CN103346676B - The control system of Cz monocrystal stove high frequency switch power and control method - Google Patents

Abstract

The control system of Cz monocrystal stove high frequency switch power disclosed by the invention and control method, Adaptive Fuzzy Control is combined with Sliding mode variable structure control, for Cz monocrystal stove HF switch heating power supply, design power-supply controller of electric based on adaptive fuzzy sliding mode variable structure control method, play fuzzy control and the respective advantage of Sliding mode variable structure control, improve the dynamic property of system further, input voltage or load disturbance are had the preferable robustness of phenomenon, buffeting that general sliding formwork occur has been alleviated or avoided.

Description

The control system of Cz monocrystal stove high frequency switch power and control method

Technical field

The invention belongs to Cz monocrystal stove high frequency switch power and control technical field, be specifically related to a kind of Cz monocrystal stove By the control method of high frequency switch power.

Background technology

Industry monocrystal silicon (whether solar level or IC level) 90% is above using Cz (Czochralski) method raw Long, unmelted polycrystalline silicon become silicon liquid guide lifting raw by seed crystal the most under vacuum conditions in the temperature environment of about 1420 DEG C Growing up to monocrystal silicon, these monocrystal silicon are widely used in solar energy and integrated circuit industry as most basic material.Add thermoelectricity Source is heart and the power of straight pulling silicon single crystal furnace, and its control accuracy, reliability, conversion efficiency etc. are that monocrystal silicon industry improves production Efficiency and the basis of benefit.Switch heating power supply using IGBT as power device utilizes IGBT power semiconductor as switch Pipe, utilizes high-frequency pulsed width modulation (PWM) technology or high-frequency impulse frequency modulating technology (PFM) to control the break-make of electric current to be formed High-frequency pulse current；With the help of inductance (high frequency transformer), by the big electricity of low pressure that the output of diode all wave rectification is stable Stream.Such power supply has the advantages such as conversion efficiency height, power factor height, little, the good stability of volume.At present, silicon monocrystal growth is just Developing towards high-purity, high integrality, high uniformity and major diameter direction, the control accuracy of Switching Power Supply is proposed higher by this Requirement, needs to be improved the interference rejection ability of system by advanced control algolithm, to obtain high-precision DC source for heating Device provides electric energy.

Regulatory PID control method needs longer regulating time, dynamic characteristic when load changing and input voltage disturbance Poor, cause output power of power supply to fluctuate, affect monocrystalline quality；Simultaneously as the non-linear behavior of high frequency switch power self, Use traditional PID to control to still have several drawbacks part, such as when being operated in the bigger operating point of dutycycle, output voltage There will be obvious hyperharmonic vibration, be unfavorable for the steady operation of Switching Power Supply.

First sliding mode variable structure control method makes the state trajectory of system move to the diverter surface suitably chosen by control, Then making Phase Pathway along diverter surface progressive motion to equilibrium point, system once enters sliding mode motion, at certain condition Under, interference and parameter perturbation have invariance the most to external world.Owing to variable-structure control need not accurate model and parameter estimation, Therefore the method has the advantages such as algorithm simple, good in anti-interference performance, easy canbe used on line, it is adaptable to Uncertain nonlinear is changeable The control object of amount.For the non-linear behavior of Switching Power Supply, the Non-Linear Control Theories such as sliding moding structure can be incorporated into In the control strategy of high frequency switch power.But, switching characteristic is the most discontinuous, therefore Sliding mode variable structure control system There is buffeting problem in system.In Sliding mode variable structure control, introduce fuzzy control theory, the impact of buffeting can be weakened and even disappear Remove, improve the performance that sliding formwork controls further.

Summary of the invention

It is an object of the invention to provide the control method of a kind of Cz monocrystal stove high frequency switch power, solve existing control System dynamic characteristic processed is poor, causes output power of power supply to fluctuate, the problem affecting monocrystalline quality.

The technical solution adopted in the present invention is, the control method of Cz monocrystal stove high frequency switch power, specifically according to Following steps are implemented:

Step 1: Switching Power Supply power section main circuit importation incoming transport voltage, through front-end filtering rectification, entirely Carry out voltage transformation after bridge reversals and high frequency transformer effect, after the rectifying and wave-filtering of rear end, obtained exporting DC voltage；

Step 2: set up model according to controlled device, it is thus achieved that the key parameter in model: input voltage V_DC, load inductance L_f, load capacitance C_o, load resistance R, original edge voltage loses the ratio R with load current_d；

Step 3: according to the modelling adaptive fuzzy sliding mode controller in step 2, determine the coefficient in switching function s And control law, obtain closed-loop control system；

Step 4: analog signal isolating gathers the d. c. voltage signal of change-over circuit 4 acquisition step 1 output, as feedback letter Number pass to the wave digital lowpass filter 5 of controller part, send the Adaptive Fuzzy Sliding Mode Control that step 3 obtains the most again to Device, adaptive fuzzy sliding mode controller is obtained controlled quentity controlled variable, and is exported PWM drive signal to the amplification of IGBT isolated drive circuit；

Step 5: the signal that drives after amplification controls the dutycycle of full-bridge inverter, when output voltage is higher than setting value, Reduce the service time of IGBT isolated drive circuit, reduce dutycycle；When output voltage is less than setting value, increase IGBT isolation The service time of drive circuit, rising high duty ratio, thus control turning on and off of switching tube, regulation output voltage is steady.

The feature of the present invention also resides in,

Step 2 therein sets up model according to controlled device, it is thus achieved that the key parameter in model, specifically according to following steps Implement:

The input voltage of definition wave filter is V_LC-in, input current is I_LC-in, output voltage is V_o, output electric current is I_o；

The transmission function of output filter is:

$H_f=\frac{V_o}{V_{LC-in}}=\frac{R//\frac{1}{C_{o}s}}{R//\frac{1}{C_{o}s}+L_{f}s}=\frac{1}{L_f{C}_o{s}^2+\frac{L_f}{R}s+1},$

When load is for R, the input impedance of output filter is:

$Z_f=\frac{V_{LC-in}}{I_{LC-in}}=\frac{I_{LC-in}\×(L_{f}s+R//\frac{1}{C_{o}s})}{I_{LC-in}}=L_{f}s+R//\frac{1}{C_{o}s}=\frac{R+L_{f}s+L_f{C}_o{\mathrm{Rs}}^2}{{\mathrm{RC}}_o{s}^2+1},$

When load is for R, the output impedance of output filter is:

$Z_n=\frac{V_o}{I_o}=\frac{V_o}{\frac{V_o}{R}+\frac{V_o}{1/C_{o}s}+\frac{V_o}{L_{f}s}}=\frac{1}{\frac{1}{R}+C_{o}s+\frac{1}{L_{f}s}}=\frac{L_{f}s}{L_f{C}_o{s}^2+\frac{L_f}{R}s+1},$

The transmission function of phase shifted full bridge ZVS converter is:

$G_{vd}=H_f{\mathrm{nV}}_{DC}\frac{Z_f}{Z_f+R_d},$

Try to achieve:

$G_{vd}\left(s\right)=\frac{{\mathrm{nV}}_{DC}}{L_f{C}_o{s}^2+(\frac{L_f}{R}+R_d{C}_o)s+\frac{R_d}{R}+1},$

Wherein, n is the no-load voltage ratio of transformator, V_DCFor input voltage, L_fFor load inductance, C_oFor load capacitance, R_dFor former limit electricity Crushing loses the ratio with load current, and R is load resistance.

Step 3 therein, according to the modelling adaptive fuzzy sliding mode controller in step 2, determines in switching function s Coefficient and control law, obtain closed-loop control system, specifically according to following steps implement:

If fuzzy system is made up of the fuzzy rule of following IF-THEN form:

${\mathrm{\ϵ}}^i=IF{x}_{1}is{A}_1^{j}and...x_{n}is{A}_n^{j}THENyis{B}^j,$

Use product inference machine, the average defuzzifier of monodrome fuzzy device and center, then fuzzy system is output as:

$y\left(x\right)=\frac{\underset{j=1}{\overset{m}{\Σ}}{y}^j\left(\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)}{\underset{j=1}{\overset{m}{\Σ}}\left(\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)},$

Wherein,For x_iMembership function；

Introducing vector ξ (x), above formula becomes:

Y (x)=θ^Tξ (x),

Wherein, θ=[y¹…y^m]^T, ξ (x)=[ξ¹(x)…ξ^m(x)]^T；

$\mathrm{\ξ}\left(x\right)=\frac{\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\left(x_i\right)}{\underset{j=1}{\overset{m}{\Σ}}\left(\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)},$

Use fuzzy system to approach ε, then ds (k) becomes:

$ds\left(k\right)=-\widehat{\mathrm{\ϵ}}Tsgn\left(s\right(k\left)\right)-qTs\left(k\right),$

$\widehat{\mathrm{\ϵ}}\left(x\right|{\mathrm{\θ}}_{\mathrm{\ϵ}})={{\mathrm{\θ}}_{\mathrm{\ϵ}}}^T\mathrm{\ξ}\left(x\right),$

ξ (x) is fuzzy vector, parameter θ_ε ^TChanging according to adaptive law, design adaptive law is:

${\stackrel{\·}{\mathrm{\θ}}}_{\mathrm{\ϵ}}=-r_{1}s\mathrm{\ξ}\left(x\right)u,$

Definition Lyapunove function:

Wherein r₁For normal number, then:

Wherein,

By formula

Substitute into formula u (k)=(C_eB)^-1=(C_eR(k+1)-C_eAx (k)-s (k)-ds (k)):

$\stackrel{\·}{V}=-k\left|s\right|+s\mathrm{\ω},$

$\stackrel{\·}{V}\≤0,$

Use continuous function S_δReplacement sgn (s):

$S_{\mathrm{\δ}}=\frac{s}{\left|s\right|+\mathrm{\δ}},$

δ=δ₀+δ₁| | e | |,

Wherein, δ₀And δ₁It is two normal numbers；B^jRepresent the fuzzy set of output language variable y；μ represents membership function；s K () represents sliding-mode surface equation；K represents that kth controls the cycle；E represents deviation；U (k) represents discrete control based on exponential approach rate System rule.

Step 4 adaptive fuzzy sliding mode controller therein obtains controlled quentity controlled variable, specifically implements according to following steps:

Step 1): utilize the d. c. voltage signal obtained and setting value to do difference, obtain the derivative of deviation e and deviationGeneration EnterTry to achieve sliding-mode surface equation s；

Step 2): by sliding-mode surface equation s and the derivative of sliding-mode surface equationSubstitute into equation u (k)=(C of control rate u_eB)^-1 =(C_eR(k+1)-C_eAx (k)-s (k)-ds (k)),

Wherein ds (k)=-ε Tsgn (s (k))-qTs (k), tries to achieve control rate u；

Step 3): by sliding-mode surface equation s and the derivative of sliding-mode surface equationTransport via adaptive fuzzy sliding mode controller (3) Calculate, obtain the size of auto-adaptive parameter ε, substitute into control rate

U (k)=(C_eB)^-1=(C_eR(k+1)-C_eAx (k)-s (k)-ds (k)),

Wherein ds (k)=-ε Tsgn (s (k))-qTs (k), thus regulate the value of control rate u；

Step 4): the output valve of control rate u is substituted into system discrete state equations x (the k+1)=Ax (k) of modeling gained+ Bu(k),x∈Rⁿ,u∈Rⁿ, thus regulation voltage level in real time, and export PWM drive signal to the amplification of IGBT isolated drive circuit.

The invention has the beneficial effects as follows, utilize Sliding mode variable structure control to have the strongest to systematic parameter perturbation and external disturbance The advantage of robustness, improves dynamic characteristic and the robustness of the system when reference voltage change and load disturbance, utilizes certainly simultaneously Adaptive fuzzy control method overcomes buffeting present in sliding formwork control.This Adaptive Fuzzy Control controls to combine with sliding formwork Switching Power Supply control method according to switch duty cycle, dynamically error is modified, dynamically compensates for the big of controlled quentity controlled variable Little, be conducive to ensureing that system is moved along diverter surface approx, reduce systematic steady state error, reach to weaken or even eliminate high frequency and tremble Dynamic purpose, shortens settling time, improves the dynamic quality of system.

Accompanying drawing explanation

Fig. 1 is the structural representation of the control system of Cz monocrystal stove high frequency switch power of the present invention；

Fig. 2 is the phase-shifting full-bridge ZVZCS changer small-signal model used in the inventive method step 2；

Fig. 3 is the fuzzy sliding mode tracking control fundamental diagram in the inventive method step 3 for high frequency switch power；

Fig. 4 is that in the inventive method, Fuzzy Sliding Model Controller realizes block diagram；

Fig. 5 is the flow chart of control method of the present invention；

The Adaptive Fuzzy Sliding Mode Control of system start-up and cunning when Fig. 6 is that in the embodiment of the present invention, voltage setting value is 60V Mould controls response wave shape comparison diagram, and wherein, upper figure is Adaptive Fuzzy Sliding Mode Control result figure, and figure below is that sliding formwork controls result Figure；

Adaptive fuzzy sliding mode control when Fig. 7 is that in the embodiment of the present invention, duty cycle property changes between 5 Ω and 10 Ω System controls response wave shape comparison diagram with sliding formwork, and wherein, upper figure is Adaptive Fuzzy Sliding Mode Control result figure, and figure below is sliding formwork control Result figure；

Adaptive fuzzy when Fig. 8 is that in the embodiment of the present invention, voltage setting value periodically changes between 60V and 80V is sliding Mould controls to control response wave shape comparison diagram with sliding formwork, and wherein, upper figure is Adaptive Fuzzy Sliding Mode Control result figure, and figure below is sliding formwork Control result figure；

Fig. 9 is that in the embodiment of the present invention, inductance value is respectively 1mH, Adaptive Fuzzy Sliding Mode Control when 3mH, 5mH and cunning Mould controls response wave shape comparison diagram, and wherein, upper figure is Adaptive Fuzzy Sliding Mode Control result figure, and figure below is that sliding formwork controls result Figure；

The regulation process schematic of auto-adaptive parameter ε when Figure 10 is that in the embodiment of the present invention, setting value is 60V.

In figure, 1.IGBT isolated drive circuit, 2.PWM generation module, 3. adaptive fuzzy sliding mode controller, 4. simulation letter Number isolation gather change-over circuit, 5. wave digital lowpass filter.

Detailed description of the invention

Below in conjunction with detailed description of the invention, the present invention is described in detail.

The load of Cz monocrystal stove and feature, power main circuit topological structure and major power device parameters for determining are Determine；The structure of controller and the control algolithm of employing determine the performance of whole power supply.Cz monocrystal stove of the present invention is high Frequently the structure of the control system of Switching Power Supply, as it is shown in figure 1, include the analog signal isolating that is sequentially connected with gather change-over circuit 4, Wave digital lowpass filter 5, adaptive fuzzy sliding mode controller 3, PWM generation module 2 and IGBT isolated drive circuit 1.Simulation letter Number isolation gathers change-over circuit 4, being connected respectively of IGBT isolated drive circuit 1, analog signal isolating with power section main circuit Gather change-over circuit 4 to be connected with LED display module, keyboard and host computer also by soft-core processor.

Wherein analog signal isolating gathers change-over circuit 4 and mainly realizes the collection of power supply output, provides feedback for controller Information；Power inverter part uses the mode of phase-shifting full-bridge, and PWM generation module 2 produces 4 tunnel phase-shift PWM ripples, according to controller Export and exported by the voltage controlling dutycycle change power supply final.PWM is amplified to ensure IGBT by IGBT isolated drive circuit 1 Reliable turn-off, protect simultaneously and use anti-IGBT power device here.These are the peripheral slave parts of controller, once these After designing, the final response performance of power supply depends primarily on designed control algolithm.

The control method of Cz monocrystal stove high frequency switch power of the present invention, as shown in Figure 5: specifically real according to following steps Execute:

Step 1: Switching Power Supply power section main circuit importation incoming transport voltage, through front-end filtering rectification, entirely Carry out voltage transformation after bridge reversals and high frequency transformer effect, after the rectifying and wave-filtering of rear end, obtained exporting DC voltage；

Step 2: set up model according to controlled device, it is thus achieved that the key parameter in model, including input voltage V_DC, load electricity Sense L_f, load capacitance C_o, load resistance R, original edge voltage loses the ratio R with load current_d；

Specifically implement according to following steps:

Phase-shifting full-bridge power supply ZVZCS changer is Buck code converter, and its small-signal model is as shown in Figure 2.This circuit is deposited At duty-cycle loss, its equivalence dutycycle is:

$D_{eff}=D-\frac{2{\mathrm{nL}}_r}{V_{DC}}\[2I_f-\frac{V_o}{L_f}(1-D)\frac{T}{2}\]---\left(1\right)$

Visible D_effBy input voltage V_DC, former Buck circuit dutycycle D and load current I_fImpact, so its small-signal There are three kinds of disturbances in model, its size is respectively as follows:

$\widehat{d_d}=(1-\frac{L_r}{L_f}{n}^2{D}_{eff})\hat{d}$

The input voltage of definition wave filter is V_LC-in, input current is I_LC-in, output voltage is V_o, output electric current is I_o。

The transmission function of output filter is:

$H_f=\frac{V_o}{V_{LC-in}}=\frac{R//\frac{1}{C_{o}s}}{R//\frac{1}{C_{o}s}+L_{f}s}=\frac{1}{L_f{C}_o{s}^2+\frac{L_f}{R}s+1}---\left(3\right)$

When load is for R, the input impedance of output filter is:

$Z_f=\frac{V_{LC-in}}{I_{LC-in}}=\frac{I_{LC-in}\×(L_{f}s+R//\frac{1}{C_{o}s})}{I_{LC-in}}=L_{f}s+R//\frac{1}{C_{o}s}=\frac{R+L_{f}s+L_f{C}_o{\mathrm{Rs}}^2}{{\mathrm{RC}}_o{s}^2+1}---\left(4\right)$

When load is for R, the output impedance of output filter is:

$Z_n=\frac{V_o}{I_o}=\frac{V_o}{\frac{V_o}{R}+\frac{V_o}{1/C_{o}s}+\frac{V_o}{L_{f}s}}=\frac{1}{\frac{1}{R}+C_{o}s+\frac{1}{L_{f}s}}=\frac{L_{f}s}{L_f{C}_o{s}^2+\frac{L_f}{R}s+1}---\left(5\right)$

Therefore, from controlled quentity controlled variable d to output V_oFrom the point of view of, the transmission function of phase shifted full bridge ZVS converter is:

$G_{vd}=H_f{\mathrm{nV}}_{DC}\frac{Z_f}{Z_f+R_d}---\left(6\right)$

Formula (3) (4) substitution (6) formula is tried to achieve:

$G_{vd}\left(s\right)=\frac{{\mathrm{nV}}_{DC}}{L_f{C}_o{s}^2+(\frac{L_f}{R}+R_d{C}_o)s+\frac{R_d}{R}+1}---\left(7\right)$

Wherein, n is the no-load voltage ratio of transformator, V_DCFor input voltage, L_fFor load inductance, C_oFor load capacitance, R_dFor former limit electricity Crushing loses the ratio with load current, and R is load resistance.

After the model obtaining controlled device, by the control method of adaptive fuzzy sliding mode, it is possible to realize height Frequently the output voltage control of Switching Power Supply main circuit.

Step 3: according to the modelling adaptive fuzzy sliding mode controller 3 in step 2, determines and in switching function s is Number and control law, obtain closed-loop control system；

Specifically implement according to following steps:

Adaptive Fuzzy Sliding Mode Control is to control to combine by Adaptive Fuzzy Control and traditional sliding formwork, and by the two Advantage is combined closely.Fuzzy sliding mode tracking control has two advantages, and one is to control target to transfer sliding formwork function to from tracking error, only Control to be applied makes sliding formwork function s be zero, and tracking error is by progressive arrival zero point.Two be for second order more than high order system, In conventional control, input should beAnd the input of fuzzy sliding mode tracking controlAll the time it is two-dimentional, such as Fig. 3 institute Show.The meaning of fuzzy control is its soft and smooth control signal, and chattering phenomenon that general sliding formwork occur has been alleviated or avoided.

1. sliding mode controller design

If discrete system state equation is as follows:

X (k+1)=Ax (k)+Bu (k), x ∈ Rⁿ,u∈Rⁿ

(8)

Position command is r (k), the derivative dr (k), R=[r (k), dr (k)] of position command, R₁=[r (k+1), dr (k +1)]。

R (k) and r (k+1) uses the method for linear extrapolation to be predicted:

R (k+1)=2r (k)-r (k-1), dr (k+1)=2dr (k)-dr (k-1)

(9)

Switching function is

S (k)=C_e[r(k)-x(k),dr(k)-dx(k)]^T

(10)

Wherein C_e=[c, 1].

Discrete control rate based on exponential approach rate:

U (k)=(C_eB)^-1=(C_eR(k+1)-C_eAx(k)-s(k)-ds(k))

(11)

Wherein ds (k)=-ε Tsgn (s (k))-qTs (k).

Under conditions of the sampling time is fixing, ε value determines the amplitude that controller is buffeted.

Define a Lyaounov function:

$V=\frac{1}{2}{s}^2---\left(12\right)$

For second-order system, haveThen have:

$\stackrel{\·}{V}=s\stackrel{\·}{s}$

$\left(13\right)$

Formula (11) is brought formula (13) into, whereinProvableSo the stability of sliding formwork control law obtains Card.

2. adaptive fuzzy sliding mode controller design

If the ε in formula (11) is difficult to determine, fuzzy system can be usedReplace ε, it is achieved Adaptive Fuzzy Sliding Mode Control.

If fuzzy system is made up of the fuzzy rule of following IF-THEN form:

${\mathrm{\ϵ}}^i=IF{x}_{1}is{A}_1^{j}and...x_{n}is{A}_n^{j}THENyis{B}^j$

Use product inference machine, the average defuzzifier of monodrome fuzzy device and center, then fuzzy system is output as:

$y\left(x\right)=\frac{\underset{j=1}{\overset{m}{\Σ}}{y}^j\left(\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)}{\underset{j=1}{\overset{m}{\Σ}}\left(\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)}---\left(14\right)$

Wherein,For x_iMembership function.

Introducing vector ξ (x), formula (14) becomes:

Y (x)=θ^Tξ(x)

(15)

Wherein, θ=[y¹…y^m]^T, ξ (x)=[ξ¹(x)…ξ^m(x)]^T。

$\mathrm{\ξ}\left(x\right)=\frac{\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\left(x_i\right)}{\underset{j=1}{\overset{m}{\Σ}}\left(\underset{i=1}{\overset{n}{\Π}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)}---\left(16\right)$

In actual control, ε is often difficult to determine, control rate (11) is difficult to, and uses fuzzy system to approach ε, then ds K () becomes:

$ds\left(k\right)=-\widehat{\mathrm{\ϵ}}Tsgn\left(s\right(k\left)\right)-qTs\left(k\right)---\left(17\right)$

$\widehat{\mathrm{\ϵ}}\left(x\right|{\mathrm{\θ}}_{\mathrm{\ϵ}})={{\mathrm{\θ}}_{\mathrm{\ϵ}}}^T\mathrm{\ξ}\left(x\right)---\left(18\right)$

ξ (x) is fuzzy vector, parameter θ_ε ^TChange according to adaptive law.Design adaptive law is:

${\stackrel{\·}{\mathrm{\θ}}}_{\mathrm{\ϵ}}=-r_{1}s\mathrm{\ξ}\left(x\right)u---\left(19\right)$

Definition Lyapunove function:

Wherein r₁For normal number, then:

Wherein,Formula (20) is substituted into control rate (11) obtain:

$\stackrel{\·}{V}=-k\left|s\right|+s\mathrm{\ω}---\left(22\right)$

Theoretical according to fuzzy close, it is the least that adaptive fuzzy system can realize approximate error ω.Therefore:

$\stackrel{\·}{V}\≤0$

$\left(23\right)$

In order to reduce buffeting, use continuous function S_δReplace sgn (s):

$S_{\mathrm{\δ}}=\frac{s}{\left|s\right|+\mathrm{\δ}}---\left(24\right)$

$\mathrm{\δ}={\mathrm{\δ}}_0+{\mathrm{\δ}}_1\left|\right|e\left|\right|---\left(25\right)$

Wherein, δ₀And δ₁It is two normal numbers, so designed adaptive law is stable；B^jRepresent output language variable y's Fuzzy set；μ represents membership function；S (k) represents sliding-mode surface equation；K represents that kth controls the cycle；E represents deviation；U (k) table Show discrete control law based on exponential approach rate.

In order to reach the real-time of higher arithmetic speed and control, native system realizes above-mentioned calculation on FPGA hardware platform Using three class pipeline structure during method, be that fuzzy inputing method, fuzzy reasoning output and sliding formwork control respectively, three links are entered simultaneously Row operation, reaches the maximum efficiency of algorithm.

The membership values of variable typically uses look-up table to obtain, and traditional look-up table is i.e. to store each opinion in FPGA respectively The degree of membership of the corresponding each obscuring element of field element, so needs more FPGA ROM resource, and needs after inquiry often The degree of membership that individual obscuring element is corresponding carries out record, wastes FPGA resource, affects the operational efficiency of program.The present invention proposes relatively For direct degree of membership query method, use Triangleshape grade of membership function here, owing to each domain element degree of membership more than 0 is 0.5 or 1, the most at most it is under the jurisdiction of two fuzzy languages, therefore for the ROM cell of each domain element design 6Bit (2*3Bit) Storing it and be subordinate to situation, represent domain language in 7 by triad (000～110), XXX is represented as sky, i.e. this value is only subordinate to Belong to front 3Bit.Domain element value can directly obtain it as lookup address and be subordinate to language and membership function value, the most both saves Save resource and in turn simplify search procedure.

The input s of fuzzy controller,Being two variablees, each variable comprises 7 obscuring element, therefore, rule of inference Being 49, rule list uses the mode of look-up table to design equally, for taking minimum resource, selects the ROM of 49*4bit as rule Then table, address wire is 6, and high 3 is the fuzzy language value of input quantity S, and low 3 areFuzzy language value.Due to obscuring element Use the binary system of 000～110 to represent successively in a program, therefore complete the inquiry of fuzzy variable degree of membership at previous stage streamline After, directly it is subordinate to element as address using obtain, corresponding reasoning can be found in ROM to export.

The process that realizes of sliding mode controller is as shown in Figure 4.Input is deviation e and deviation derivativeAfter constituting switching function s Output it, take equation s and the derivative thereof of switching functionInput as fuzzy controller, fuzzy controller output controlled quentity controlled variable, The controlled quentity controlled variable returned and deviation e and deviation derivativeThe switching function s that must make new advances after computing, dutycycle is updated by lasting computing S control, be finally reached control switching tube and opened shutoff, made system output voltage stable in setting value.

Step 4: analog signal isolating gathers the d. c. voltage signal of change-over circuit 4 acquisition step 1 output, as feedback letter Number giving controller part, the adaptive fuzzy sliding mode controller 3 that controller part utilizes step 3 to obtain obtains controlled quentity controlled variable, tool Body calculates process:

1. the magnitude of voltage utilizing collecting part to obtain does difference with setting value, obtains the derivative of deviation e and deviationSubstitute intoTry to achieve the equation of slipform design.

2. by sliding-mode surface equation s and the derivative of sliding-mode surface equationSubstitute into the equation of control rate u, try to achieve control rate u.

3. by sliding-mode surface equation s and the derivative of sliding-mode surface equationVia fuzzy controller computing, obtain auto-adaptive parameter ε Size, regulation control rate u value.

4. by the system discrete state equations of the output valve substitution modeling gained of control rate u, thus regulation voltage level in real time, And export PWM drive signal and amplify to IGBT isolated drive circuit 1；

Step 5: the signal that drives after amplification controls the dutycycle of full-bridge inverter.When output voltage is higher than setting value, Reduce the service time of IGBT isolated drive circuit 1, reduce dutycycle；When output voltage less than setting value time, increase IGBT every From the service time of drive circuit 1, rising high duty ratio, thus control turning on and off of switching tube, regulation output voltage is steady, Reach to regulate electric power output voltage or the purpose of power.

Embodiment

In order to verify the effect of above-mentioned adaptive fuzzy sliding mode controller, for TDR-100 type single crystal growing furnace full-bridge inverting High frequency switch power, parameter is chosen as follows: switching function isWherein, c=4.5, q=50 in control rate.Power supply is defeated Enter voltage V=380V, switching frequency f=20kHz.Resistance 5 Ω of load, load inductance is 1mH.

Fig. 6 is that Adaptive Fuzzy Sliding Mode Control controls the results contrast result figure when voltage setting value is 60V with sliding formwork.Its In, upper figure is fuzzy sliding mode tracking control result figure, and figure below is that sliding formwork controls result figure.Adaptive Fuzzy Sliding Mode Control as seen from the figure It is 0.005s that mode arrives the stable time, and it is 0.015s that sliding formwork control mode arrives the stable time, and substantially can see Go out sliding formwork to control to carve on startup to also exist than more serious buffeting.

Fig. 7 is Adaptive Fuzzy Sliding Mode Control and sliding formwork controls when the change between 5 Ω and 10 Ω of the duty cycle property, Fuzzy sliding mode tracking control controls result figure with sliding formwork.Wherein, upper figure is fuzzy sliding mode tracking control result figure, and figure below is that sliding formwork controls result Figure.As seen from the figure in 0.04s and the 0.08s moment, setting load value change saltus step, sliding formwork controls response wave shape and occurs bigger Fluctuation, reaches steady statue again through 0.002s, and fuzzy sliding mode tracking control response wave shape then fluctuates less, through 0.001s again Reach steady statue.

Fig. 8 be voltage setting value periodically between 60V and 80V during change, fuzzy sliding mode tracking control controls result with sliding formwork Figure.Wherein, upper figure is fuzzy sliding mode tracking control result figure, and figure below is that sliding formwork controls result figure.Can be seen that when 0.04s and 0.08 Carving, voltage setting value changes, and fuzzy sliding mode tracking control reaches rapidly stable after 0.002s again, sliding formwork control and regulation time and cunning Mould control and regulation time phase difference is little, but shake is stronger.

Fig. 9 is that inductance value is respectively 1mH, and when 3mH, 5mH, Adaptive Fuzzy Sliding Mode Control and sliding formwork control comparison diagram and control Startup response wave shape.Wherein, upper figure is fuzzy sliding mode tracking control result figure, and figure below is that sliding formwork controls result figure.Figure can be seen Going out two kinds of control methods when inductance value increases, response speed is slack-off.But fuzzy sliding mode tracking control is compared to sliding formwork control, response Speed wants very fast, and amplitude of buffeting is less, and system remains in that good performance.

Figure 10 describes under modified fuzzy sliding mode controlling method, and setting value is 60V, the regulation process of auto-adaptive parameter ε, starter system Oscillation phase, parameter ε carries out Automatic adjusument, reaches steady operation moment ε in system and reaches stationary value too, terminates regulation Process.

By above-mentioned comparing result it can be seen that Adaptive Fuzzy Sliding Mode Control compared to fuzzy sliding mode tracking control for, knot Close strong adaptability that sliding formwork controls and fuzzy control need not the feature of system Exact Equation.Buffet and reduce, start time contracting Short, simultaneously under the catastrophe of system load and reference voltage, regulating time is shorter, and overshoot is relatively low, additionally in fuzzy cunning Under mould control method, the ripple of system waveform is less, so the robustness of control method is stronger.Situation in circuit parameter disturbance Under, after being attained by steady statue, and arrival stable state, circuit parameter disturbance is had invariance.

Claims (4)

1. The control method of 1.Cz monocrystal stove high frequency switch power, it is characterised in that use Cz monocrystal stove HF switch The control system of power supply, the structure of described control system is: include that the analog signal isolating being sequentially connected with gathers change-over circuit (4), wave digital lowpass filter (5), adaptive fuzzy sliding mode controller (3), PWM generation module (2) and IGBT isolation drive electricity Road (1), described analog signal isolating gathers change-over circuit (4), IGBT isolated drive circuit (1) electricity main with power section respectively Road connects, described analog signal isolating gather change-over circuit (4) by soft-core processor and LED display module, keyboard and on Position machine connects；Described control method, specifically implements according to following steps:

   Step 1: Switching Power Supply power section main circuit importation incoming transport voltage, through front-end filtering rectification, full-bridge is inverse Carry out voltage transformation after change process and high frequency transformer effect, after the rectifying and wave-filtering of rear end, obtained exporting DC voltage；

   Step 2: set up model according to controlled device, it is thus achieved that the key parameter in model: input voltage V_DC, load inductance L_f, negative Carry electric capacity C_o, load resistance R, original edge voltage loses the ratio R with load current_d；

   Step 3: according to the modelling adaptive fuzzy sliding mode controller (3) in step 2, determine the coefficient in switching function s And control law, obtain closed-loop control system；

   Step 4: analog signal isolating gathers the d. c. voltage signal of change-over circuit (4) acquisition step 1 output, as feedback signal Pass to the wave digital lowpass filter (5) of controller part, send the Adaptive Fuzzy Sliding Mode Control that step 3 obtains the most again to Device (3), adaptive fuzzy sliding mode controller (3) is obtained controlled quentity controlled variable, and is exported PWM drive signal to IGBT isolated drive circuit (1) amplify；

   Step 5: the signal that drives after amplification controls the dutycycle of full-bridge inverter, when output voltage is higher than setting value, reduces The service time of IGBT isolated drive circuit (1), reduce dutycycle；When output voltage is less than setting value, increase IGBT isolation The service time of drive circuit (1), rising high duty ratio, thus control turning on and off of switching tube, regulation output voltage is steady.
2. The control method of Cz monocrystal stove high frequency switch power the most according to claim 1, it is characterised in that described Step 2 sets up model according to controlled device, it is thus achieved that the key parameter in model, specifically implements according to following steps:

   The input voltage of definition wave filter is V_LC-in, input current is I_LC-in, output voltage is V_o, output electric current is I_o；

   The transmission function of output filter is:

   $H_f=\frac{V_o}{V_{LC-in}}=\frac{R//\frac{1}{C_{o}s}}{R//\frac{1}{C_{o}s}+L_{f}s}=\frac{1}{L_f{C}_o{s}^2+\frac{L_f}{R}s+1},$

   When load is for R, the input impedance of output filter is:

   $Z_f=\frac{V_{LC-in}}{I_{LC-in}}=\frac{I_{LC-in}\×(L_{f}s+R//\frac{1}{C_{o}s})}{I_{LC-in}}=L_{f}s+R//\frac{1}{C_{o}s}=\frac{R+L_{f}s+L_f{C}_o{\mathrm{Rs}}^2}{{\mathrm{RC}}_o{s}^2+1},$

   When load is for R, the output impedance of output filter is:

   $Z_n=\frac{V_o}{I_o}=\frac{V_o}{\frac{V_o}{R}+\frac{V_o}{1/C_{o}s}+\frac{V_o}{L_{f}s}}=\frac{1}{\frac{1}{R}+C_{o}s+\frac{1}{L_{f}s}}=\frac{L_{f}s}{L_f{C}_o{s}^2+\frac{L_f}{R}s+1},$

   The transmission function of phase shifted full bridge ZVS converter is:

   $G_{vd}=H_f{\mathrm{nV}}_{DC}\frac{Z_f}{Z_f+R_d},$

   Try to achieve:

   $G_{vd}\left(s\right)=\frac{{\mathrm{nV}}_{DC}}{L_f{C}_o{s}^2+(\frac{L_f}{R}+R_d{C}_o)s+\frac{R_d}{R}+1},$

   Wherein, n is the no-load voltage ratio of transformator, V_DCFor input voltage, L_fFor load inductance, C_oFor load capacitance, R_dDamage for original edge voltage Losing the ratio with load current, R is load resistance.
3. The control method of Cz monocrystal stove high frequency switch power the most according to claim 1, it is characterised in that described Step 3, according to the modelling adaptive fuzzy sliding mode controller (3) in step 2, determines the coefficient in switching function s and control Rule, obtains closed-loop control system, specifically implements according to following steps:

   If fuzzy system is made up of the fuzzy rule of following IF-THEN form:

   ${\mathrm{\ϵ}}^i=IF{x}_{1}is{A}_1^{j}and...x_{n}is{A}_n^{j}THENyis{B}^j,$

   Use product inference machine, the average defuzzifier of monodrome fuzzy device and center, then fuzzy system is output as:

   $y\left(x\right)=\frac{\underset{j=1}{\overset{m}{\Σ}}{y}^j\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μA}}_i^j\left(x_i\right)\right)}{\underset{j=1}{\overset{m}{\Σ}}\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μA}}_i^j\left(x_i\right)\right)},$

   Wherein,For x_iMembership function；

   Introducing vector ξ (x), above formula becomes:

   Y (x)=θ^Tξ (x),

   Wherein, θ=[y¹…y^m]^T, ξ (x)=[ξ¹(x)…ξ^m(x)]^T；

   $\mathrm{\ξ}\left(x\right)=\frac{\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μA}}_i^j\left(x_i\right)}{\underset{j=1}{\overset{m}{\mathrm{\Π}}}\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μA}}_i^j\right(x_i\left)\right)},$

   Use fuzzy system to approach ε, then ds (k) becomes:

   $ds\left(k\right)=-\widehat{\mathrm{\ϵ}}Tsgn\left(s\left(k\right)\right)-qTs\left(k\right),$

   $\widehat{\mathrm{\ϵ}}\left(x\right|{\mathrm{\θ}}_{\mathrm{\ϵ}})={{\mathrm{\θ}}_{\mathrm{\ϵ}}}^T\mathrm{\ξ}\left(x\right),$

   ξ (x) is fuzzy vector, parameter θ_ε ^TChanging according to adaptive law, design adaptive law is:

   ${\stackrel{\·}{\mathrm{\θ}}}_{\mathrm{\ϵ}}=-r_{1}s\mathrm{\ξ}\left(x\right)u,$

   Definition Lyapunove function:

   Wherein r₁For normal number, then:

   Wherein,

   By formula

   Substitute into formula u (k)=(C_eB)^-1=(C_eR(k+1)-C_eAx (k)-s (k)-ds (k)):

   $\stackrel{\·}{V}=-k\left|s\right|+s\mathrm{\ω},$

   $\stackrel{\·}{V}\≤0,$

   Use continuous function S_δReplacement sgn (s):

   $S_{\mathrm{\δ}}=\frac{s}{\left|s\right|+\mathrm{\δ}},$

   δ=δ₀+δ₁| | e | |,

   Wherein, δ₀And δ₁It is two normal numbers；B^jRepresent the fuzzy set of output language variable y；μ represents membership function；S (k) table Show sliding-mode surface equation；K represents that kth controls the cycle；E represents deviation；U (k) represents discrete control law based on exponential approach rate.
4. The control method of Cz monocrystal stove high frequency switch power the most according to claim 1, it is characterised in that described Step 4 adaptive fuzzy sliding mode controller (3) obtains controlled quentity controlled variable, specifically implements according to following steps:

   Step 1): utilize the d. c. voltage signal obtained and setting value to do difference, obtain the derivative of deviation e and deviationSubstitute intoTry to achieve sliding-mode surface equation s；

   Step 2): by sliding-mode surface equation s and the derivative of sliding-mode surface equationSubstitute into equation u (k)=(C of control rate u_eB)^-1= (C_eR(k+1)-C_eAx (k)-s (k)-ds (k)),

   Wherein ds (k)=-ε Tsgn (s (k))-qTs (k), tries to achieve control rate u；

   Step 3): by sliding-mode surface equation s and the derivative of sliding-mode surface equationVia adaptive fuzzy sliding mode controller (3) computing, ask Go out the size of auto-adaptive parameter ε, substitute into control rate

   U (k)=(C_eB)^-1=(C_eR(k+1)-C_eAx (k)-s (k)-ds (k)),

   Wherein ds (k)=-ε Tsgn (s (k))-qTs (k), thus regulate the value of control rate u；

   Step 4): the output valve of control rate u is substituted into system discrete state equations x (k+1)=Ax (the k)+Bu of modeling gained (k),x∈Rⁿ,u∈Rⁿ, thus regulation voltage level in real time, and export PWM drive signal to IGBT isolated drive circuit (1) amplification.