CN106773685A - A kind of angle PI controller tuning methods for wind power yawing system - Google Patents
A kind of angle PI controller tuning methods for wind power yawing system Download PDFInfo
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- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
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Abstract
A kind of angle PI controller tuning methods for wind power yawing system, the present invention relates to wind power yawing system PI controller tuning methods.The present invention obtains system transter according to rotary speed instruction and feedback rotating speed, ONLINE RECOGNITION yaw system rotational speed regulation model.According to the model, analogue system is built, using the least square majorized function setting method of control error, with reference to trusted zones iterative algorithm, search makes the minimum PI parameters of control error, so as to complete adjusting for yaw control system PI controller parameters.The method feature is that the method requires no knowledge about the accurate model of yaw system, is particularly well-suited to time-variable parameter system；Algorithm is obtained by iteration recursion, can canbe used on line controller parameter is adjusted.The method is applied to polytype Wind turbines, and the result of adjusting for obtaining is controlled for systems such as PLC to the yaw system of Wind turbines, practical.The present invention is applied to the yaw system control field of Wind turbines.
Description
Technical field
Angle PI controller tuning methods the present invention relates to be used for wind power yawing system.
Background technology
In Wind turbines, yaw system is its important component.Impeller needs to meet the direction for aweather blowing to obtain most
Good wind energy, and change impeller and boat storehouse direction, it is exactly based on yaw system realization.
The quality of yaw system control, will affect the reliability of wind energy utilization efficiency and yaw maneuver.Driftage control system
The performance of system, is mainly reflected in static and two aspects of dynamic.In static state, it is desirable to improve to wind precision, in dynamic, it is desirable to can
The change of tracking wind direction in time.The former problem is how to overcome anemoscope to examine indeterminable influence, and this is also that driftage at present is
The part of concentration is compared in system research, and precision is improved often through the method for search.It is fast-changing that the latter is mainly reflected in wind direction
Occasion, it is desirable to improve dynamic performance, but dynamic performance is improved merely, often influence the stability of system so that
System oscillation, causes load change, support vibration.In order that obtaining system working stability, the adjustment process of controller is slower, and
The setting of various control parameters is often carried out according to field test.This mode low cost, technical difficulty is small, have been obtained for compared with
Many practical applications, but in wind vector, frequently occasion is less efficient, and yaw device is adjusted not in time, will waste wind-force, is increased
Plus loss.
In Practical Project, yaw control system adjustment process mainly carries out simple PI control realizations by PLC, including outer
Ring angle PI is controlled and inner ring rotating speed PI controls, and wherein outer shroud angle PI controllers influence larger to system perspective tracking performance,
Therefore the present invention only studies outer shroud angle PI attitude conirol methods.Often by field adjustable during PI attitude conirols
Personnel are configured according to the experience of live practical operation situation and commissioning staff.In order to improve stability, often parameter is chosen
More guard, the dynamic property of yaw system is poor, is unfavorable for that wind direction quickly changes occasion.Additionally, Wind turbines are for a long time
Work, its power transmission shaft parameter has time variation, and after work a period of time, control parameter originally may be improper, it is necessary to carry out
Constantly safeguard, increased later stage expense.
The content of the invention
The technical problem to be solved in the present invention is to realize the on-line tuning of yaw system angle PI controllers, by distinguishing online
The method of knowledge, obtains the autoregression model of driftage revolution speed control system, using the model, studies under different control parameters, driftage
Angle and the difference of desired value, with the minimum optimal conditions of the quadratic sum of difference, search for optimal PI controller parameters.Institute of the present invention
Parameter is needed to be Wind turbines routine monitoring parameter, without installing new sensor, it is only necessary to increase corresponding software.
The principle of the invention is divided into two parts：Driftage revolution speed control system linear regression model (LRM) on-line identification, it is flat based on minimum
Side and the PI controller tuning methods of majorized function.
(1) on-line identification of driftage revolution speed control system linear regression model (LRM)
The structure chart of yaw control system is as shown in Figure 1.Wherein θ * are cabin angle command, are typically detected by anemoscope
Be given plus some backoff algorithms.θ is the actually detected angle of cabin.The difference of instruction angle and actual angle is controlled by angle PI
Device, obtains the rotary speed instruction ω * of yaw system.ω * subtract Yawing mechanism actual feedback rotational speed omega, the difference between the two feeding rotating speed
PIS controllers, obtain torque instruction T*, and torque instruction is applied to transmission mechanism by drive mechanism.Because drive mechanism is produced
The response speed of torque quickly, realize, i.e. K by the approximate low pass filter of this process3/(1+T0s).The torque T for finally giving makees
For load transmission system, JmIt is its rotary inertia, D is its frictional damping.
In actual wind power yawing control system, angle controller PI and rotational speed governor PIS is by wind power equipment integrator
Exploitation, and produce the device of torque, such as servo-driver is then generally provided by third party, and its equivalent model typically cannot be straight
Connect and obtain.Meanwhile, general JmIt is also unknown with D, and with time-varying characteristics, parameter may occur partially after operation a period of time
Move.Therefore, part B structure is unknown in block diagram, and the design to PI controllers brings difficulty, if it is possible to recognize the model,
Design can be then optimized to PI controllers.
In order to not increase sensor, yaw system moment information is not selected here as observed quantity, and use driftage rotating speed,
I.e. with ω * as input quantity, ω is output quantity, and the model F comprising revolution speed control system is recognized.After F is picked out, can be right
Yaw angle controller PI is adjusted.Because the control of yaw angle θ is outer shroud, it determines the main of whole yaw system
Performance, therefore it is feasible that only it is adjusted.
F department patterns discrimination method is in yaw system：
1) linear regression model (LRM) with controlled quentity controlled variable is set up.
For single-input single-output system (SISO), the relation useable linear regression model statement between output y and input u
For
Y (k)=a1y(k-1)+a2y(k-2)+…+anay(k-na)+b1u(k-1)+b2u(k-2)+…+bnby(k-nb)
(1)
For yaw system, output quantity y is ω, and input quantity u is ω *.K, k-1, k-2 ..., when representing each sampling
Carve.If a=(a can be recognized1, a2..., ana), b=(b1, b2..., bnb) parameter, you can identification model F.
2) parameter identification
The discrimination method of linear regression model (LRM) is more, is distinguished using the Least Square Recurrence beneficial to computer canbe used on line here
Know algorithm.For formula (1), being write as matrix form is
Wherein,It is data vector, λ is model parameter vector, i.e.,
λ=[a1,...,ana,b1,...,bnb]T
Then least square method of recursion iterative step is：
Can finally obtain being model parameter vector λ, i.e. a in formula (1), the value of each parameters of b, the F department patterns in such Fig. 1
Recognize and obtained.
(2) the PI controller tuning methods based on least square and majorized function
After identification obtains model F, you can the parameter to controller PI is adjusted.Here the setting method for using is error
Least square and majorized function method.Due to having picked out the structure of model F, the actual mould of identification model approximate substitution can be used
Type is optimized to controller.For whole control system, the controller after optimization can cause the angle of yaw system with
Instruction angular error is minimum, i.e.,
F=∫ e2dt (4)
Wherein, e=θ *-θ.Under the excitation of identical input angle, if PI controller parameters are different, the output response for obtaining
Also different, by the method for traversal search, can find satisfaction makes the minimum parameter of formula (4).In order to accelerate search procedure, this
In use trusted zones optimizing algorithm.
Assuming that the controller parameter to be designed is x=[Kp Ki], Search Range is LB≤x≤UB, LB and UB values are according to reality
Border situation is manually set.Parameter x realized by continuous iteration,
xk+1=xk+dk (5)
dkShould be less than current Trust Region Radius.Due to being difficult to directly obtain the relationship of the two from formula (4), it is considered to secondary forced with its
Near-lying mode type q (d) approximately replaces f,
If along dkDirection qkValue reduce, then by (5) undated parameter, at the same retain trusted zones, otherwise, ginseng is not updated
Number, trusted zones reduce.
So, updated by continuous iteration, x can restrain, the value of this up-to-date style (4) has local minimum.Choose multiple first
Initial point, obtains the parameter after correspondence convergence, final to choose the parameter for making (4) minimum.
Invention effect：
Needed in yaw system it is a kind of can automatic on-line adjust the yaw system control method of angle PI controller parameters,
It can automatically obtain the operation characteristic of unit, with this optimal controller parameter, improve diagonal displacement instruction response speed and
Precision.The on-line identification that the present invention passes through the linear regression model (LRM) to yaw drive system, obtains unit operation feature, i.e. its biography
Delivery function, then by optimizing algorithm, obtains the PI controller parameters for controlling error minimum, and real-time update controller parameter,
Improve the intelligent level of Wind turbines.After being adjusted through the inventive method, PI controllers have better Static and dynamic performance.
The technical problem to be solved in the present invention is to realize the on-line tuning of yaw system PI controllers, by on-line identification
Method, obtains the autoregression model of driftage revolution speed control system, with its autoregression model as reference, studies under different inputs, is
System output and the difference of desired value, with the minimum optimal conditions of the quadratic sum of difference, search for optimal PI controller parameters.The present invention
Required parameter is Wind turbines routine monitoring parameter, without installing new sensor, it is only necessary to increase corresponding software.
Brief description of the drawings
Fig. 1 is yaw system control structure figure；
Fig. 2 is that yaw system linear regression model (LRM) of the invention recognizes figure；
Fig. 3 is the PI parameter optimization method figures based on trusted zones of the invention；
Fig. 4 is the comparing figure of linear regression model (LRM) rotating speed analog result and actual speed；
Fig. 5 compares figure for front and rear Angular displacement control effect of adjusting.
Specific embodiment
In conjunction with the accompanying drawings and embodiments, to the inventive method principle, realize and effect is elaborated.It is proposed by the present invention
PI controller tuning methods based on the identification of system linear regression model.
First, by identification, the autoregression model of yaw system is obtained.It should be noted that model order, that is, determine formula
(1) na and nb is worth size in.Consider yaw system as shown in Figure 1, the transmission function of revolution speed control system (F) is,
Therefore model order is 3, that is, take na=nb=3 and system is recognized.During specific implementation, with the interval sampling cycle
Ts, obtains angular displacement closed loop output valve, i.e. reference angular velocities ω *, and the actual corners of yaw system are obtained by speed observer
Speed omega, with ω * as input quantity, ω is output quantity, and operation is iterated by formula (3), finally obtains a in formula (1), b ginsengs
Number, that is, obtain identification model.The process is as shown in Figure 2.
Secondly, according to identification model, the complete yaw system model as shown in structure chart 1 is set up.Simulation angular displacement refers to
Make θ*, the model is sent into, under different angle controller PI parameters, different output θ will be obtained.By trusted zones convergence algorithm,
Current PI parameters xkUnder, change parameter value by formula (5), model is emulated by software programming, and obtain under parameter current
The error described by formula (4).According to error amount, current trusted zones are adjusted, finally obtain current when Trust Region Radius are sufficiently small
Optimum point.The process is as shown in Figure 3.
Finally, according to the optimal PI parameters for searching, it is cured in control device such as PLC, is realized the online of parameter
Automatically update.
Linear regression model (LRM) recognition effect is as shown in figure 4, the angular speed curve and actual corners that are obtained by identification model are fast
Line write music closely.Fig. 5 reflects the difference of PI controller angular displacement tracing controls before and after positive definite, after adjusting, PI controls
Utensil has better Static and dynamic performance.
Claims (4)
1. a kind of angle PI controller tuning methods for wind power yawing system, it is characterised in that the wind power yawing system
PI controller tuning methods are comprised the following steps：
Step one：Set up the linear regression model (LRM) of driftage revolution speed control system；
Step 2：According to the linear regression model (LRM) that step one is set up, by Least Square Recurrence iterative algorithm, linear regression is obtained
Model parameter, identification driftage revolution speed control system；
Step 3：According to the identification model that step 2 is obtained, using least square and majorized function method, yaw angle control is obtained
The minimum angle PI controller parameters of error, complete adjusting for PI controllers.
2. a kind of angle PI controller tuning methods for wind power yawing system according to claim 1, its feature exists
In the detailed process that linear regression model (LRM) of the yaw drive system with controlled quentity controlled variable is set up in the step one is：
Y (k)=a1y(k-1)+a2y(k-2)+…+anay(k-na)+b1u(k-1)+b2u(k-2)+…+bnby(k-nb) (1)
Output quantity y is yaw system actual angular frequency ω, input quantity u and is its reference instruction ω *；K, k-1, k-2 ..., point
The sampling of current and past time, a=(a are not represented1, a2..., ana), b=(b1, b2..., bnb) it is linear regression model (LRM) ginseng
Number.
3. a kind of angle PI controller tuning methods for wind power yawing system according to claim 1 and 2, its feature
It is that, by Least Square Recurrence iterative algorithm in the step 2, the detailed process for recognizing Linear Regression Model Parameters is：
Using the Least Square Recurrence identification algorithm beneficial to computer canbe used on line, being write formula (1) as matrix form is：
WhereinIt is data vector, λ is model parameter vector；
λ=[a1,...,ana,b1,...,bnb]T
Then least square method of recursion iterative step is：
Wherein K, P are the intermediate variable in iterative process, and operation is iterated by formula (3), obtain the parameter a in formula (1)
And b, that is, obtain the identification model of yaw system.
4. a kind of angle PI controller tuning methods for wind power yawing system according to claim 3, its feature exists
In, the minimum PI controller parameters of yaw angle error are obtained in the step 3, complete the specific mistake adjusted of PI controllers
Cheng Wei：
Yaw drive system actual physics model is substituted with identification model to optimize PI controller parameters, the control after optimization
Device makes the angle, θ of yaw system minimum with instruction angle, θ * errors, i.e.,
F=∫ e2dt (4)
Wherein, e=θ *-θ, are input with θ *, under different PI state modulators, different output θ will be obtained, by traversal search
Method, finds the parameter for making formula (4) minimum；To accelerate search procedure, using trusted zones optimizing algorithm；
Assuming that the controller parameter to be designed is x=[Kp Ki], parameter x is realized by continuous iteration：
xk+1=xk+dk (5)
The wherein increased variable quantity d of each iteration of controller parameterkLess than current Trust Region Radius,
Replace f with secondary approximation model q (d)：
If along dkDirection qkValue reduce, then by formula (5) update controller parameter x, while retain trusted zones, otherwise, not more
New parameter x, trusted zones reduce；
Updated by continuous iteration, when formula (6) value of close iteration twice is less than given threshold, be judged to convergence, this up-to-date style
(4) value has minimum value, and now x corresponding Kp and Ki are the PI parameters of optimization.
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| CN108983595A (en) * | 2018-07-18 | 2018-12-11 | 天津大学 | A kind of automatic setting method of feedforward controller parameter |
| CN108983595B (en) * | 2018-07-18 | 2021-04-20 | 天津大学 | Automatic setting method for parameters of feedforward controller |
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