CN103309364B - Based on the marine biological enzyme Separation of Solid and Liquid flow controller of Fuzzy Sliding Mode Variable Structure - Google Patents

Abstract

The invention discloses a kind of marine biological enzyme Separation of Solid and Liquid flow controller based on Fuzzy Sliding Mode Variable Structure, belong to marine biological enzyme Separation of Solid and Liquid flow control technique field.The present invention is by DSP module, sliding formwork control module, the part such as fuzzy control model and flow sensor composition, next position command r(k by DSP module delivery rate), flow sensor detects and exports the position signalling x(k of present flow rate), after a series of data processing, export control signal u(k).The solid-liquid separation system that the present invention is directed to fermentation of marine biologic enzyme liquid has large time delay, non-linear, time variation and cannot draw the features such as mathematical models, traditional fuzzy control is combined with Sliding mode variable structure control, possess both advantages, both the advantage of conventional fuzzy control had been remained, strengthen again the stability of system, reduce the chattering phenomenon that sliding formwork controls simultaneously.

Description

Based on the marine biological enzyme Separation of Solid and Liquid flow controller of Fuzzy Sliding Mode Variable Structure

Technical field

The invention belongs to marine biological enzyme Separation of Solid and Liquid flow control technique field, more precisely, the present invention relates to the application of a kind of Fuzzy Sliding Mode Variable Structure technology in the flow control of marine biological enzyme Separation of Solid and Liquid.

Background technology

Sedimentation is centrifugal is one important process in current fermentation of marine biologic enzyme, and wherein feed rate is the important parameter affecting centrifugal efficiency.If inlet amount is excessive, axial flow velocity is too fast, and comparatively fine particle residence time in rotary drum will be less than sedimentation required time, then can not be separated outside fine particle will go out rouse with liquid slime flux.As inlet amount is too small, though particle can be separated, velocity of separation is excessively slow, and efficiency is but too low.Experimentally learn, within the specific limits, the suitable change of flow is less on separation efficiency impact, and when flow, to be increased to certain limit separation efficiency lower.Therefore need flow to be maintained within a certain range in marine biological enzyme sedimentation centrifugal process.

In fluid mechanics, quality keeps the expression formula of homeostasis reason is continuity equation.As shown in Figure 1, in the inside of hydro-extractor, an infinitesimal is got in flow field, for axisymmetric condition, hoop rate of change is zero, can find out that in hydro-extractor, flow can change along with rotating speed, simultaneously because the factors such as sediment in practical operation also can cause flow in hydro-extractor to change, therefore controlling flow in hydro-extractor is that an optimum value has important practical usage.

Current China ocean enzyme Separation of Solid and Liquid flow control technique is want than also there is suitable gap with advanced country in the world, domestic general employing PID control technology controls flow, but traditional PID control works in this nonlinear system of marine biological enzyme Separation of Solid and Liquid flow control is not very good.

In recent years, Sliding mode variable structure control technology obtains in fields such as motor, robot, aviation, military affairs and pays close attention to widely.The mathematical model accuracy requirement of Sliding mode variable structure control to system is not high, has adaptivity completely to the uncertain parameter of system, Parameters variation, the uncertainty of mathematical description and the disturbance of external environment.But, need switch back and forth between different steering logics because sliding formwork controls to make system remain on motion on sliding manifolds, will easily cause the disadvantageous buffeting of system.

And fuzzy control is combined with Sliding mode variable structure control, it is relative to traditional Sliding mode variable structure control, can well solve the buffeting problem that sliding formwork controls, and can also improve control accuracy and response speed simultaneously.And fuzzy control being combined with Sliding mode variable structure control can also solve traditional fuzzy Controller gain variations and not rely on the model of controlled device but rely on the experimental knowledge of expert or operator thus be difficult to the problem of the stability of Guarantee control system.

Summary of the invention

The object of the invention is: for the deficiency in prior art existing for ocean enzyme Separation of Solid and Liquid flow control technique, a kind of marine biological enzyme Separation of Solid and Liquid flow controller based on Fuzzy Sliding Mode Variable Structure is provided, thus sliding formwork is controlled to combine with fuzzy control, to improve system stability, reliability and dynamic quality.

Specifically, the present invention adopts following technical scheme to realize: based on the marine biological enzyme Separation of Solid and Liquid flow controller of Fuzzy Sliding Mode Variable Structure, comprise DSP module, sliding formwork control module, fuzzy control model and flow sensor, wherein: described fuzzy control model is made up of obfuscation module, fuzzy reasoning module, sharpening module and base module; Described sliding formwork control module is made up of Integral Sliding Mode face mould block, sliding formwork Reaching Law module, equivalent controller module and switch controller module; The next position command r (k) of described DSP module delivery rate, described flow sensor detects and exports position signalling x (k) of present flow rate, and has error signal e (k)=r (k)-x (k).

When | e (k) | when being less than the threshold value ep preset, first using error signal e (k) and differential signal e ' (K) thereof as the input of Integral Sliding Mode face mould block to obtain switching function signal s (k), then produce switch-over control signal u through sliding formwork Reaching Law module to switch controller module on the one hand by switching function signal s (k) _sw, produce equivalent control signals u through equivalent controller module on the other hand _ep, and obtain control signal u (k)=u _sw+ u _ep; Simultaneously, using the input as fuzzy controller of switching function signal s (k) and differential signal s ' (k) thereof, successively through obfuscation module, fuzzy reasoning module and sharpening module, obtain fuzzy control output signal fs (k), then fuzzy control is outputed signal fs (k) and feed back to switch controller module; Finally control signal u (k) is exported to hydro-extractor system to realize flow control.

When | e (k) | when being not less than the threshold value ep preset, get control signal u (k)=u (k-1)+m, and control signal u (k) is exported to hydro-extractor system to realize flow control, wherein m is a limited constant value.

Above-mentioned switching function signal s (k)=ex (k), switch-over control signal u _sw=(CB) ^-1[-qTs (k)-ξ Tsgn (s (k))], equivalent control signals u _eq=-(CB) ^-1c (A mono-I) X (k), wherein A, B, C are sliding formwork control coefrficient, ξ=| fs (k) |, T is system communication cycle, O < q < 1/T.

Of the present inventionly to be further characterized in that: input s (k) of described fuzzy controller, s'(k and the fuzzy set exporting fs (k) are all taken as 3, are expressed as that { NB=is negative large, ZO=zero, PB=is honest }, the fuzzy rule adopted is following 9:

①If(s(k)isNB)and(s'(k)isNB)then(fs(k)isNB)

②If(s(k)isNB)and(s'(k)isZO)then(fs(k)isNB)

③If(s(k)isNB)and(s'(k)isPB)then(fs(k)isZO)

④If(s(k)isZO)and(s'(k)isNB)then(fs(k)isNB)

⑤If(s(k)isZO)and(s'(k)isZO)then(fs(k)isZO)

⑥If(s(k)isZO)and(s'(k)isPB)then(fs(k)isZO)

⑦If(s(k)isPB)and(s'(k)isNB)then(fs(k)isZO)

⑧If(s(k)isPB)and(s'(k)isZO)then(fs(k)isZO)

⑨If(s(k)isPB)and(s'(k)isPB)then(fs(k)isPB)。

Beneficial effect of the present invention is as follows: traditional design of Fuzzy Controller does not rely on the model of controlled device, but relies on the experimental knowledge of expert or operator, and it is not easy to self-teaching and the adjustment of controling parameters, is thus difficult to the stability of Guarantee control system.Marine biological enzyme Separation of Solid and Liquid flow controller based on Fuzzy Sliding Mode Variable Structure of the present invention, adopts fuzzy control to combine with Sliding mode variable structure control, improves the antijamming capability of control system, overcomes and causes control system unstable due to external disturbance; Control accuracy and response speed obtain corresponding raising; Fuzzy control rule greatly reduces, and system is more easy to operate; The buffeting problem simultaneously controlled due to the introducing sliding formwork of fuzzy control have also been obtained good weakening.

Accompanying drawing explanation

Fig. 1 is infinitesimal velocity analysis figure in marine biological enzyme solid-liquid separation centrifuge.

Fig. 2 is marine biological enzyme Separation of Solid and Liquid flow control schematic diagram.

Fig. 3 is the marine biological enzyme Separation of Solid and Liquid flow control schematic diagram based on Fuzzy Sliding Mode Variable Structure.

Fig. 4 is the marine biological enzyme Separation of Solid and Liquid flow control process figure based on Fuzzy Sliding Mode Variable Structure.

Embodiment

With reference to the accompanying drawings and in conjunction with example, the present invention is described in further detail.

Fig. 2 is hydro-extractor flow control block diagram of the present invention, flow sensor records flow signal after filtering in centrifugal chamber, simulating signal is converted into digital signal and is input to DSP module by Voltage to current transducer again, exports the centrifugal flow in control signal adjustment centrifugal chamber after DSP module process

Fig. 3 is the marine biological enzyme Separation of Solid and Liquid flow control schematic diagram that the present invention is based on Fuzzy Sliding Mode Variable Structure.Controller of the present invention is made up of parts such as DSP module, sliding formwork control module, fuzzy control model and flow sensors as seen from Figure 3.Flow sensor can adopt SW-600 flow sensor.Wherein fuzzy control model is made up of obfuscation module, fuzzy reasoning module, sharpening module and base module, and sliding formwork control module is made up of Integral Sliding Mode face mould block, sliding formwork Reaching Law module, equivalent controller module and switch controller module.The next position command r (k) of DSP module delivery rate, flow sensor detects and exports position signalling x (k) of present flow rate, and has error signal e (k)=r (k)-x (k).

Discrete sliding mode control error within the specific limits time, more easily set up sliding-mode surface, and control more accurate, therefore preset threshold value ep according to practical operation and control signal m, ep and m are all limited constant value, can determine according to engineering practice.

When | e (k) | when being less than the threshold value ep preset, first using error signal e (k) and differential signal e ' (k) thereof as the input of Integral Sliding Mode face mould block to obtain switching function signal s (k), then produce switch-over control signal U through sliding formwork Reaching Law module to switch controller module on the one hand by switching function signal s (k) _sw, produce equivalent control signals U through equivalent controller module on the other hand _eq, and obtain control signal u (k)=U _sw+ U _eq; Simultaneously, using switching function signal s (k) and differential signal s'(k thereof) as the input of fuzzy controller, successively through obfuscation module, fuzzy reasoning module and sharpening module, obtain fuzzy control output signal fs (k), then fuzzy control is outputed signal fs (k) and feed back to switch controller module; Finally control signal u (k) is exported to hydro-extractor system to realize flow control.

When | e (k) | when being not less than the threshold value ep preset, get control signal u (k)=u (k-1)+m, and control signal u (k) is exported to hydro-extractor system to realize flow control.

Specifically, the design of fuzzy sliding mode variable structure control of the present invention is as follows:

1, sliding mode controller design

Sampling x ₁ ^(k), x ₂ ^(k)... .x _n ^(k)for n the state variable in system k moment, u (k) is system k moment control signal, and state equation is:

$\left\{\begin{array}{c}{x_1}^{(k+1)}=a_{11}{x_1}^{\left(k\right)}+a_{12}{x_2}^{\left(k\right)}+\&CenterDot;\&CenterDot;\&CenterDot;a_{1n}{x_n}^{\left(k\right)}+{{b_1}^u}^{\left(k\right)}\\ {x_2}^{(k+1)}=a_{21}{x_1}^{\left(k\right)}+a_{22}{x_2}^{\left(k\right)}+\&CenterDot;\&CenterDot;\&CenterDot;a_{2n}{x_n}^{\left(k\right)}+{{b_2}^u}^{\left(k\right)}\\ \&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\\ {x_n}^{(k+1)}=a_{n1}{x_1}^{\left(k\right)}+a_{n2}{x_2}^{\left(k\right)}+\&CenterDot;\&CenterDot;\&CenterDot;a_{\mathrm{nn}}{x_n}^{\left(k\right)}+{{b_n}^u}^{\left(k\right)}\end{array}\right.$

Wherein a ₁₁, a ₁₂... a _nnand b ₁, b ₂... b _nbe all constant.

Above equation can abbreviation be:

$\left\{\begin{array}{c}{x_1}^{(k+1)}\\ {x_2}^{(k+1)}\\ \&CenterDot;\&CenterDot;\&CenterDot;\\ {x_n}^{(k+1)}\end{array}\right\}=\left\{\begin{array}{cccc}{a}_{11}& a_{12}& \&CenterDot;& a_{1n}\\ a_{21}& \&CenterDot;& & \&CenterDot;\\ \&CenterDot;& & \&CenterDot;& \&CenterDot;\\ a_{n1}& \&CenterDot;& \&CenterDot;& a_{\mathrm{nn}}\end{array}\right\}\left\{\begin{array}{c}{x_1}^{\left(k\right)}\\ {x_2}^{\left(k\right)}\\ \&CenterDot;\&CenterDot;\&CenterDot;\\ {x_n}^{\left(k\right)}\end{array}\right\}+\left\{\begin{array}{c}{b}_1\\ b_2\\ \\ b_n\end{array}\right\}u\left(k\right)$

Namely in marine biological enzyme Separation of Solid and Liquid, flow status equation is:

x(k+1)＝Ax(k)+Bu(k)(1)

Wherein, x is quantity of state, and u is controlled quentity controlled variable, x ∈ R ⁿ, u ∈ R ⁿ, $A=\left\{\begin{array}{cccc}{a}_{11}& a_{12}& \&CenterDot;& a_{1n}\\ a_{21}& \&CenterDot;& & \&CenterDot;\\ \&CenterDot;& & \&CenterDot;& \&CenterDot;\\ a_{n1}& \&CenterDot;& \&CenterDot;& a_{\mathrm{nn}}\end{array}\right\},$ $B=\left\{\begin{array}{c}{b}_1\\ b_2\\ \&CenterDot;\\ b_n\end{array}\right\},$ A ₁₁..a _nn, b ₁..b _nbe all constant, the value of A, B can be determined according to engineering practice.

If the sampling time is T, design the sliding-mode surface based on Reaching Law:

$e\left(k\right)=r\left(k\right)-x\left(k\right)---\left(2\right)$

$\mathrm{de}\left(k\right)=\frac{e\left(k\right)-e(k-1)}{T}---\left(3\right)$

Definition switching function is:

s(k)＝ce(k)+de(k)＝Cx(k)（4）

Wherein, c is controlled constant, C ∈ R ^{n × 1}be a constant matrices, its value can be determined according to engineering practice.

When system enters desirable sliding mode, get equivalent control u _eqfor controlled quentity controlled variable, s (k) meets:

s(k+1)＝s(k)(5)

Formula 5 is substituted into formula 4, has:

$(\mathrm{CA}-C)x\left(k\right)+{\mathrm{CB}}_{u_{\mathrm{eq}}}=0---\left(8\right)$

Meanwhile, can be obtained by formula 5:

s(k+1)-s(k)＝0（7）

Formula 4 and formula 6 are substituted into formula 7 to obtain:

$(\mathrm{CA}-C)x\left(k\right)+{\mathrm{CB}}_{u_{\mathrm{eq}}}=0---\left(8\right)$

When [CB] full rank, namely have:

u _eq＝-[CB] ^-1C(A-I)x(k)（9）

The method that the present invention adopts equivalent control to add Reaching Law can weaken buffeting, and control law total when adopting in this way is:

u＝u _eq+u _sw（10）

For continuous Sliding mode variable structure control, to be exponentially approaching rule be conventional Reaching Law:

s'(t)＝-ξsgn(s(t))-qs(t)（11）

For this discrete system by its discretize, obtaining exponentially approaching rule is:

s(k+1)-s(k)＝-qTs(k)-ξTsgn(s(k))（12）

Wherein, ξ > 0, q > 0,1-qT > O, T is the sampling period.

When not being ideal state, obtained by formula 6:

s(k+1)＝Cx(k+1)＝CAx(k)+CBu(k)（13）

Formula 13 is brought into formula 12 to obtain:

-qTs(k)-ξTsgn(s(k))＝C(A-I)x(k)+CBu(k)（14）

When [CB] full rank, have:

u(k)＝-(CB) ^-1[C(A-I)x(k)+qTs(k)+ξTsgn(s(k))]（15）

Formula 9 and 10 substitution formula 15 is drawn:

u _sw＝(CB) ^-1[-qTs(k)-ξTsgn(s(k))]（16）

Wherein s'=-qTs (k)-ξ Tsgn (s (k)) is the control rate in convergence stage.

The accessibility of the inventive method and stability prove as follows:

[s(k+1)-s(k)]sgn(s(k))＝[-qTs(k)-ξTsgn(s(k))]sgn(s(k))

＝-qT|s(k)|-ξT|s(k)|＜0（17）

Following meet accessibility condition so can design, definition Lyapunov function is:

$V\left(k\right)=\frac{1}{2}s{\left(k\right)}^2---\left(18\right)$

Obtained by formula 6:

S(k+1)＝Cx(k+1)＝CAx(k)+CBu(k)（19）

$s{(k+1)}^2-s{\left(k\right)}^2=2s\left(k\right){\mathrm{CB}}_{u_{\mathrm{sw}}}+{\left({\mathrm{CB}}_{u_{\mathrm{sw}}}\right)}^2---\left(20\right)$

Make s (k+1) ²-s (k) ²< 0, as long as now designed sliding mode meets stability condition.

2, design of Fuzzy Controller

The unchangeability of variable structure control system to systematic parameter and external disturbance is its outstanding advantages, but due to the time upper postpone, the reason such as the simplification of delayed and system model spatially, be not strict with sliding formwork curved slide motion after causing system to enter sliding-mode surface, but a kind ofly tremble oscillating movement along sliding formwork curve, buffeting is the obvious shortcoming that sliding-mode structure controls.Based on above-mentioned thought, design the buffeting that a fuzzy controller slackens system, improve Control platform.

Under the condition that the sampling time is fixing, the value of ξ determines the amplitude of controller buffeting.Get the absolute value that ξ is output fs (k) of Fuzzy control system:

ξ＝|fs(k)|(21)

Design two input singly exports fuzzy controller, and get switching function s (k) and rate of change s ' (k) conduct input thereof, variation range is [-1,1]; Fs (k) is as exporting, and variation range is [-1,1].

(1) ambiguity in definition collection

PB=honest ZO=zero NB=bears little

(2) according to fuzzy control principle, the input that definition s (k) and s ' (k) are fuzzy controller, exports as fs (k):

s(k)={NB,ZO,PB}

s'(k)={NB,ZO,PB}

fs(k)={NB,ZO,PB}

Its domain is:

S (k)={-1,0, ten 1}

s'(k)={-1,0,+1}

Fs (k)={-1,0, ten 1}

(3) fuzzy control rule of Fuzzy Sliding Model Controller is determined

S (k) → 0 is made by adopting fuzzy control rule and fuzzy reasoning.

Rule of thumb, following 9 fuzzy rules are adopted

①If(s(k)isNB)and(s'(k)isNB)then(fs(k)isNB)

②If(s(k)isNB)and(s'(k)isZO)then(fs(k)isNB)

③If(s(k)isNB)and(s'(k)isPB)then(fs(k)isZO)

④If(s(k)isZO)and(s'(k)isNB)then(fs(k)isNB)

⑤If(s(k)isZO)and(s'(k)isZO)then(fs(k)isZO)

⑥If(s(k)isZO)and(s'(k)isPB)then(fs(k)isZO)

⑦If(s(k)isPB)and(s'(k)isNB)then(fs(k)isZO)

⑧If(s(k)isPB)and(s'(k)isZO)then(fs(k)isZO)

⑨If(s(k)isPB)and(s'(k)isPB)then(fs(k)isPB)。

(4) anti fuzzy method:

The present invention adopts gravity model appoach by fuzzy output precision.

Fig. 4 is the marine biological enzyme Separation of Solid and Liquid flow control process figure based on Fuzzy Sliding Mode Variable Structure.As shown in Figure 4, by system initialization post-sampling error signal e (k) and e ' (k), when error signal within the specific limits time, by error signal e (k) and e ' (k) the defeated input definition switching function as sliding mode controller, design variable-structure control rule, again using switching function s (k) and s ' (k) obfuscation as the input of fuzzy controller through fuzzy reasoning, sharpening exports fs (k) and feeds back to controlled quentity controlled variable.When error signal is not in setting range, then to get control signal be u (k)=u (k-1)+m, m is the limited constant value obtained according to control experience.

Although the present invention with preferred embodiment openly as above, embodiment is not of the present invention for limiting.Without departing from the spirit and scope of the invention, any equivalence change done or retouching, belong to the protection domain of the present invention equally.Therefore the content that protection scope of the present invention should define with the claim of the application is standard.

Claims (2)

1. based on the marine biological enzyme Separation of Solid and Liquid flow controller of Fuzzy Sliding Mode Variable Structure, it is characterized in that, comprise DSP module, sliding formwork control module, fuzzy control model and flow sensor, wherein:

Described fuzzy control model is made up of obfuscation module, fuzzy reasoning module, sharpening module and base module;

Described sliding formwork control module is made up of Integral Sliding Mode face mould block, sliding formwork Reaching Law module, equivalent controller module and switch controller module;

The next position command r (k) of described DSP module delivery rate, described flow sensor detects and exports position signalling x (k) of present flow rate, and has error signal e (k)=r (k)-x (k);

When | e (k) | when being less than the threshold value ep preset, first using error signal e (k) and differential signal e ' (k) thereof as the input of Integral Sliding Mode face mould block to obtain switching function signal s (k), then produce switch-over control signal u through sliding formwork Reaching Law module to switch controller module on the one hand by switching function signal s (k) _sw, produce equivalent control signals u through equivalent controller module on the other hand _eq, and obtain control signal u (k)=u _sw+ u _eq; Simultaneously, using the input as fuzzy controller of switching function signal s (k) and differential signal s ' (k) thereof, successively through obfuscation module, fuzzy reasoning module and sharpening module, obtain fuzzy control output signal fs (k), then fuzzy control is outputed signal fs (k) and feed back to switch controller module; Finally control signal u (k) is exported to hydro-extractor system to realize flow control;

When | e (k) | when being not less than the threshold value ep preset, get control signal u (k)=u (k-1)+m, and control signal u (k) is exported to hydro-extractor system to realize flow control, wherein m is a limited constant value;

Above-mentioned switching function signal s (k)=Cx (k), switch-over control signal u _sw=(CB) ^-1[-qTs (k)-ξ Tsgn (s (k))], equivalent control signals u _eq=-(CB) ^-1c (A-I) x (k), wherein A, B, C are sliding formwork control coefrficient, ξ=| fs (k) |, T is system communication cycle, 0<q<1/T.

2. the marine biological enzyme Separation of Solid and Liquid flow controller based on Fuzzy Sliding Mode Variable Structure according to claim 1, it is characterized in that, the fuzzy set of input s (k) of described fuzzy controller, s ' (k) and output signal fs (k) is all taken as 3, be expressed as that { NB=is negative large, ZO=zero, PB=is honest }, the fuzzy rule adopted is following 9:

①If(s(k)isNB)and(s’(k)isNB)then(fs(k)isNB)

②If(s(k)isNB)and(s’(k)isZO)then(fs(k)isNB)

③If(s(k)isNB)and(s’(k)isPB)then(fs(k)isZO)

④If(s(k)isZO)and(s’(k)isNB)then(fs(k)isNB)

⑤If(s(k)isZO)and(s’(k)isZO)then(fs(k)isZO)

⑥If(s(k)isZO)and(s’(k)isPB)then(fs(k)isZO)

⑦If(s(k)isPB)and(s’(k)isNB)then(fs(k)isZO)

⑧If(s(k)isPB)and(s’(k)isZO)then(fs(k)isZO)

⑨If(s(k)isPB)and(s’(k)isPB)then(fs(k)isPB)。