of control system under detecting pattern.Detection module uses these parameter detecting to go out the last half-wave time T of control system threshold oscillation
MAXReach half-wave time T down
MIN, threshold oscillation peak value V
MAXAnd valley V
MIN, and calculate the period T of threshold oscillation and the amplitude V of threshold oscillation.Pid parameter computing module (3) input is by detection module (2) detected threshold oscillation cycle (T) and amplitude (V), and the stagnant ring amplitude (H) and the hysteresis band two-position controller controlled variable such as (e) of switch control reach desired phase angle stabilization, nargin Q
MWith amplitude stability nargin A
M, calculate P, I, D parameter under this stability margin.The fuzzy self-adjusting module (4) of appeal comprises deviation variation rate processing unit (6), deviation Fuzzy processing unit (7), deviation variation rate Fuzzy processing unit (8), fuzzy regulation rule inference net (9), de-fuzzy processing unit (10).After handling, the deviation variation rate processing unit (6) that the control deviation of being sent here by module (1) is delivered to module (4) delivers to deviation variation rate Fuzzy processing unit (8) again; The control deviation of being sent here by module (1) is also delivered to the deviation Fuzzy processing processing unit (7) of module (4); Deviation Fuzzy processing processing unit (7) and deviation variation rate Fuzzy processing processing unit (8) are delivered to fuzzy regulation rule inference net (9) with output separately respectively; De-fuzzy processing unit (10) is delivered in the output of inference net (9), and the fuzzy adjustment coefficient of its output is delivered to fuzzy parameter adaptive module (5).Described fuzzy parameter adaptive module (5) comprising: the fuzzy coefficient unit (11) that adds up of adjusting; Multimode maximum stable nargin proportional band parameter calculation unit (12), the moderate stability margin proportional band of multimode parameter calculation unit (15), the minimum stability margin proportional band parameter calculation unit (18) of multimode; Multimode maximum stable nargin integral parameter computing unit (13), the moderate stability margin integral parameter of multimode computing unit (16), the minimum stability margin integral parameter computing unit (19) of multimode; Multimode maximum stable nargin differential parameter computing unit (14), the moderate stability margin differential parameter of multimode computing unit (17), the minimum stability margin differential parameter computing unit (20) of multimode; Proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23).Calculate minimum, moderate, proportional band P, the integration I of maximum stable nargin, maximum, moderate, the minimum stability margin parameter calculation unit (12,15,18) that differential D parameter is delivered to module (5) respectively by module (3), (13,16,19), (14,17,20), the operating condition signal that will detect controlled system with data telecommunication line is also delivered to each parameter calculation unit (12)～(20) respectively; Deliver to proportional band parametric synthesis computing unit (21) respectively by the proportional band parameter that proportional band parameter calculation unit (12,15,18) is calculated; The integral parameter that integral parameter computing unit (13,16,19) is calculated is delivered to integral parameter COMPREHENSIVE CALCULATING unit (22) respectively; The differential parameter that differential parameter computing unit (14,17,20) is calculated is delivered to differential parameter COMPREHENSIVE CALCULATING unit (23) respectively; Extrapolate proportional band P, the integration I of corresponding stability margin, the outer given side of controlled variable that differential D parameter is delivered to controller (1) by proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23).
Advantage of the present invention:
1. the process of adjusting certainly among the present invention is under closed loop, adds that by a small margin relay-type control realizes, the assurance system overshoot, unstability can not occur in the process of adjusting, and can carry out again at any time from adjusting according to the requirement of operation.
2. no matter control system is subjected to disturbing in disturbing still outward, utilizes fuzzy parameter adaptive module of the present invention, all can obtain best controlled variable this moment, makes system obtain satisfied control effect.
3. the present invention's optimization that can solve P, I, D (ratio, integration, differential) parameter in the various PID control system (comprising single loop control, tandem control, multiloop control) is preferably adjusted and the online self-adjusting problem of parameter.
4. adopt the present invention to improve original control system, only need former pid control algorithm module is added two control function, in former control system, embed critical parameters detection module of the present invention (2), pid parameter computing module (3), fuzzy self-adjusting module (4), fuzzy parameter adaptive (5) module, and connect with data communication line and former pid control algorithm module, just can make system that deviation and working conditions change are had adaptive ability.Both save the time of system transplantation, programming, debugging etc., reduced the expense of transform soft, hardware again.
5. use the system of the present invention's transformation, its dynamic sensitivity, rapidity, the stability of stable state and robustness all are better than the control effect of existing process controller, and be especially more obvious for the system effect of time variation, non-linear, large time delay, strong jamming, variable parameter operation.
By accompanying drawing know-why of the present invention and implementation step are described below.
Fig. 1 is that control system of the present invention constitutes sketch;
Fig. 2 is that improved PID controller constitutes block diagram;
Fig. 3 is the typical curve of process of adjusting certainly;
Fig. 4 constitutes block diagram for fuzzy self-adjusting module;
Fig. 5 is that fuzzy parameter adaptive module constitutes block diagram;
Fig. 6 for the steam temperature cascade control system adopt respectively general Ziegler-Nichole adjust method (Z-N),
Among the present invention based on the pid parameter of given stability margin in tuning device (SPGM), the present invention
Add that at pid parameter pid parameter blurs self-adjusting mechanism on the tuning device basis
(SPGM+FST) step response and disturbance response conditional curve.
Fig. 1 is that control system of the present invention constitutes sketch.PID controller after improving in Fig. 1 has increased stagnant ring relay type switch control (i.e. two controls) function, can make control system to produce threshold oscillation by a small margin; Detection module (2) is connected on the PID controller after the improvement by data telecommunication line, obtains the measured value of switch state of a control (opening or closing) and control system, calculates critical parameters; The critical parameters that pid parameter computing module (3) utilization is obtained calculate the proportional band (P), integration (I), the differential controlled variable such as (D) that are fit to the stability margin requirement; Fuzzy self-adjusting module (4) matches with fuzzy parameter adaptive module (5), finishes the task of adjusting P, I, D parameter according to the variation of deviation signal and actual measurement working condition signal automatically jointly; Fuzzy self-adjusting module (4) receives deviation signal on the PID controller (1) by data telecommunication line, it is by deviation signal and deviation variation rate thereof, by means of bluring the fuzzy adjustment coefficient that self-adjusting inference rule calculates controlled variable, be transferred to fuzzy parameter adaptive module by data telecommunication line; The parameter adaptive module is by P, I, D parameter and next actual measurement operating condition signal, the parameter adjustment coefficient of transmission of the minimum stability margin of input, moderate stability margin, maximum stable nargin, calculate P, I, D parameter, in transfer back to PID controller (23) by data telecommunication line, adjust P, I, D parameter in real time, the control controlled system is so that system obtains desirable sound attitude controlling performance.
Fig. 2 is that improved PID controller constitutes block diagram.As improved PID controller (1) among Fig. 2 is on former PID controller (23), adds adjustable two-position controller (24) of the ring that stagnates and control model change-over switch (25) and constitutes.The control output of PID controller is transferred on the A end of mode selector switch by data telecommunication line, the control output of two-position controller also is transferred on the B end of change-over switch by data line, by mode switch end input boolean (bool) number in change-over switch, the PID controller after control improves carries out the normal control of PID or carries out the test control of two excitations.Before test pattern,, estimate the control amplitude of two-position controller, and the dead band and the amplitude of its control are imported two-position controller in advance earlier according to the required amplitude of system's threshold oscillation.When mode selector switch is got to test lead (B), when the two-position controller that presets can exceed the hysteresis band of the ring relay type switch control that stagnates in the deviation of measured value and setting value, export positive and negative step signal, change the control outbound course (by open → close or close → open), thereby cause that system produces the vibration of may command amplitude near current setting value.Constantly grope the dynamic perfromance of process by this control, measure the threshold oscillation cycle and the amplitude of system.
Fig. 3 is the typical curve of process of adjusting certainly.Detection module (2) is connected on the PID controller after the improvement by data telecommunication line, obtain the measured value of change-over switch state of a control (opening or closing) and control system, detection module uses these parameters to measure, preserve the also last half-wave time T of display control program threshold oscillation
MAXReach half-wave time T down
MIN, threshold oscillation peak value V
MAXAnd valley V
MIN, so just can calculate T (T=T cycle length of control system threshold oscillation
MAX+ T
MIN) and the amplitude V (V=V of threshold oscillation
MAX-V
MIN).With threshold oscillation period T and the amplitude V that records, the stagnant ring width of cloth (H) and hysteresis band two controlled variable such as (e) of corresponding stagnant ring relay-type switch control with it, and desired phase angle stabilization, nargin (Q
m) and amplitude stability nargin (A
m) be input in the pid parameter computing module (3), proportional band (P), integration (I), the differential (D) that is suitable for the stability margin that requires just can be calculated, preserves and be shown to parameter calculating module.On certain typical conditions, just can calculate P, I, D parameter under the different stability margins at this moment by changing phase angle stabilization, nargin and amplitude stability margin value.When adopting the present invention to carry out the control of fuzzy parameter adaptive, need on typical condition, calculate and satisfy minimum stability margin, moderate stability margin, three groups of P, I of maximum stable nargin, D parameter respectively.Need carry out variable parameter operation control on a large scale and work as controlled system, also wanting segmentation to carry out controlled variable when being necessary under each typical condition adjusts, calculate minimum, moderate under the different operating modes, P, the I of maximum stable nargin, D controlled variable, be input to the corresponding computing unit of adaptation module (5) respectively, realize the fuzzy multimode pid parameter adaptive control of variable working condition.
Fig. 4 constitutes block diagram for fuzzy self-adjusting module.Fuzzy self-adjusting module (4) comprising: deviation variation rate processing unit (6), deviation Fuzzy processing unit (7), deviation variation rate Fuzzy processing unit (8), fuzzy regulation rule inference net (9), de-fuzzy processing unit (10).The control deviation that module (1) is sent here is delivered to deviation variation rate processing unit (6) and deviation Fuzzy processing unit (7) respectively through data telecommunication line; Deliver to deviation variation rate Fuzzy processing unit (8) by the deviation variation rate that the deviation variation rate processing unit calculates by data telecommunication line; The relevant subordinate function that calculate separately deviation Fuzzy processing unit (7) and deviation variation rate Fuzzy processing unit (8) is delivered to fuzzy regulation rule inference net (9) by data telecommunication line; The fuzzy reasoning net constitutes according to fuzzy regulation rule with corresponding fuzzy operation piece, deviation of calculating and deviation variation rate subordinate function are through the computing of inference net, reason out the fuzzy number of corresponding deviation and deviation variation rate, each fuzzy number is delivered to de-fuzzy processing unit (10) by data telecommunication line; The de-fuzzy unit carries out the de-fuzzy computing according to gravity model appoach and draws the fuzzy coefficient of adjusting.
Fig. 5 is that fuzzy parameter adaptive module constitutes block diagram.Fuzzy parameter adaptive module (5) comprising: the fuzzy coefficient unit (11) that adds up of adjusting; Multimode maximum stable nargin proportional band parameter calculation unit (12), the moderate stability margin proportional band of multimode parameter calculation unit (15), the minimum stability margin proportional band parameter calculation unit (18) of multimode; Multimode maximum stable nargin integral parameter computing unit (13), the moderate stability margin integral parameter of multimode computing unit (16), the minimum stability margin integral parameter computing unit (19) of multimode; Multimode maximum stable nargin differential parameter computing unit (14), the moderate stability margin differential parameter of multimode computing unit (17), the minimum differential parameter computing unit (20) of multimode stability margin; Proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23).Fuzzy parameter adaptive module (5) is obtained the fuzzy coefficient of adjusting by the data telecommunication line that is connected to self-adjusting module (4); Fuzzy adjustment coefficient in parameter adaptive module (5) is delivered to the fuzzy coefficient unit (11) that adds up of adjusting through data telecommunication line; Deliver to proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23) by the adjustment coefficient that adds up that the unit that adds up calculates respectively through data telecommunication line; P, the I that is calculated by module (3), D parameter minimum, moderate, P, the I of maximum stable nargin, D parameter are delivered to each multimode controlled variable computing unit (12,15,18) respectively, (13,16,19), (14,17,20), with data telecommunication line detected operating condition signal is also delivered to each controlled variable computing unit (12)～(20) respectively, each multimode parameter calculation unit is extrapolated P, I, the D controlled variable of different relatively stability margins by the operating mode of current operation; By proportional band parameter calculation unit (12,15,18) the proportional band parameter of calculating is delivered to proportional band parametric synthesis computing unit (21) respectively, integral parameter computing unit (1 3,16, the integral parameter of 19) calculating is delivered to integral parameter COMPREHENSIVE CALCULATING unit (22) respectively, differential parameter computing unit (14,17, the differential parameter of 20) calculating is delivered to differential parameter COMPREHENSIVE CALCULATING unit (23) respectively, adjust the proportional band P that coefficient is extrapolated corresponding stability margin in each controlled variable COMPREHENSIVE CALCULATING unit according to fuzzy adding up, integration I, differential D parameter is as the output of fuzzy parameter adaptive module, be transferred to the P of controller (1) by data telecommunication line, I, the outer given side of D controlled variable, the variation of finishing by deviation signal and operating mode adjusts best P automatically, I, the task of D controlled variable, the control controlled system.
Fig. 6 adds the step response and the disturbance response conditional curve of the fuzzy self-adjusting mechanism (SPGM+FST) of pid parameter among method (Z-N), the present invention for adopt general Ziegler-Nichole to adjust respectively in the steam temperature cascade control system on the tuning device basis at pid parameter in tuning device (SPGM), the present invention based on the pid parameter of given stability margin.
From simulation result we as can be seen, adopt that of the present invention to come Tuning PID Controller device parameter from tuning device (SPGM) be effective.From closed loop response as can be seen: no matter be step response or disturbance rejection response, P, the I that given stability margin rule is adjusted, D parameter control effect all are better than usefulness Z-N rule, and on the tuning device basis, increasing fuzzy self-adjusting mechanism (SPGM+FST), then make the controlling performance of system obtain bigger improvement, its transit time the shortest (the adjusting time that reaches stationary value is 12 minutes and 27 seconds), dynamic deviation and static deviation are all minimum.Clearly adopt the SPGM+FST method for designing to improve conventional PID control for big inertia, non-linear, large time delay, strong jamming system, control system can be got extraordinary control effect; And the parameter that in the past adopted the Z-N method to adjust PID, the response of control system then than it slowly many (the adjusting time that reaches stationary value is 21 minutes and 45 seconds).
Pid parameter fuzzy adaptive controller of the present invention is significantly improved the antijamming capability of system after being used for certain 670T/H dum boiler master Stream Temperature Control System.Under load frequent fluctuation, the violent situation of burning disturbance, the main steam temperature of being controlled is reached ± is reduced in ± 5 ℃ more than 20 ℃ by original maximum fluctuation scope.
Pid parameter fuzzy adaptive controller of the present invention also is successfully used to the relevant control loop of coal-burning power plant's the ball type pulverizer system.The control of pulverized coal preparation system is one and relates to three and go into the three multivariable Control problems that go out.Traditional control method adopts three independently conventional pid control circuits, controls import and export differential pressure, entrance negative pressure, the outlet temperature of bowl mill respectively.Can't solve three Coupling Control problems that parameter is mutual like this.Up to now, this type systematic remains manual operation, to such an extent as to each parameter control is unstable; Following coal is extremely inhomogeneous; Material level often is lower than rational material level; Cause the bowl mill milling efficiency low.Behind utilization the present invention, system can control the variation that each operational factor adapts to various interference and regulation and control instruction automatically, finishes the control task of decoupling zero, guarantees that bowl mill stably operates on the given working point.Can not cause the fluctuation of differential pressure, material level; The regulation and control of temperature, negative pressure also can be kept the stable of parameter well.Having broken through for a long time can not the automatic situation of pitching grinding machine, has reduced the power consumption of bowl mill, remarkable in economical benefits.
Claims (6)
1. a pid parameter fuzzy adaptive controller that is applied in the Industry Control comprises improved PID controller (1), critical parameters detection module (2), pid parameter computing module (3), fuzzy self-adjusting module (4), fuzzy parameter adaptive module (5).It is characterized in that: former PID controller is improved, make it increase ring relay type switch control (i.e. two controls) mode that stagnates, use so that control system produces threshold oscillation by a small margin; Detection module (2) is used for being under two state of a controls in system, obtains system's critical parameters; Pid parameter computing module (3) utilization calculates the proportional band (P), integration (I), the differential controlled variable such as (D) that are suitable for the stability margin requirement from the critical parameters that module (2) obtains; Fuzzy self-adjusting module (4) matches with fuzzy parameter adaptive module (5), finish the task of adjusting P, I, D parameter according to the variation of deviation signal and operating mode automatically jointly, fuzzy self-adjusting module (4) is by the deviation signal of being sent here by module (1) and the variation of deviation variation rate thereof, extrapolate the adjustment coefficient of controlled variable by means of bluring regulation rule, be transferred to parameter adaptive module (5) by data telecommunication line; The parameter adaptive module is by P, I, D parameter and actual measurement operating condition signal, the parameter adjustment coefficient of the minimum stability margin of input, moderate stability margin, maximum stable nargin, adjust P, I, D parameter, via controller (1) control controlled system is so that system obtains desirable sound attitude controlling performance.
2. controller according to claim 1, it is characterized in that: improved PID controller (1) is on former PID controller (23), adding adjustable two-position controller (24) of the ring that stagnates and control model change-over switch (25) constitutes, the A end of change-over switch (25) is received in the output of controller (24), and the B end of change-over switch (25) is received in the output of controller (23).
3. controller according to claim 1, it is characterized in that: detection module (2) is connected on the PID controller (1) after the improvement by data telecommunication line, obtains the switch state of a control (open or close) of controller and the measured value of control system under detecting pattern.Detection module uses these parameter detecting to go out the last half-wave time T of control system threshold oscillation
MAXReach half-wave time T down
MIN, threshold oscillation peak value V
MAXAnd valley V
MIN, and calculate the period T of threshold oscillation and the amplitude V of threshold oscillation.
4. controller according to claim 1, it is characterized in that: pid parameter computing module (3) is imported by detection module (2) detected threshold oscillation cycle (T) and amplitude (V), the stagnant ring amplitude (H) and the hysteresis band two-position controller controlled variable such as (e) of switch control, and desired phase angle stabilization, nargin Q
MWith amplitude stability nargin A
M, calculate proportional band P, integration I, differential D parameter under this stability margin.
5. controller according to claim 1 is characterized in that: fuzzy self-adjusting module (4) comprises deviation variation rate processing unit (6), deviation Fuzzy processing unit (7), deviation variation rate Fuzzy processing unit (8), fuzzy regulation rule inference net (9), de-fuzzy processing unit (10).The control deviation of being sent here by module (1) is delivered to the deviation variation rate processing unit (6) of module (4) and is delivered to deviation variation rate Fuzzy processing unit (8) again; The control deviation of being sent here by module (1) is also delivered to the deviation Fuzzy processing processing unit (7) of module (4); Deviation Fuzzy processing processing unit (7) and deviation variation rate Fuzzy processing processing unit (8) output to fuzzy regulation rule inference net (9) respectively; De-fuzzy processing unit (10) is delivered in the output of inference net (9), and the fuzzy adjustment coefficient of its output is delivered to fuzzy parameter adaptive module (5).
6. controller according to claim 1 is characterized in that: fuzzy parameter adaptive module (5) comprises the fuzzy coefficient unit (11) that adds up of adjusting; Multimode maximum stable nargin proportional band parameter calculation unit (12), the moderate stability margin proportional band of multimode parameter calculation unit (15), the minimum stability margin proportional band parameter calculation unit (18) of multimode; Multimode maximum stable nargin integral parameter computing unit (13), the moderate stability margin integral parameter of multimode computing unit (16), the minimum stability margin integral parameter computing unit (19) of multimode; Multimode maximum stable nargin differential parameter computing unit (14), the moderate stability margin differential parameter of multimode computing unit (17), the minimum stability margin differential parameter computing unit (20) of multimode; Proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23).The fuzzy adjustment coefficient of being sent here by module (4) is delivered to fuzzy adjustment coefficient in the module (5) unit (11) that adds up, and adding up after the unit that adds up calculates adjusted coefficient and delivered to proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23) again; Calculate minimum, moderate, proportional band P, the integration I of maximum stable nargin, maximum, moderate, minimum each parameter calculation unit of stability margin (12,15,18) that differential D parameter is delivered to module (5) respectively by module (3), (13,16,19), (14,17,20), the operating condition signal that will detect controlled system with data telecommunication line is also delivered to each parameter calculation unit (12)～(20) respectively, and each parameter calculation unit is extrapolated P, I, the D controlled variable of different relatively stability margins by the operating mode of current operation; Deliver to proportional band parametric synthesis computing unit (21) respectively by the proportional band parameter that proportional band parameter calculation unit (12,15,18) is calculated; The integral parameter that integral parameter computing unit (13,16,19) is calculated is delivered to integral parameter COMPREHENSIVE CALCULATING unit (22) respectively; The differential parameter that differential parameter computing unit (14,17,20) is calculated is delivered to differential parameter COMPREHENSIVE CALCULATING unit (23) respectively; Extrapolate proportional band P, the integration I of corresponding stability margin, the outer given side of controlled variable that differential D parameter is delivered to controller (1) by proportional band parametric synthesis computing unit (21), integral parameter COMPREHENSIVE CALCULATING unit (22), differential parameter COMPREHENSIVE CALCULATING unit (23).
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2001
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