CN102720634B - Variable universe fuzzy electric pitch control method for optimizing parameters - Google Patents

Variable universe fuzzy electric pitch control method for optimizing parameters Download PDF

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CN102720634B
CN102720634B CN201210234372.1A CN201210234372A CN102720634B CN 102720634 B CN102720634 B CN 102720634B CN 201210234372 A CN201210234372 A CN 201210234372A CN 102720634 B CN102720634 B CN 102720634B
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fuzzy
domain
contraction
parameter
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董海鹰
魏占宏
李宏伟
李晓青
王国华
李帅兵
马博
李晓楠
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Lanzhou Jiaotong University
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Abstract

The invention discloses a variable universe fuzzy electric pitch control method for optimizing parameters, and relates to three-closed-loop (namely a current loop, a velocity loop and a position loop) control established by an electric pitch system. Through analyzing the structure of contraction-expansion factors of the variable universe, the parameters thereof can be optimized by genetic algorithm, the intelligent optimization of the parameters can be realized, and a reasonable mechanism for determining the contraction-expansion factors can be established. According to the invention, the optimized variable universe fuzzy control algorithm is applied to the velocity and position control for the electric pitch system, and the appropriate target function is established according to control objectives of the velocity loop and the position loop, so that the optimal control performance of a variable universe fuzzy controller can be realized. The torque pulsation is efficiently inhibited, the dynamic and steady performances of the system are improved, and finally the quick and accurate tracing of the pitch angle position is realized, therefore, an efficient and practical control method is provided for the wind power pitch system.

Description

A kind of fuzzy electric variable pitch controlling method of change domain of Optimal Parameters
Technical field
The present invention relates to electric variable pitch controlling method technical field, particularly, relate to a kind of fuzzy electric variable pitch controlling method of change domain of Optimal Parameters.
Background technique
For the nonlinear system of the serious large inertia that lags behind of the such high-order strong coupling of wind-powered electricity generation unit electric variable propeller system, although conventional controller technology is very ripe, in industrial process control, obtain being widely used, but meet wind-powered electricity generation unit and respond fast the requirement of wind speed, the control effect of these controllers is undesirable on the contrary.Based on the electric variable propeller system of fuzzy control, fuzzy controller can be undertaken some by the simple scale conversion of formula and adjust, to the knot model of control ring without further investigation, can obtain certain control effect, by the division in domain interval also be can further improve to control quality, this is applied in fuzzy control the advantage place of wind-powered electricity generation electric variable propeller system just.But controller still has certain blindness in parameter tuning process, and the key that becomes domain fuzzy control is to determine contraction-expansion factor, domain is changed in the reasonable scope, and current mainly rely on empirical value or repeatedly debugging realize, it may not be optimum making controller parameter, controls quality not best.
Summary of the invention
For problems of the prior art, the present invention proposes a kind of change domain fuzzy control method that utilizes genetic algorithm optimization contraction-expansion factor in electric variable pitch control system.The change domain FUZZY ALGORITHMS FOR CONTROL of optimization is applied in the speed and positioning control of electric variable propeller system, sets up suitable objective function according to the control target of speed ring and position ring, realize the optimal control performance that becomes Universe Fuzzy Controller.Effectively suppressed torque pulsation, improved dynamic performance and the steady-state behaviour of system, and finally realized propeller pitch angle position fast, accurately follow the tracks of.For wind power pitch-controlled system provides a kind of effective, practical controlling method.
For this reason, adopt following technological scheme: a kind of fuzzy electric variable pitch controlling method of change domain of Optimal Parameters, it relates to three closed loop controls that electric variable propeller system is set up, be electric current loop, speed ring and position ring, become the structure of domain contraction-expansion factor by analysis, utilize its parameter of genetic algorithm optimization, realize the intelligent optimizing of parameter, set up the rational mechanism of determining contraction-expansion factor; Specific as follows:
A, the change domain FUZZY ALGORITHMS FOR CONTROL of genetic algorithm optimization is applied in the speed and positioning control of described electric variable propeller system, the input of described position and speed controller is all error
Figure 928850DEST_PATH_IMAGE001
variable quantity with error
Figure 118523DEST_PATH_IMAGE002
, output is all
Figure 18345DEST_PATH_IMAGE003
, the basic domain of definite described speed and position controller input, output language variable respectively, the basic domain of input language variable is respectively
Figure 20674DEST_PATH_IMAGE004
, and the basic domain of output language variable is
Figure 322343DEST_PATH_IMAGE005
, the structure that can set up contraction-expansion factor is:
Figure 682917DEST_PATH_IMAGE006
(1)
B, set up the fuzzy control rule table of described electric variable pitch speed and positioning control, in double input list output fuzzy controller, based on becoming domain thought, design becomes domain Fuzzy control system;
C, the parameter list of described contraction-expansion factor is shown as to chromosome or the individuality in hereditary space, encode, obtain initial population, the parameter of described contraction-expansion factor is assigned to designed fuzzy inference system, use the fuzzy control of described change domain to control, set up suitable objective function according to the control target of described speed ring and position ring, write the fitness function that calculates ideal adaptation degree value according to this objective function, the fitness value that calculates each individuality by this fitness function, offers heredity operatorselect operation, interlace operation and mutation operation, obtain new colony, after setting the evolution of iterations, algorithmic statement is in best chromosome, it is the optimal parameter of described contraction-expansion factor, thereby realizes the optimal control performance of electric variable propeller system change Universe Fuzzy Controller.
Further:
Described contraction-expansion factor parameter adopts real coding, and chromosome length is 6.
In described speed ring objective function, add Error Absolute Value time integral to improve its transition dynamic performance.
In described position ring objective function, take penalty factor to avoid over control.
The present invention becomes the structure of domain contraction-expansion factor by analysis, utilize its parameter of genetic algorithm optimization, realize the intelligent optimizing of parameter, set up the rational mechanism of definite contraction-expansion factor, efficiently solve and become domain fuzzy control method contraction-expansion factor by experience and repeatedly debug definite problem, improved control accuracy.The change domain FUZZY ALGORITHMS FOR CONTROL of optimization is applied in the speed and positioning control of electric variable propeller system, sets up suitable objective function according to the control target of speed and position, realize the optimal control performance that becomes Universe Fuzzy Controller.Effectively suppressed torque pulsation, improved dynamic performance and the steady-state behaviour of system, and finally realized propeller pitch angle position fast, accurately follow the tracks of.For wind power pitch-controlled system provides a kind of effective, practical controlling method.
Accompanying drawing explanation
Fig. 1 is electric variable propeller system control principle structural drawing;
Fig. 2 is the speed ring of genetic algorithm optimization of the present invention and the control block diagram of position ring;
Fig. 3 is the change domain fuzzy control flow chart of genetic algorithm optimization of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described, should be appreciated that preferred embodiment described herein, only for description and interpretation the present invention, is not intended to limit the present invention.
In the time that wind speed is below the above cut-out wind speed of rated wind speed, pitch-controlled system starts to become oar, given drive motor rotating speed
Figure 70036DEST_PATH_IMAGE007
and propeller pitch angle
Figure 377520DEST_PATH_IMAGE008
, calculate speed error according to actual measured value
Figure 268116DEST_PATH_IMAGE009
, propeller pitch angle error
Figure 65171DEST_PATH_IMAGE010
and speed error variable quantity
Figure 674007DEST_PATH_IMAGE011
, propeller pitch angle error change amount , set it as the input of electric variable propeller system position and speed change Universe Fuzzy Controller, see attached Fig. 1 and 2, according to formula 1, set up the structure of contraction-expansion factor, total
Figure 858180DEST_PATH_IMAGE013
treat excellent parameter for 6.
Set up the fuzzy control rule table of described electric variable pitch speed and positioning control, in double input list output fuzzy controller, based on becoming domain thought, design described change domain Fuzzy control system.Wherein,
Figure 763819DEST_PATH_IMAGE014
with
Figure 859951DEST_PATH_IMAGE015
be respectively two input variables of described fuzzy controller,
Figure 571555DEST_PATH_IMAGE016
with
Figure 436743DEST_PATH_IMAGE017
be respectively the corresponding contraction-expansion factor of described input variable,
Figure 513284DEST_PATH_IMAGE018
be the contraction-expansion factor of described output variable,
Figure 96712DEST_PATH_IMAGE019
the controller function approaching for described fuzzy controller.The computing of its basic underlying variables of Fuzzy control system depends on time step
Figure 346427DEST_PATH_IMAGE020
, be designated as respectively , therefore available time function represents to become domain, is denoted as
Figure 641460DEST_PATH_IMAGE022
.Along with the carrying out of optimizing, also corresponding changing of input output fuzzy subset domain, membership function
Figure 712184DEST_PATH_IMAGE023
corresponding variation occurs, and what remember is
Figure 195949DEST_PATH_IMAGE024
, this makes fuzzy control rule become one group of DP :
Figure 516389DEST_PATH_IMAGE026
(2)
In the time of k=0, formula 2 is fuzzy control initial control rules.Along with the variation of k, control function, along with domain changes and correspondingly distortion occurs, can be designated as:
Figure 808830DEST_PATH_IMAGE027
(3)
Wherein,
Figure 665928DEST_PATH_IMAGE028
for the membership function number of input language variable (error),
Figure 297898DEST_PATH_IMAGE029
;
Figure 949459DEST_PATH_IMAGE030
for the membership function number of input language variable (error rate),
Figure 994775DEST_PATH_IMAGE031
; ,
Figure 938777DEST_PATH_IMAGE033
occurrence determine by real system runnability.
From becoming domain theory,
Figure 964502DEST_PATH_IMAGE034
monotonicity has guaranteed monotonicity, thereby guaranteed control function validity.The design that becomes Universe Fuzzy Controller has weakened the dependence to control field expertise, according to the variation tendency of fuzzy control rule, correspondingly basic domain is stretched along with the variation of controller input language variable, by basic domain self adaption is adjusted, realize the improvement of electric variable propeller system dynamic performance, improve the stable state accuracy of controlling.
6 parameter lists of described contraction-expansion factor are shown as to chromosome or the individuality in hereditary space, utilize genetic algorithm to be optimized 6 of contraction-expansion factor parameters, carry out real coding, chromosome length .Real coding needn't carry out numerical value conversion, can be directly in phenotype, carries out operatings of genetic algorithm solving.Obtain initial population, 6 parameters of described contraction-expansion factor are assigned to designed change domain fuzzy inference system, use the fuzzy control of described change domain to control, set up suitable objective function according to the control target of described speed ring and position ring
Figure 30361DEST_PATH_IMAGE038
, in described speed ring objective function, add Error Absolute Value time integral to improve its transition dynamic performance, in described position ring objective function, take penalty factor to avoid over control.Adopt following objective function to guarantee to have better dynamic and output controlled quentity controlled variable within limits:
(4)
Be wherein
Figure 521703DEST_PATH_IMAGE040
controlled quentity controlled variable,
Figure 45088DEST_PATH_IMAGE041
for the rise time,
Figure 474932DEST_PATH_IMAGE042
for the weights of objective speed function.
The given angle that is input as propeller pitch angle of position ring
Figure 887197DEST_PATH_IMAGE043
with actual output angle
Figure 427899DEST_PATH_IMAGE044
difference
Figure 71370DEST_PATH_IMAGE045
and error change
Figure 406537DEST_PATH_IMAGE046
, can obtain compared with reflex angle degree by fuzzy reasoning.Its structure is shown in accompanying drawing 2, adopts contraction-expansion factor described in genetic algorithm optimization 6 parameter values, adopt penalty factor to avoid position ring output overshoot, and objective function is as follows:
Figure 151956DEST_PATH_IMAGE048
(5)
Wherein for controlled quentity controlled variable, for the rise time,
Figure 372219DEST_PATH_IMAGE051
for the weights of Place object function.
Write the fitness function that calculates ideal adaptation degree value according to described objective function, fitness function is taken as:
Figure 254724DEST_PATH_IMAGE052
(6)
Passing through type 6 fitness functions calculate the fitness value of each individuality, offer genetic operator (order offers and selects operator, crossover operator and mutation operator) and select operation, interlace operation and mutation operation, obtain new colony, after setting the evolution of iterations, algorithmic statement is in best chromosome, it is the optimal parameter of described contraction-expansion factor, thereby realizes the optimal control performance of electric variable propeller system change Universe Fuzzy Controller.
Contraction-expansion factor is adopted after genetic algorithm optimization, can directly determine its optimum value, efficiently solve and become domain fuzzy control method contraction-expansion factor by experience and repeatedly debug definite problem, make to become the application of domain fuzzy control on electric variable propeller system conveniently and actual effect.

Claims (4)

1. the fuzzy electric variable pitch controlling method of the change domain of an Optimal Parameters, it relates to three closed loop controls that electric variable propeller system is set up, be electric current loop, speed ring and position ring, it is characterized in that: the structure that becomes domain contraction-expansion factor by analysis, utilize its parameter of genetic algorithm optimization, realize the intelligent optimizing of parameter, set up the rational mechanism of determining contraction-expansion factor; Specific as follows:
A, the change domain FUZZY ALGORITHMS FOR CONTROL of genetic algorithm optimization is applied in the speed and positioning control of described electric variable propeller system, the input of described position and speed controller is all error variable quantity with error
Figure 559531DEST_PATH_IMAGE002
, output is all
Figure 552895DEST_PATH_IMAGE003
, the basic domain of definite described speed and position controller input, output language variable respectively, the basic domain of input language variable is respectively
Figure 307224DEST_PATH_IMAGE004
, and the basic domain of output language variable is
Figure 857285DEST_PATH_IMAGE005
, the structure of setting up the contraction-expansion factor of described input, output language variable is:
(1)
Total in formula (1) treat excellent parameter for 6;
B, set up the fuzzy control rule table of described electric variable pitch speed and positioning control, in double input list output fuzzy controller, based on becoming domain thought, design becomes domain Fuzzy control system;
C, the parameter list of contraction-expansion factor is shown as to chromosome or the individuality in hereditary space, encode, obtain initial population, the parameter of described contraction-expansion factor is assigned to designed fuzzy inference system, use the fuzzy control of described change domain to control, set up suitable objective function according to the control target of described speed ring and position ring, write the fitness function that calculates ideal adaptation degree value according to this objective function, calculate the fitness value of each individuality by this fitness function, offer genetic operator and select operation, interlace operation and mutation operation, obtain new colony, after setting the evolution of iterations, algorithmic statement is in best chromosome, it is the optimal parameter of described contraction-expansion factor, thereby realize the optimal control performance of electric variable propeller system change Universe Fuzzy Controller.
2. according to the fuzzy electric variable pitch controlling method of the change domain of a kind of Optimal Parameters described in right 1, it is characterized in that: described contraction-expansion factor parameter adopts real coding, and chromosome length is 6.
3. according to the fuzzy electric variable pitch controlling method of the change domain of a kind of Optimal Parameters described in right 1, it is characterized in that: in described speed ring objective function, add Error Absolute Value time integral to improve its transition dynamic performance.
4. according to the fuzzy electric variable pitch controlling method of the change domain of a kind of Optimal Parameters described in right 1, it is characterized in that: in described position ring objective function, take penalty factor to avoid over control.
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