CN109739292A - Photovoltaic system MPPT obscures Auto-disturbance-rejection Control, controller and system - Google Patents
Photovoltaic system MPPT obscures Auto-disturbance-rejection Control, controller and system Download PDFInfo
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Abstract
The present disclosure proposes photovoltaic system MPPT to obscure Auto-disturbance-rejection Control, controller and system, establishes the model of the photovoltaic power supply system based on Boost；Disturbance is added near model stability operating point, obtains the small signal dynamics equation of Boost；Carrying out Laplace transform to the small signal dynamics equation of Boost can be obtained duty ratio disturbance quantity to the transmission function of photovoltaic cell output voltage disturbance quantity；Reference output voltage designs first differential tracker, extended state observer and error state feedback rate control；Fuzzy control is used in automatic disturbance rejection controller, fuzzy control and automatic disturbance rejection controller are combined and are applied to MPPT, by obscuring Application of Auto-Disturbance Rejection, simplify the process of adjustment automatic disturbance rejection controller parameter tuning, realize the adaptivity of controller parameter, make MPPT control strategy that there is good vulnerability to jamming, dynamic response, stability and robustness, avoids the complex process of parameter tuning.
Description
Technical field
This disclosure relates to automate, field of power electronics, Active Disturbance Rejection Control side is obscured more particularly to photovoltaic system MPPT
Method, controller and system.
Background technique
Photovoltaic power generation have clean and environmental protection, maintain easily, install simply, the service life is long, pollution-free, noiseless, not by region
The advantages that limitation.But also have the shortcomings that randomness, intermittence and the efficiency of light energy utilization are low etc..
Traditional MPPT tracking, some are controlled just with approximate linear relationship, such as: constant voltage process,
There is no truly realize MPPT for these algorithms.When acute variation occurs for external environment, photovoltaic battery array will be inclined
From maximum power point, to cause the loss of power.
It is normally applied observation method of perturbation in existing photovoltaic power supply system MPPT controller, but due to voltage disturbance amount
In the presence of observing method of perturbation will necessarily emergent power concussion problem when tracking maximum power point.In addition, when illumination mutates
When, observation method of perturbation can generate erroneous judgement, eventually lead to collapse of voltage.Fuzzy logic control method, neural network and sliding formwork control
These control method algorithm difficulty of implementation such as method are big and need high performance controller.
As it can be seen that disturbance observation method and conductance increment method will appear power oscillation and mistake when tracking maximum power point
Sentence.Comprehensive, can summarize the shortcomings that having MPPT control algolithm is: tracking slow, power oscillation, erroneous judgement etc..
By above-mentioned analysis, useful linear active disturbance rejection control strategy is studied in Boost in research both domestic and external
The problem of MPPT maximum power point tracking (MPPT), but all do not consider to study maximum power with Fuzzy Nonlinear Application of Auto-Disturbance Rejection
Point tracking (MPPT) controller.
Summary of the invention
In order to solve the deficiencies in the prior art, embodiment of the disclosure provides photovoltaic system MPPT and obscures active disturbance rejection control
Method processed, even if enabling photovoltaic power supply system quickly to reach maximum power point simultaneously in the case where temperature and illumination variation
And it being capable of stable operation.
To achieve the goals above, the disclosure uses following technical scheme:
Photovoltaic system MPPT obscures Auto-disturbance-rejection Control, comprising:
The model of the photovoltaic power supply system based on Boost of foundation；
Disturbance is added near model stability operating point, obtains the small signal dynamics equation of Boost；
Carrying out Laplace transform to the small signal dynamics equation of Boost can be obtained duty ratio disturbance quantity to photovoltaic
The transmission function of cell output voltage disturbance quantity；
Reference output voltage designs first differential tracker, extended state observer and error state feedback rate control；
Track to obtain reference voltage using first differential tracker, extended state observer observe obtaining system state and
Total disturbance, is made of the deviation of system, the voltage that reference voltage and observer obtain then with the change of the deviation of system and deviation
It is turned to the input of fuzzy controller, by exporting the input as nonlinear state error Feedback Control Laws after fuzzy reasoning
Amount, obtains control amount by error feedback control.
Further technical solution, the model of the photovoltaic power supply system based on Boost utilize state when establishing
The method of average models system, can be obtained according to KCL, KVL law:
In formula:
In formula: V is photovoltaic cell output voltage；I is that photovoltaic cell exports electric current；iLFor inductive current；V0For load electricity
Pressure；D is duty ratio；L is inductance value；C and C1For capacitance；R0For load value.
Further technical solution, the first differential tracker are as follows:
In formula: R is load value, VmFor the corresponding voltage in maximum power point place, i.e. the reference that is tracked of differential tracker
Voltage z1Indicate the voltage at the maximum power point of differential tracker tracking.
Further technical solution, the extended state observer:
It for above-mentioned first differential tracker, is controlled it, is enabled using single order automatic disturbance rejection controller (ADRC)
x2=f,2 rank ESO are then designed, using nonlinear extension state observer, Z1The state x of observation system1, Z2Observation system
Total disturbance f:
In formula: λ1、λ2For Error Gain；Z1For the state for tracking y in ESO；Z2For the shape for tracking expansion state f in ESO
State, δ are the linearly interval length of nonlinear function, b0For the disturbance compensation factor, α is the power number of nonlinear function, and e is differential
The original signal and ESO of tracker tracking observe the error between the original signal come.
Further technical solution, the error state feedback rate control:
Wherein, Δ β0、Δβ1For the output valve of fuzzy controller, β00For Δ β0Initial value, β10For Δ β1Initial value,
qiAnd qpFor correction factor, β0It is the parameter of integration control in error state Feedback Control Laws, β1In error state Feedback Control Laws
The parameter of ratio control, b0The disturbance compensation factor, u0Error state feedback rate control.
Further technical solution, various combination of the fuzzy controller according to input quantity, the change provided according to control rule
Change amount makes the control effect of controller reach best；
Choose error e and error rateFor the input language variable of fuzzy controller, Δ β0With Δ β1For output language
Variable.Determine the continuous domain range of input quantity and output quantity, fuzzy subset is only { NB (negative big), NS (bearing small), ZO (zero)
PS (just small), PB (honest) } membership function of fuzzy subset selects triangular membership functions, determine the mould of input quantity and output quantity
Domain is pasted, fuzzy reasoning uses mamdani rationalistic method, and model fuzz method uses weighted mean method.
Further technical solution, fuzzy controller fuzzy control rule table include table 1 and table 2:
1 Δ β of table0Fuzzy control rule table
2 Δ β of table1Fuzzy control rule table
Embodiment of the disclosure also discloses a kind of controller, and the controller includes Nonlinear Tracking Differentiator, expansion state
Observer and nonlinear state error Feedback Control Laws；
The first differential tracker obtains reference voltage for tracking；
The extended state observer is used to observe the state Z for the system that obtains1That is photovoltaic output voltage V and total disturbance f, so
Afterwards by reference voltage VmThe state variable Z obtained with extended state observer1That is photovoltaic output voltage V constitutes the deviation e of system,
With the deviation e of system and the variation of deviationInput as fuzzy controller；
Nonlinear state error Feedback Control Laws, by fuzzy controller by exporting Δ β after fuzzy reasoning0With Δ β1As
Input quantity obtains control amount by error feedback control.
Embodiment of the disclosure also discloses a kind of fuzzy active disturbance rejection system, including controller, utilizes above controller
Realize the MPPT maximum power point tracking to photovoltaic system.
Embodiment of the disclosure also discloses a kind of photovoltaic system, and the photovoltaic system is based on Boost
Photovoltaic power supply system obscures Auto-disturbance-rejection Control using above-mentioned photovoltaic system MPPT and realizes to MPPT maximum power point tracking.
Compared with prior art, the beneficial effect of the disclosure is:
The MPPT controller based on fuzzy active disturbance rejection of the disclosure, come solve poor MPPT algorithm vulnerability to jamming, power oscillation, with
The disadvantages of track speed is slow, while fuzzy control is applied in the parameter tuning of non-linear automatic disturbance rejection controller, realize parameter
Adaptivity, greatly improve the efficiency of controller.
The disclosure is for power oscillation, erroneous judgement existing for existing MPPT control algolithm, tracking velocity is slow, algorithm difficulty of implementation
Greatly, the problems such as project cost is high, control circuit is complicated, fuzzy active disturbance rejection is applied in MPPT, tracking has both been effectively raised
Speed and the efficiency of light energy utilization, and the adaptivity of automatic disturbance rejection controller parameter is realized, improve the performance of controller.
Active Disturbance Rejection Control is primarily directed to a kind of uncertainty plantWherein f
For the unknown disturbance of system, including interior disturb and disturb outside.Controller mainly consists of three parts: Nonlinear Tracking Differentiator (TD), expansion shape
State observer (ESO) and nonlinear state error Feedback Control Laws (NLSEF).Entire controller only needs the input quantity of system and defeated
Output is as information source.The essence of active disturbance rejection is that disturbance f is estimated by ESO, and disturbance is offset in then design of feedback control, thus
Achieve the purpose that reconfigure object.Active disturbance rejection is obscured in the disclosure to combine fuzzy control and automatic disturbance rejection controller, is not only had
Have the advantages that automatic disturbance rejection controller reaction speed is fast, overshoot is small, and there is stronger robustness and anti-interference, it is more important
Be the adaptivity for realizing controller parameter, greatly improve the efficiency of controller.
Detailed description of the invention
The Figure of description for constituting a part of this disclosure is used to provide further understanding of the disclosure, and the disclosure is shown
Meaning property embodiment and its explanation do not constitute the improper restriction to the disclosure for explaining the disclosure.
Fig. 1 is structure chart of the photovoltaic cell of the one or more examples of implementation of the disclosure in conjunction with Boost circuit；
Fig. 2 is that the single order of the one or more examples of implementation of the disclosure obscures the structure chart of ADRC.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the disclosure.Unless another
It indicates, all technical and scientific terms used herein has usual with disclosure person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the disclosure.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
Active Disturbance Rejection Control is primarily directed to a kind of uncertainty plantWherein f
For the unknown disturbance of system, including interior disturb and disturb outside.Controller mainly consists of three parts: Nonlinear Tracking Differentiator (TD), expansion shape
State observer (ESO) and nonlinear state error Feedback Control Laws (NLSEF).Entire controller only needs the input quantity of system and defeated
Output is as information source.The essence of active disturbance rejection is that disturbance f is estimated by ESO, and disturbance is offset in then design of feedback control, thus
Achieve the purpose that reconfigure object.Active disturbance rejection is obscured in the disclosure to combine fuzzy control and automatic disturbance rejection controller, is not only had
Have the advantages that automatic disturbance rejection controller reaction speed is fast, overshoot is small, and there is stronger robustness and anti-interference, it is more important
Be the adaptivity for realizing controller parameter, greatly improve the efficiency of controller.
In a kind of typical embodiment of the disclosure, photovoltaic system MPPT obscures Auto-disturbance-rejection Control, comprising:
The model of the photovoltaic power supply system based on Boost of foundation, structure of the photovoltaic cell in conjunction with Boost circuit
Figure is as shown in Figure 1.
System is modeled using state averaging method, can be obtained according to KCL, KVL law:
In formula:
In formula: V is photovoltaic cell output voltage；I is that photovoltaic cell exports electric current；iLFor inductive current；V0For load electricity
Pressure；D is duty ratio；L is inductance value；R is inductance parasitic resistance；C is input filter capacitor；C1For output filter capacitor；R0It is negative
Carry resistance.
In order to solve the small signal dynamics equation of Boost, disturbance is added near its stable operating point, enables instantaneous
Value are as follows:
In formula:For disturbance quantity:Value when to stablize.Omitted variables multiply
Product, obtains the small signal dynamics equation of Boost are as follows:
In formula:
It is available that Laplace transform is carried out to above formulaIt is rightTransmission function
In formula:
α1=V0/(LC)；α2=[V0+R0(1-d)iL]/(R0LCC1)；
β3=1/ (R0C1)+R/L
As can be seen from the above equation, state variable V, iL、V0Between stronger coupled relation, in Active Disturbance Rejection Control, can will
Coupling unit is regarded the interior of system as and is disturbed, to realize decoupling.Therefore it may only be necessary to which the system of determination is output and input.According to
It is above-mentioned, available:
In formula: V is photovoltaic cell output voltage；I is that photovoltaic cell exports electric current；iLFor inductive current；W is the outer of system
Portion's disturbance, parameter uncertainty, switching loss such as Boost, evaluated error and detection error of system etc..Therefore on
Stating formula can be written as
In formula: f is total disturbance；V0For load voltage；D is duty ratio；b0For Discontinuous Factors.
Above-mentioned be a first-order system i.e.Output is the output voltage V of photovoltaic, and input is photovoltaic electric current
I.The extended state observer and linearity error of first differential tracker below, second order can be designed for this first-order system
STATE FEEDBACK CONTROL.
In another embodiment of the present disclosure, the design of fuzzy automatic disturbance rejection controller is disclosed: determining system input reference
The differential tracker of voltage
Following first differential tracker is designed the reference output voltage of fuzzy active disturbance rejection system:
Nonlinear Tracking Differentiator is derived from by stable system, as long as there is a stable system, we can root
Nonlinear Tracking Differentiator is designed according to this stable system.It is well known thatIt is an exponentially stable system,
Because of the characteristic value of its only one negative real part, and first differential tracker can be designed by this stable system derivation
, i.e., following first differential tracker:
In formula: R is velocity factor, can change the speed of differential tracker tracking by adjusting R.z1Indicate differential tracking
The reference voltage of device tracking.
Determine the extended state observer of system:
It unites for above-mentioned 1 level, is controlled it using 1 rank ADRC, enabledThen design
2 rank ESO, in order to improve the precision and efficiency of observer, using nonlinear extension state observer.Z1The state x of observation system1,
Z2Total disturbance f of observation system
In formula: λ1、λ2For Error Gain；Z1For the state for tracking y in ESO；Z2For the shape for tracking expansion state f in ESO
State.
Determine the error state feedback rate control of system:
Since system is a first-order system, in order to eliminate static error, error joined in linearity error feedback
Integration control, the integration control of error is by realizing error intergal.Therefore, PD control is designed for above-mentioned first-order system, it may be assumed thatThe linearity error feedback designed observes the total disturbance f come with extended state observer again
The control u of system is constituted together, it may be assumed thatThe form that can be written as follow:
Wherein Δ β0、Δβ1For the output valve of fuzzy controller, β00For Δ β0Initial value, β10For Δ β1Initial value, qi
And qpFor correction factor.
Choose error e and error rateFor the input language variable of fuzzy controller, Δ β0With Δ β1For output language
Variable.Determine the continuous domain range of input quantity and output quantity, fuzzy subset is only { NB (negative big), NS (bearing small), ZO (zero)
PS (just small), PB (honest) } membership function of fuzzy subset selects triangular membership functions.Determine the mould of input quantity and output quantity
Domain is pasted, fuzzy reasoning uses mamdani rationalistic method, and model fuzz method uses weighted mean method.
Controller imitates the control of controller according to the variable quantity that control rule provides according to the various combination of input quantity
Fruit reaches most preferably, and rule is general are as follows:
(1) when system input is inclined | e | when bigger, β1Value is appropriate to be increased, and is accelerated system response, is reduced β0Value, to accelerate to be
The response speed of system.
(2) when system error originated from input | e | and error rateWhen moderate, β1It is appropriate to reduce, to reduce overshoot, take moderate
β0Value, to accelerate the response speed of system.
(3) when systematic error | e | when smaller, β0And β1Value can suitably increase.
(4) systematic error change rate is kept offValue it is bigger when, β0Value can suitably increase, β1Value can suitably reduce.
According to the summary of experience of the above rule and forefathers, following fuzzy control rule table is devised.
1 Δ β of table0Fuzzy control rule table
2 Δ β of table1Fuzzy control rule table
It can be seen that fuzzy automatic disturbance rejection controller is by automatic disturbance rejection controller and fuzzy control from the design of the above controller
Device two parts are constituted, and are tracked to obtain V by TDm, ESO observes obtaining the state V and total disturbance f of system, then by reference voltage VmWith
The voltage V that observer obtains constitutes the deviation e of system, with the deviation e of system and the variation of deviationAs the defeated of fuzzy controller
Enter, by exporting Δ β after fuzzy reasoning0With Δ β1As the input quantity of SEF, control amount u is obtained by error feedback control, one
The structure chart that rank obscures ADRC is illustrated in fig. 2 shown below.
Embodiment of the disclosure also discloses a kind of fuzzy active disturbance rejection system, including controller, utilizes above controller
Realize the MPPT maximum power point tracking to photovoltaic system.
Embodiment of the disclosure also discloses a kind of photovoltaic system, and the photovoltaic system is based on Boost
Photovoltaic power supply system obscures Auto-disturbance-rejection Control using above-mentioned photovoltaic system MPPT and realizes to MPPT maximum power point tracking.
The disclosure uses non-linear Auto Disturbances Rejection Control Technique, and non-linear automatic disturbance rejection controller is used in MPPT, can be significantly
System response time is improved, power oscillation is reduced, even if controller also can be fine when illumination and temperature change
Realization MPPT, improve the utilization rate of luminous energy.
Fuzzy control is used in automatic disturbance rejection controller, fuzzy control and automatic disturbance rejection controller are combined and are applied to
MPPT simplifies the process of adjustment automatic disturbance rejection controller parameter tuning, realizes controller by obscuring Application of Auto-Disturbance Rejection
The adaptivity of parameter makes MPPT control strategy have good vulnerability to jamming, dynamic response, stability and robustness, avoids
The complex process of parameter tuning.
The disclosure controls the MPPT maximum power point tracking (MPPT) based on Boost with fuzzy Application of Auto-Disturbance Rejection
Device is designed, even if photovoltaic system, by temperature and illumination effect, system still can also trace into well
Maximum power point voltage greatly improves the utilization rate of luminous energy.
The foregoing is merely preferred embodiment of the present disclosure, are not limited to the disclosure, for the skill of this field
For art personnel, the disclosure can have various modifications and variations.It is all within the spirit and principle of the disclosure, it is made any to repair
Change, equivalent replacement, improvement etc., should be included within the protection scope of the disclosure.
Claims (10)
1. photovoltaic system MPPT obscures Auto-disturbance-rejection Control, characterized in that include:
The model of the photovoltaic power supply system based on Boost of foundation；
Disturbance is added near model stability operating point, obtains the small signal dynamics equation of Boost；
Carrying out Laplace transform to the small signal dynamics equation of Boost can be obtained duty ratio disturbance quantity to photovoltaic cell
The transmission function of output voltage disturbance quantity；
Reference output voltage designs first differential tracker, extended state observer and error state feedback rate control；
It tracks to obtain reference voltage using first differential tracker, extended state observer is observed obtaining the state of system and always disturbed
It is dynamic, the deviation of system is then made of the voltage that reference voltage and observer obtain, and is made with the variation of the deviation of system and deviation
It is passed through for the input of fuzzy controller by exporting the input quantity as nonlinear state error Feedback Control Laws after fuzzy reasoning
It crosses error feedback control and obtains control amount.
2. photovoltaic system MPPT as described in claim 1 obscures Auto-disturbance-rejection Control, characterized in that converted based on Boost
The model of the photovoltaic power supply system of device models system when establishing, using state averaging method, according to KCL, KVL law
:
In formula:
In formula: V is photovoltaic cell output voltage；I is that photovoltaic cell exports electric current；iLFor inductive current；V0For load voltage；D is
Duty ratio；L is inductance value；R is inductance parasitic resistance；C is input filter capacitor；C1For output filter capacitor；R0For load electricity
Resistance.
3. photovoltaic system MPPT as described in claim 1 obscures Auto-disturbance-rejection Control, characterized in that the first differential with
Track device are as follows:
In formula: R is load value, VmFor the corresponding voltage in maximum power point place, i.e. the reference voltage that is tracked of differential tracker,
z1Indicate the voltage that the maximum power of differential tracker tracking is pointed out.
4. photovoltaic system MPPT as claimed in claim 1 or 3 obscures Auto-disturbance-rejection Control, characterized in that the expansion shape
State observer are as follows:
It for above-mentioned first differential tracker, is controlled it, is enabled using 1 rank automatic disturbance rejection controllerx2=f,
2 rank ESO are then designed, using nonlinear extension state observer, Z1The state x of observation system1, Z2Total disturbance f of observation system:
In formula: λ1、λ2For Error Gain；Z1For the state for tracking y in ESO；Z2For the state for tracking expansion state f in ESO, δ is
The linearly interval length of nonlinear function, b0For the disturbance compensation factor, α is the power number of nonlinear function, and e is differential tracker
The original signal and ESO of tracking observe the error between the original signal come.
5. photovoltaic system MPPT as described in claim 1 obscures Auto-disturbance-rejection Control, characterized in that the error state is anti-
Present control rate:
Wherein, Δ β0、Δβ1For the output valve of fuzzy controller, β00For Δ β0Initial value, β10For Δ β1Initial value, qiAnd qp
For correction factor, β0It is the parameter of integration control in error state Feedback Control Laws, β1Ratio control in error state Feedback Control Laws
The parameter of system, b0The disturbance compensation factor, u0For error state feedback rate control, Z2For the state for tracking expansion state f in ESO.
6. photovoltaic system MPPT as described in claim 1 obscures Auto-disturbance-rejection Control, characterized in that fuzzy controller according to
The various combination of input quantity makes the control effect of controller reach best according to the variable quantity that control rule provides；
Choose error e and error rateFor the input language variable of fuzzy controller, Δ β0With Δ β1For output language variable,
Determine the continuous domain range of input quantity and output quantity, fuzzy subset is only that { NB (negative big), NS (bearing small), ZO (zero) PS are (just
It is small), PB (honest) membership function of fuzzy subset selects triangular membership functions, determine the fuzzy theory of input quantity and output quantity
Domain, fuzzy reasoning use mamdani rationalistic method, and model fuzz method uses weighted mean method.
7. photovoltaic system MPPT as claimed in claim 6 obscures Auto-disturbance-rejection Control, characterized in that fuzzy controller is fuzzy
Control rule table includes table 1 and table 2:
1 Δ β of table0Fuzzy control rule table
2 Δ β of table1Fuzzy control rule table
。
8. a kind of controller, characterized in that the controller includes Nonlinear Tracking Differentiator, extended state observer and nonlinear state
Error Feedback Control Laws；
The first differential tracker obtains reference voltage for tracking；
The extended state observer is used to observe the state Z for the system that obtains1That is photovoltaic output voltage V and total disturbance f, then by
The Z that reference voltage and observer obtain1That is photovoltaic output voltage V constitutes the deviation e of system, with the deviation e of system and deviation
VariationInput as fuzzy controller；
Nonlinear state error Feedback Control Laws, by fuzzy controller by exporting Δ β after fuzzy reasoning0With Δ β1As input
Amount, obtains control amount by error feedback control.
9. a kind of fuzzy active disturbance rejection system, including controller according to any one of claims 8 are realized using above controller to photovoltaic system
The MPPT maximum power point tracking of system.
10. a kind of photovoltaic system, the photovoltaic system is the photovoltaic power supply system based on Boost, using claim
Any photovoltaic system MPPT of 1-7 obscures Auto-disturbance-rejection Control and realizes to MPPT maximum power point tracking.
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| CN114879806A (en) * | 2022-06-07 | 2022-08-09 | 固德威电源科技(广德)有限公司 | Photovoltaic static and dynamic MPPT disturbance observation and identification method and photovoltaic array power generation system |
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