CN104345636A - Dissolved-oxygen control method based on improved differential algorithm - Google Patents

Abstract

Disclosed is a dissolved-oxygen control method based on an improved differential algorithm. The method includes the following steps: a data acquisition system and a central control system. The data acquisition system includes a sensing device, a communication gateway and an OPC server. The sensing device carries out real-time online detection on technological parameters in a sewage disposal process and is connected with the gateway through a communication protocol. The gateway converts acquired data into data which can be identified by the OPC server and transmits the data through the OPC server. The central control system includes an OPC client and an optimizing system. The OPC client receives data information transmitted by the OPC server and transmits the data information to the optimizing system. Based on a virtual instrument technology, a powerful interconnection interface technology of LabVIEW is used to realize mixed programming of the LabVIEW and Matlab and the powerful operation capacity of the Matlab is used to carry out optimal-value searching based on the improved differential algorithm on the concentration of dissolved oxygen in a sewage disposal process. On the premise that the water quality of effluent water complies with the state standard, the operation cost is effectively saved and win-win of efficiency and economy is realized.

Description

A kind of Dissolved Oxygen Control Method based on improving difference algorithm

Technical field

The present invention relates to the fields such as intelligent optimization algorithm, the network communications technology, Based Intelligent Control and electric automatization control, being specifically related to a kind of Dissolved Oxygen Control Method based on improving difference algorithm.

Background technology

According to environmental administration's statistics, whole nation industry total consumption fresh water amount 543.95 hundred million tons, wherein industrial sewage total release 211.86 hundred million tons, wherein industrial COD total release 365.6 ten thousand tons in 2010.Can find out that the treatment and discharge situation of national Industrial Waste Water Treatments is still very pessimistic.

Compared with general industry production run, the operation of wastewater treatment has singularity.First wastewater treatment must observe the enforceable emission standard of environmental regulation, then could consider the realization of control objectives.Consider from the angle of environmental protection, effluent quality is more high better, but from operating cost aspect, effluent quality is high means more energy consumption, and operating cost is high.

Traditional supervisory system is that the real-time online that cannot realize production run controls by checking that on-the-spot patrol record judges the reading of field instrument, the obvious like this requirement that cannot meet to real-time property and accuracy in industrial processes.

The automatization level of domestic sewage disposal process still suitable backwardness, great majority only rest on data acquisition, are confined to local monitoring for site disposal technological process great majority.Many Water Treatment Automatic Control System major parts only have simple digital output modul or traditional PID control, do not reach the controlling extent controlling integrated special service, intellectuality, overall process, non-linear, the Great inertia of sewage disposal process cannot be met and be difficult to the features such as Accurate Model.Operational efficiency is low, and energy consumption is large, costly.

Summary of the invention

The object of the invention is to overcome prior art above shortcomings, designing a kind of Dissolved Oxygen Control Method based on improving difference algorithm.

The present invention is achieved by the following technical solutions:

Based on the Dissolved Oxygen Control Method improving difference algorithm, comprising: data acquisition system (DAS) and central control system.

Described data acquisition system (DAS), comprising: sensing equipment, communication gate, opc server; Sewage disposal process technological parameter real-time online detects by sensing equipment, and be connected with gateway by communication protocol, the data collected are converted to the data that opc server can identify by gateway, data are transferred out by opc server.

Described central control system, comprising: OPC client and optimization system; OPC client accepts the data message that opc server spreads out of, and is transferred to optimization system; Based on virtual instrument technique, the interconnecting interface technology utilizing LabVIEW powerful, realize LabVIEW and Matlab hybrid programming, utilize the arithmetic capability that Matlab is powerful, the optimal value optimizing based on improving difference algorithm is carried out to dissolved oxygen concentration in sewage disposal process.

Described optimization system is based on the wastewater treatment Mechanism Model simplified, according to the state equation of controlled system, objective function, constraint condition and input variable, by improving difference algorithm optimal control variable, from the control program that a class allows, find out an optimum control program, make target function value be optimum to greatest extent.

Described Treatment of Sludge Mechanism Model, be two classes by microorganism and organism merger, i.e. dissolved matter (BOD) and particulate matter (MLSS), ignore the metabolism of microorganism in second pond and enter oxygen in water, simultaneously for the ease of carrying out fixing quantity to discharge mud, specify the direct spoil disposal from aeration tank.

Described state equation, with discharge (Q of intaking _w) and dissolved oxygen concentration (DO) be control variable, with water outlet BOD concentration (S) and MLSS concentration (X) for state variable, equation is as follows:

$\left\{\begin{array}{c}\frac{\mathrm{dX}}{\mathrm{dt}}=X(\frac{\mathrm{YkS}}{K_s+S}-K_d)\·\frac{\mathrm{DO}}{K_0+\mathrm{DO}}-\frac{Q_{w}X}{V}\\ \frac{\mathrm{dS}}{\mathrm{dt}}=\frac{Q(S_0-S)}{V}-\frac{\mathrm{XkS}}{K_s+S}\·\frac{\mathrm{DO}}{K_0-\mathrm{DO}}\end{array}\right.$

In formula: k is that substrate high specific utilizes rate constant; K ₀for the saturation constant of oxygen; K _dfor the rate of decay of microorganism; K _sfor BOD saturation coefficient; V is aeration tank useful volume; Y is yield coefficient.

Described objective function, using the operating cost sum of excess sludge process, sludge reflux and air feed as performance index, is expressed as follows by functional:

$J=\underset{0}{\overset{1}{\∫}}\{{\mathrm{AQ}}_{w}X+\frac{\mathrm{BX}(Q-Q_w)}{X_r-X}+C_1\frac{D_S-{\mathrm{DO}}_1}{D_S-\mathrm{DO}}[\frac{\mathrm{VXDO}}{K_0+\mathrm{DO}}(\frac{\mathrm{akS}}{K_S+S}+1.42K_d)+Q\·\mathrm{DO}\left]\right\}\mathrm{dt}$

In formula: A, B, C ₁for expense constant; A is the Required coefficient utilizing unit substrate; DO ₁for the setting value of dissolved oxygen concentration; D _sfor the saturation concentration of dissolved oxygen DO.

Described constraint condition, with organic emission total amount and effluent quality for constraint condition, is expressed as follows:

$\left\{\begin{array}{c}{Z}_S-Z\left(1\right)\&GreaterEqual;0\\ 0<\mathrm{DO}\&le;D_S\\ Q_w>0\end{array}\right.$

In formula: Z _sfor national regulation organic emission total amount, general Z _s=150kg (BOD)/d, D _sfor saturated dissolved oxygen concentration.

Described improvement difference algorithm, differential evolution (DE) is simulated Darwinian evolutionism and grows up, it is a kind of heuristic global search technology, and this algorithm principle simply, easily realizes and controlled parameter is few, strong robustness, has good Optimal performance; Improvement difference algorithm (ADE) is the improvement to DE algorithm, the aberration rate in DE algorithm is improved to self-adaptation type, avoids optimum solution and destroyed.

Initialization population, $\left\{x_i\left(0\right)\right|x_{i,j}^L\&le;x_{i,j}\left(0\right)\&le;x_{i,j}^U,i=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,\mathrm{NP};j=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,D\}$ Random generation:

$x_{i,j}\left(0\right)=x_{i,j}^L+\mathrm{rand}*(x_{i,j}^U-x_{i,j}^L)$

In formula, x _i(0) i-th individuality in the 0th generation in population is represented, x _{i, j}(0) the jth gene that i-th of the 0th generation is individual is represented, for the boundary value of feasible solution, NP is population scale, and D is the dimension of identified parameters, and rand is the random number produced between (0,1).

Mutation operation, to select in colony two different individuality vectors at random, utilizes aberration rate F to zoom in or out its difference vector; Then, individuality vector to be made a variation is acted on.For each object vector x _i(g), the variation vector v of its correspondence _i(g+1) be:

v _i(g+1)＝x _t1(g)+F·(x _t2(g)-x _t3(g))(i≠t1≠t2≠t3)

In formula, t1, t2, t3 ∈ [1, NP] is different and different from i, and F is aberration rate, and it controls difference vector (x _t2(g)-x _t3(g)) convergent-divergent, x _ig () represents that g is for i-th individuality in population.

Adapt variance, adaptive mutation rate is as follows:

$M=F_0\&CenterDot;2^{e^{(1-\frac{\mathrm{gen}\_\max }{\mathrm{gen}\_\max +1-\mathrm{count}})}}$

In formula, F ₀for Mutation parameter, gen_max is maximum evolutionary generation, and count is current evolutionary generation (1≤count≤gen_max).

Interlace operation, by individual for the parent before variation x _ithis generation after (g) and variation individual v _i(g+1) carry out interlace operation by certain rule, obtain testing individual u _{i, j}(g+1).For making individual in population x _ig () is evolved, DE algorithm guarantees the individual u of test produced _{i, j}(g+1) one is had at least to be provided by variation individuality, otherwise individual by not producing new parent; As for u _{i, j}(g+1) other position, by the random number rand of generation and the magnitude relationship of crossover probability factor CR, determines by x _ig () is supplied to u _{u, j}(g+1), or by v _i(g+1) u is supplied to _{i, j}(g+1), scheme is as follows:

$u_{i,j}(g+1)=\left\{\begin{array}{cc}{v}_{i,j}(g+1),& \mathrm{ifrand}\&le;\mathrm{CR\; or\; j}=j_{\mathrm{rand}}\\ x_{i,j}\left(g\right),& \mathrm{otherwise}\end{array}\right.$

In formula, rand ∈ [0,1] is equally distributed random number, u _{i, j}(g+1) for test is individual, represent and to produce in new parent colony i-th individual jth gene, CR is crossover probability, j _randfor [1,2 ..., D] random integers.

Select operation, the individual u of the test produced after variation with interlace operation _iand x (g+1) _ig () is at war with, determine to enter follow-on individuality.For minimization problem, only at the individual u of test _i(g+1) fitness function value is than target individual x _ithe fitness function value hour of (g), u _i(g+1) just can by original x _ig () replaces, otherwise x _ig () is retained by continuation, as of future generation individual.Select operation as follows:

$x_i(g+1)=\left\{\begin{array}{cc}{u}_i(g+1),& \mathrm{if\; f}\left(u_i(g+1)\right)\&le;f\left(x_i\left(g\right)\right)\\ x_i\left(g\right),& \mathrm{otherwise}\end{array}\right.$

In formula, f is fitness function, f (u _i(g+1)) be the individual u of test _i(g+1) corresponding fitness value.

Described input variable, comprises flow of inlet water (Q) and water inlet BOD concentration (S ₀), adopt sensing equipment real-time online to detect respectively, simultaneously by communication gate by real time data acquisition, be transferred to central control system.

Described central control system, can be packaged into an entirety, therefore only need access input variable and just can seek obtaining the dissolved oxygen concentration optimal value of this plant of water disposal.

In order to can better the present invention be performed, there is provided following optimum decision system: by equipment such as frequency converter, fan blower, online dissolved oxygen meters, dissolved oxygen DO is controlled formation closed-loop system, the optimal value that central control system is sought by opc server is transferred to PLC, introduce Fuzzy Self-adaptive PID, realize the Based Intelligent Control to this closed-loop system.

The difference algorithm of improvement is incorporated in sewage treatment process by the present invention, carries out optimized control to dissolved oxygen concentration, under ensureing that effluent quality meets the prerequisite of national standard, has effectively saved the cost run, implementation efficiency and economic doulbe-sides' victory; Utilize the Modern Tracking Technology's such as communication gate, LabVIEW, PLC, ensure that real-time and the accuracy of input variable; Central control system can be packaged into an entirety, and system suitability is strong, portable high; The present invention simultaneously also proposes an optimum decision system, according to the dissolved oxygen concentration optimal value obtained, introduce the Based Intelligent Control of Fuzzy Self-adaptive PID realization to dissolved oxygen concentration, reduce energy resource consumption, the demand of China to wastewater treatment can be met, there is larger application and promotional value.

Accompanying drawing explanation

Fig. 1 is control structure figure of the present invention;

Fig. 2 is algorithm flow chart of the present invention (illustrating);

Fig. 3 is algorithm optimizing result figure of the present invention (citing emulation);

Fig. 4 is preferred structure figure of the present invention;

Embodiment

Below in conjunction with accompanying drawing, the present invention is described further:

As shown in Figure 1, the present invention includes: data acquisition system (DAS) and central control system.

Described data acquisition system (DAS), comprising: sensing equipment, communication gate, opc server; Sewage disposal process technological parameter real-time online detects by sensing equipment, and be connected with gateway by communication protocol, the data collected are converted to the data that opc server can identify by gateway, data are transferred out by opc server.

Described sensing equipment, comprising: electromagnetic flowmeter and BOD on-line detector, and real-time online detects Q and S ₀, adopt the sensing equipment supporting MODBUS communication protocol.

Described communication gate, adopts the universal serial port PROFIBUS DP gateway PM-160 of SiboTech Automation (Shanghai) Co., Ltd., realizes the conversion of MODBUS to PROFIBUS DP, by Siemens 300 series of PLC by Q and S ₀data acquisition; Set up opc server by PLC data are transferred out.

Described central control system, based on virtual instrument technique, using control system as OPC client, gathers Q and S on opc server ₀data; Utilize the interconnecting interface technology that LabVIEW is powerful simultaneously, realize LabVIEW and Matlab hybrid programming, utilize the arithmetic capability that Matlab is powerful, the optimal value optimizing based on improving difference algorithm is carried out to dissolved oxygen concentration in sewage disposal process.

Described central control system, can be packaged into an entirety, therefore only need access input variable and just can seek obtaining the dissolved oxygen concentration optimal value of this plant of water disposal.

As shown in Figure 2, improve difference algorithm to the optimal-search control of dissolved oxygen concentration optimal value to better illustrate, the present invention is illustrated by following case: with aeration tank useful volume V=2500m ³the optimal control of sewage disposal process be that example is carried out designing and emulates.Due to this sewage disposal system flow of inlet water with water inlet substrate (BOD) concentration be constantly change in time, in order to convenience of calculation, if in one day flow of inlet water Q and intake substrate (BOD) concentration S ₀in time by sinusoidal wave change:

$\left\{\begin{array}{c}Q=Q\left(t\right)=10000+50000\sin \left(2\mathrm{\&pi;t}\right)\\ S_0=S_0\left(t\right)=0.15+0.05\sin \left(2\mathrm{\&pi;t}\right)\end{array}\right.$

Initialization population, $\left\{x_i\left(0\right)\right|x_{i,j}^L\&le;x_{i,j}\left(0\right)\&le;x_{i,j}^U,i=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,\mathrm{NP};j=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,D\}$ Random generation:

$x_{i,j}\left(0\right)=x_{i,j}^L+\mathrm{rand}*(x_{i,j}^U-x_{i,j}^L)$

In formula, x _i(0) i-th individuality in the 0th generation in population is represented, x _{i, j}(0) the jth gene that i-th of the 0th generation is individual is represented, for the boundary value of feasible solution, NP is population scale, and D is the dimension of identified parameters, and rand is the random number produced between (0,1).

Mutation operation, to select in colony two different individuality vectors at random, utilizes aberration rate F to zoom in or out its difference vector;

Then, individuality vector to be made a variation is acted on.For each object vector x _i(g), the variation vector v of its correspondence _i(g+1) be:

v _i(g+1)＝x _t1(g)+F·(x _t2(g)-x _t3(g))(i≠t1≠t2≠t3)

In formula, t1, t2, t3 ∈ [1, NP] is different and different from i, and F is aberration rate, and it controls difference vector (x _t2(g)-x _t3(g)) convergent-divergent, x _ig () represents that g is for i-th individuality in population.

Adapt variance, adaptive mutation rate is as follows:

$M=F_0\&CenterDot;2^{e^{(1-\frac{\mathrm{gen}\_\max }{\mathrm{gen}\_\max +1-\mathrm{count}})}}$

In formula, F ₀for Mutation parameter, gen_max is maximum evolutionary generation, and count is current evolutionary generation (1≤count≤gen_max).

Interlace operation, by individual for the parent before variation x _ithis generation after (g) and variation individual v _i(g+1) carry out interlace operation by certain rule, obtain testing individual u _{i, j}(g+1).For making individual in population x _ig () is evolved, DE algorithm guarantees the individual u of test produced _{i, j}(g+1) one is had at least to be provided by variation individuality, otherwise individual by not producing new parent; As for u _{i, j}(g+1) other position, by the random number rand of generation and the magnitude relationship of crossover probability factor CR, determines by x _ig () is supplied to u _{i, j}(g+1), or by v _t(g+1) u is supplied to _{i, j}(g+1), scheme is as follows:

$u_{i,j}(g+1)=\left\{\begin{array}{cc}{v}_{i,j}(g+1),& \mathrm{ifrand}\&le;\mathrm{CR\; or\; j}=j_{\mathrm{rand}}\\ x_{i,j}\left(g\right),& \mathrm{otherwise}\end{array}\right.$

In formula, rand ∈ [0,1] is equally distributed random number, u _{i, j}(g+1) for test is individual, represent and to produce in new parent colony i-th individual jth gene, CR is crossover probability, j _randfor [1,2 ..., D] random integers.

Select operation, the individual u of the test produced after variation with interlace operation _iand x (g+1) _ig () is at war with, determine to enter follow-on individuality.For minimization problem, only at the individual u of test _i(g+1) fitness function value is than target individual x _ithe fitness function value hour of (g), u _i(g+1) just can by original x _ig () replaces, otherwise x _ig () is retained by continuation, as of future generation individual.Select operation as follows:

$x_i(g+1)=\left\{\begin{array}{cc}{u}_i(g+1),& \mathrm{if\; f}\left(u_i(g+1)\right)\&le;f\left(x_i\left(g\right)\right)\\ x_i\left(g\right),& \mathrm{otherwise}\end{array}\right.$

In formula, f is fitness function, f (u _i(g+1)) be the individual u of test _i(g+1) corresponding fitness value.

As shown in Figure 3, described case is identical with Fig. 2, obtains control variable Q by Matlab emulation _wand DO, state variable S and X, the Optimal Curve of constraint condition Z and objective function J.

If Fig. 4 is the optimum decision system of this patent, this patent can better be performed, by equipment such as frequency converter, fan blower, online dissolved oxygen meters, dissolved oxygen DO is controlled formation closed-loop system, the optimal value that central control system is sought by opc server is transferred to PLC, introduce Fuzzy Self-adaptive PID, realize the Based Intelligent Control to this closed-loop system.

Claims (6)

1., based on the Dissolved Oxygen Control Method improving difference algorithm, comprising: data acquisition system (DAS) and central control system.Data acquisition system (DAS), comprising: sensing equipment, communication gate, opc server; Sewage disposal process technological parameter real-time online detects by sensing equipment, and be connected with gateway by communication protocol, the data collected are converted to the data that opc server can identify by gateway, data are transferred out by opc server.Central control system, comprising: OPC client and optimization system; OPC client accepts the data message that opc server spreads out of, and is transferred to optimization system.

2. sensing equipment according to claim 1 is electromagnetic flowmeter and the BOD on-line detector of supporting MODBUS agreement.

3. communication gate according to claim 1 adopts the universal serial port PROFIBUS DP gateway PM-160 of SiboTech Automation (Shanghai) Co., Ltd., realizes the conversion of MODBUS to PROFIBUS DP.

4. opc server according to claim 1 is set up by Siemens 300 series of PLC.

5. OPC client according to claim 1 is realized by the DataSocket technology under LabVIEW development platform.

6. optimization system according to claim 1 is based on the wastewater treatment Mechanism Model simplified, the interconnecting interface technology utilizing LabVIEW powerful, realize LabVIEW and Matlab hybrid programming, utilize the arithmetic capability that Matlab is powerful, the optimal value optimizing based on improving difference algorithm is carried out to dissolved oxygen concentration in sewage disposal process.