CN117784590B - PID control method and system for microbial fuel cell - Google Patents
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- QTBSBXVTEAMEQO-UHFFFAOYSA-M Acetate Chemical compound CC([O-])=O QTBSBXVTEAMEQO-UHFFFAOYSA-M 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- GPRLSGONYQIRFK-UHFFFAOYSA-N hydron Chemical compound [H+] GPRLSGONYQIRFK-UHFFFAOYSA-N 0.000 claims description 3
- 238000004590 computer program Methods 0.000 claims 2
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/50—Fuel cells
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Abstract
The invention belongs to the technical field of energy control, and particularly relates to a PID control method and system of a microbial fuel cell, wherein the PID control method comprises the following steps: acquiring parameters of a microbial fuel cell; constructing a PID controller of the microbial fuel cell according to the acquired parameters; and controlling the dilution ratio of the microbial fuel cell based on the input of the controller constructed by the time delay estimation and the PID control, optimizing the parameters of the constructed PID controller by adopting an improved ant colony algorithm to obtain the maximum output voltage of the microbial fuel cell, and completing the PID control on the microbial fuel cell.
Description
Technical Field
The invention belongs to the technical field of energy control, and particularly relates to a PID control method and system of a microbial fuel cell.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Microbial fuel cells are a new energy technology that utilizes microorganisms in wastewater as catalysts to convert chemical energy of organic matters in wastewater into electric energy. At present, the energy supply required by human beings mainly comes from the combustion of fossil fuels, however, fossil fuels in nature are limited, and the transitional use of fossil fuels can not only cause energy crisis, but also inevitably cause the problem of environmental pollution. Therefore, human beings are very urgent to find a new green renewable energy source, so research on microbial fuel cells is advantageous to solve the above problems.
The internal reactions of microbial fuel cells are very complex, involving multiple disciplines of microbiology, electrochemistry, control, materials, etc. The internal structure of the double-chamber microbial fuel cell with high power generation efficiency consists of an anode, a cathode and a proton exchange membrane between the anode and the cathode. When the substrate of the microbial fuel cell is glucose, the microorganisms of the anode oxidize and decompose the glucose to generate protons and electrons, the protons are transferred to the cathode through the proton exchange membrane, the electrons reach the cathode through an external circuit, and meanwhile, the electrons release electric energy through the external circuit, and the electrons are combined with oxygen at the cathode to generate water.
The current use of microbial fuel cells is in the laboratory stage; the choice and control of the type of anode and cathode materials and the electricity-producing microorganisms are all important factors affecting the electricity production of microbial fuel cells. To the inventors' knowledge, microbial fuel cells are in fact a complex class of nonlinear systems, and the electrical performance is affected by a number of external factors as well as internal factors such as interactions between microorganisms within the microbial fuel cell. The microbial fuel cell has low electricity generation speed, unstable output voltage, and is easily affected by internal and external uncertainty factors, and how to realize the control of the output voltage of the microbial fuel cell by controlling the input of the microbial fuel cell and the change of the substrate concentration is a problem to be solved.
Disclosure of Invention
In order to solve the above problems, the present invention provides a PID control method and system for a microbial fuel cell, which controls the input of the microbial fuel cell by PID, optimizes PID parameters by using an improved ant colony algorithm, and counteracts external disturbance of the microbial fuel cell and the influence of interactions between various microorganisms inside the microbial fuel cell by using time delay estimation, so that the microbial fuel cell rapidly and stably generates a maximum output voltage.
According to some embodiments, the first aspect of the present invention provides a PID control method of a microbial fuel cell, which adopts the following technical scheme:
a PID control method of a microbial fuel cell, comprising:
Acquiring parameters of a microbial fuel cell;
Constructing a PID controller of the microbial fuel cell according to the acquired parameters;
And controlling the dilution ratio of the microbial fuel cell based on the input of the controller constructed by the time delay estimation and the PID control, optimizing the parameters of the constructed PID controller by adopting an improved ant colony algorithm to obtain the maximum output voltage of the microbial fuel cell, and completing the PID control on the microbial fuel cell.
As a further technical limitation, the reference value of the state is set asThen/>，/>Then, the error dynamics are: /(I)，/>Is a constant matrix; select control input as/>Wherein/>，/>For/>Can be expressed asWhere L is the sampling period, when L is infinitely small, then/>; At this time, control input。
As a further technical limitation, optimizing parameters of the constructed PID controller by adopting an improved ant colony algorithm, specifically, encoding the parameters of the PID controller by binary numbers, dividing an initial population into a plurality of sub-populations which are equal in size and in which pheromones cannot be communicated, respectively carrying out path selection and iteration of each sub-population in different modes, merging the sub-populations after the sub-populations reach the maximum iteration times, carrying out the pheromone communication of the merged sub-populations, and continuously carrying out normal optimizing operation of the ant colony algorithm on the sub-populations, wherein the maximum iteration times is set to be 100; and obtaining an optimal solution Z, wherein the output voltage of the corresponding microbial fuel cell is f (Z), and a plurality of new solutions Z 1,Z2,…Zn are randomly generated, wherein n is a finite value. At this time, the corresponding output voltage is f (Z 1),f(Z2),…,f(Zn); comparing f (Z) with f (Z 1),f(Z2),…,f(Zn), if f (Z) is maximum, outputting x=z, f (X) =f (Z); otherwise, outputting the largest f (Z q), q belongs to [1, n ], namely X=Z q, f(X)=f(Zq), then using a new solution Z q and an old solution Z as the upper and lower bounds of a local optimization range, carrying out local optimization by using an ant colony optimization algorithm, and outputting an optimal solution X=Z a,f(X)=f(Za), wherein a belongs to [1, n ]; and when the set maximum iteration number reaches 100, outputting an optimal solution to obtain the optimal PID control parameters of the microbial fuel cell.
As a further technical definition, prior to constructing the PID controller of the microbial fuel cell, a mathematical model of the microbial fuel cell is obtained from the obtained microbial fuel cell parameters, and the total voltage of the microbial fuel cell is obtained from the obtained mathematical model of the microbial fuel cell.
As a further technical definition, the microbial fuel cell parameters in the constructed mathematical model of the microbial fuel cell are analyzed according to the obtained total voltage of the microbial fuel cell, so as to obtain the time delay estimation and the PID controller of the microbial fuel cell.
Further, according to the obtained mathematical model and time delay estimation of the microbial fuel cell and the PID controller, an expression of the dilution ratio of the microbial fuel cell is obtained; and controlling the state of the microbial fuel cell by controlling the dilution ratio.
As a further technical definition, the acquired microbial fuel cell parameters include at least substrate concentration, microbial content, acetate concentration, hydrogen ion concentration, microbial growth rate, and substrate utilization in the microbial fuel cell.
According to some embodiments, a second aspect of the present invention provides a PID control system of a microbial fuel cell, which adopts the following technical scheme:
A PID control system for a microbial fuel cell, comprising:
An acquisition module configured to acquire microbial fuel cell parameters;
a construction module configured to construct a PID controller of the microbial fuel cell according to the acquired parameters;
And the control module is configured to control the dilution rate of the microbial fuel cell based on the delay estimation and the input of a controller constructed by PID control, optimize the parameters of the constructed PID controller by adopting an improved ant colony algorithm, obtain the maximum output voltage of the microbial fuel cell and finish the PID control of the microbial fuel cell.
According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium, which adopts the following technical solutions:
a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the steps in the PID control method of a microbial fuel cell according to the first aspect of the present invention.
According to some embodiments, a fourth aspect of the present invention provides an electronic device, which adopts the following technical solutions:
An electronic device comprising a memory, a processor and a program stored on the memory and running on the processor, the processor implementing the steps in the PID control method of a microbial fuel cell according to the first aspect of the present invention when executing the program.
Compared with the prior art, the invention has the beneficial effects that:
the invention uses the time delay estimation and the PID controller to control the input of the microbial fuel cell, uses the improved ant colony algorithm to optimize the PID parameter, and uses the time delay estimation to offset the external disturbance of the microbial fuel cell and the interaction among various microorganisms in the microbial fuel cell, so that the microbial fuel cell can quickly and stably generate the maximum output voltage.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification, illustrate and explain the embodiments and together with the description serve to explain the embodiments.
FIG. 1 is a flow chart of a PID control method of a microbial fuel cell according to a first embodiment of the invention;
FIG. 2 is a flow chart of inputs constructed based on delay estimation and PID controllers in accordance with a first embodiment of the invention;
FIG. 3 is a flowchart of optimizing parameters of a PID controller based on an improved ant colony algorithm according to an embodiment of the invention;
fig. 4 is a block diagram of the PID control system of the microbial fuel cell according to the second embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
In the present invention, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", etc. refer to an orientation or a positional relationship based on that shown in the drawings, and are merely relational terms, which are used for convenience in describing structural relationships of various components or elements of the present invention, and do not denote any one of the components or elements of the present invention, and are not to be construed as limiting the present invention.
In the present invention, terms such as "fixedly attached," "connected," "coupled," and the like are to be construed broadly and refer to either a fixed connection or an integral or removable connection; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the terms in the present invention can be determined according to circumstances by those skilled in the art or relevant scientific research and is not to be construed as limiting the invention.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Example 1
The embodiment of the invention introduces a PID control method of a microbial fuel cell.
A PID control method of a microbial fuel cell as shown in fig. 1, comprising:
a PID control method of a microbial fuel cell, comprising:
Acquiring parameters of a microbial fuel cell;
Constructing a PID controller of the microbial fuel cell according to the acquired parameters;
And controlling the dilution ratio of the microbial fuel cell based on the input of the controller constructed by the time delay estimation and the PID control, optimizing the parameters of the constructed PID controller by adopting an improved ant colony algorithm to obtain the maximum output voltage of the microbial fuel cell, and completing the PID control on the microbial fuel cell.
As one or more embodiments, prior to constructing the PID controller of the microbial fuel cell, a mathematical model of the microbial fuel cell is obtained from the obtained microbial fuel cell parameters, i.e.
；
；
；
；
Wherein the state x 1,x2,x3,x4 represents the substrate concentration, the microorganism content, the acetate concentration and the hydrogen ion concentration, respectively, and、/>，/>Representing unknown microbiological dynamics in a microbiological fuel cell,/>Is a disturbance input,/>Representing maximum substrate utilization,/>Represents the maximum microorganism growth rate, Q represents the half-saturation constant; n represents an initial substrate concentration value, b represents a microbial attenuation coefficient, and u represents a dilution ratio of the microbial fuel cell. Therefore, only the state x 1,x2 needs to be analyzed, and the control of the output voltage can be completed.
The state x 1,x2 in the mathematical model of the microbial fuel cell is analyzed to make x= [ x 1,x2]T, and at this time, the nonlinear mathematical model of the microbial fuel cell can be converted into:
；
Wherein, =/>，/>，,/>; Then/>; Wherein/>。
As shown in fig. 2, the state of the microbial fuel cell is controlled by controlling the dilution ratio u, so that the state is quickly stabilized to reach a desired value, and the microbial fuel cell is quickly generated with a stable output voltage, and the reference value of the state is set asThen/>，/>Then, the error dynamics are: /(I)，/>Is a constant matrix; select control input as/>Wherein/>，/>For/>Can be expressed asWhere L is the sampling period, when L is infinitely small, then/>; At this time, control input。
As one or more embodiments, the present example optimizes parameters of the constructed PID controller using the modified ant colony algorithm as shown in fig. 3, to achieve maximum power output of the microbial fuel cell.
In the embodiment, in the initial stage, the initial population number is set to be 40, 40 binary character strings are generated according to a random method, the heuristic factor is set to be 2, the pheromone volatilization factor is set to be 0.5, and the pheromone factor is set to be 2; the population is divided into three sub-populations with the same size, the three populations generate respective pheromones, different species cannot be mutually identified, and the three populations are optimized in different modes.
Population one: information such as pheromone, heuristic factors and the like in a normal ant colony algorithm is adopted for optimizing.
Population II: while taking information such as pheromone, heuristic factors and the like into consideration for path selection, a new mechanism is introduced, namely, when each ant makes path selection, the method comprises the following steps ofRandom movement is carried out on the probability of (2); where T represents the current iteration number and T represents the maximum iteration number. As the algorithm iterates, t increases, resulting in/>The value of (2) gradually decreases.
Population III: in the process of path selection, ants consider information such as pheromones and heuristic factors. At the same time, a randomly generated probability P is introduced. When P is larger than 0.5, the ant updates the path according to the normal ant colony algorithm, namely, the ant guides the ant according to the pheromone concentration and the heuristic factor. When P is smaller than 0.5, ants choose to randomly move, and are not constrained by pheromones and heuristic factors.
And taking the output voltage of the microbial fuel cell as a cost function, wherein the maximum iteration number is 100, and when the maximum iteration number is reached, combining the three sub-populations and intercommunicating the pheromones. Continuing to perform normal optimization operation of the ant colony algorithm on the population, and setting the maximum iteration number as 100; and obtaining an optimal solution Z, wherein the output voltage of the corresponding microbial fuel cell is f (Z), and a plurality of new solutions Z 1,Z2,…Zn are randomly generated, wherein n is a finite value. At this time, the corresponding output voltage is f (Z 1),f(Z2),…,f(Zn); comparing f (Z) with f (Z 1),f(Z2),…,f(Zn), if f (Z) is maximum, outputting x=z, f (X) =f (Z); otherwise, outputting the largest f (Z q), q belongs to [1, n ], namely X=Z q, f(X)=f(Zq), then using a new solution Z q and an old solution Z as the upper and lower bounds of a local optimization range, carrying out local optimization by using an ant colony optimization algorithm, and outputting an optimal solution X=Z a,f(X)=f(Za), wherein a belongs to [1, n ]; when the set maximum iteration number 100 is reached, the optimal solution is output. At this time, the microbial fuel cell is realized at the maximum power output.
The embodiment optimizes PID parameters by using an improved ant colony algorithm through time delay estimation and PID control of the input of the microbial fuel cell, and counteracts the influence of external disturbance of the microbial fuel cell and interaction among various microorganisms inside the microbial fuel cell by using the time delay estimation, so that the microbial fuel cell can quickly and stably generate the maximum output voltage.
Example two
The second embodiment of the invention introduces a PID control system of a microbial fuel cell.
A PID control system of a microbial fuel cell as shown in fig. 4, comprising:
An acquisition module configured to acquire microbial fuel cell parameters;
a construction module configured to construct a PID controller of the microbial fuel cell according to the acquired parameters;
And the control module is configured to control the dilution rate of the microbial fuel cell based on the delay estimation and the input of a controller constructed by PID control, optimize the parameters of the constructed PID controller by adopting an improved ant colony algorithm, obtain the maximum output voltage of the microbial fuel cell and finish the PID control of the microbial fuel cell.
The detailed steps are the same as those of the PID control method of the microbial fuel cell provided in the first embodiment, and will not be described herein.
Example III
The third embodiment of the invention provides a computer readable storage medium.
A computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the steps in a PID control method of a microbial fuel cell according to the first embodiment of the present invention.
The detailed steps are the same as those of the PID control method of the microbial fuel cell provided in the first embodiment, and will not be described herein.
Example IV
The fourth embodiment of the invention provides electronic equipment.
An electronic device comprising a memory, a processor and a program stored on the memory and running on the processor, wherein the processor implements the steps in the PID control method of a microbial fuel cell according to the first embodiment of the present invention when executing the program.
The detailed steps are the same as those of the PID control method of the microbial fuel cell provided in the first embodiment, and will not be described herein.
The above description is only a preferred embodiment of the present embodiment, and is not intended to limit the present embodiment, and various modifications and variations can be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment should be included in the protection scope of the present embodiment.
Claims (8)
1. A PID control method of a microbial fuel cell, comprising:
Acquiring parameters of a microbial fuel cell;
Constructing a PID controller of the microbial fuel cell according to the acquired parameters;
Based on the input of a controller constructed by time delay estimation and PID control, controlling the dilution rate of the microbial fuel cell, optimizing parameters of the constructed PID controller by adopting an improved ant colony algorithm to obtain the maximum output voltage of the microbial fuel cell, and completing the PID control on the microbial fuel cell;
Based on mathematical model of microbial fuel cell system, the reference value of the state is set as Then/>，/>Then, the error dynamics are: /(I)，/>Is a constant matrix; select control input as/>Wherein/>，/>For/>Can be expressed asWhere L is the sampling period, when L is infinitely small, then/>; At this time, control input；
The method comprises the steps of optimizing parameters of a constructed PID controller by adopting an improved ant colony algorithm, namely, encoding the parameters of the PID controller through binary numbers, dividing an initial population into a plurality of sub-populations which are equal in size and in which pheromones cannot be communicated, respectively carrying out path selection and iteration of each sub-population in different modes, merging the sub-populations after the sub-populations reach the maximum iteration times, carrying out normal optimization operation of the ant colony algorithm on the merged sub-populations, and setting the maximum iteration times as 100; obtaining an optimal solution Z, wherein the output voltage of a corresponding microbial fuel cell is f (Z), and a plurality of new solutions Z 1,Z2,…Zn are randomly generated, wherein n is a finite value; the corresponding output voltage is f (Z 1),f(Z2),…,f(Zn); comparing f (Z) with f (Z 1),f(Z2),…,f(Zn), if f (Z) is maximum, outputting x=z, f (X) =f (Z); otherwise, outputting the largest f (Z q), q belongs to [1, n ], namely X=Z q, f(X)=f(Zq), then using a new solution Z q and an old solution Z as the upper and lower bounds of a local optimization range, carrying out local optimization by using an ant colony optimization algorithm, and outputting an optimal solution X=Z a,f(X)=f(Za), wherein a belongs to [1, n ]; and when the set maximum iteration number reaches 100, outputting an optimal solution to obtain the optimal PID control parameters of the microbial fuel cell.
2. A PID control method of a microbial fuel cell as claimed in claim 1, characterized in that a mathematical model of the microbial fuel cell is obtained from the obtained parameters of the microbial fuel cell, and the total voltage of the microbial fuel cell is obtained from the obtained mathematical model of the microbial fuel cell, before the PID controller of the microbial fuel cell is constructed.
3. The PID control method of a microbial fuel cell as claimed in claim 2, wherein the time delay estimation and the PID controller of the constructed mathematical model of the microbial fuel cell are obtained by analyzing the parameters of the microbial fuel cell according to the obtained total voltage of the microbial fuel cell.
4. A PID control method of a microbial fuel cell as claimed in claim 3, characterized in that an expression of the dilution ratio of the microbial fuel cell is obtained based on the obtained mathematical model and time delay estimation of the microbial fuel cell and the PID controller; and controlling the state of the microbial fuel cell by controlling the dilution ratio.
5. A method of PID control of a microbial fuel cell as claimed in claim 1, characterized in that the obtained microbial fuel cell parameters comprise at least the substrate concentration, the microbial content, the acetate concentration, the hydrogen ion concentration, the microbial growth rate and the substrate utilization rate in the microbial fuel cell.
6. A PID control system of a microbial fuel cell, comprising:
An acquisition module configured to acquire microbial fuel cell parameters;
a construction module configured to construct a PID controller of the microbial fuel cell according to the acquired parameters;
The control module is configured to control the dilution rate of the microbial fuel cell based on the delay estimation and the input of a controller constructed by PID control, optimize the parameters of the constructed PID controller by adopting an improved ant colony algorithm, obtain the maximum output voltage of the microbial fuel cell, and finish the PID control on the microbial fuel cell;
Based on mathematical model of microbial fuel cell system, the reference value of the state is set as Then/>，/>Then, the error dynamics are: /(I)，/>Is a constant matrix; select control input as/>Wherein/>，/>For/>Can be expressed asWhere L is the sampling period, when L is infinitely small, then/>; At this time, control input；
The method comprises the steps of optimizing parameters of a constructed PID controller by adopting an improved ant colony algorithm, namely, encoding the parameters of the PID controller through binary numbers, dividing an initial population into a plurality of sub-populations which are equal in size and in which pheromones cannot be communicated, respectively carrying out path selection and iteration of each sub-population in different modes, merging the sub-populations after the sub-populations reach the maximum iteration times, carrying out normal optimization operation of the ant colony algorithm on the merged sub-populations, and setting the maximum iteration times as 100; obtaining an optimal solution Z, wherein the output voltage of a corresponding microbial fuel cell is f (Z), and a plurality of new solutions Z 1,Z2,…Zn are randomly generated, wherein n is a finite value; the corresponding output voltage is f (Z 1),f(Z2),…,f(Zn); comparing f (Z) with f (Z 1),f(Z2),…,f(Zn), if f (Z) is maximum, outputting x=z, f (X) =f (Z); otherwise, outputting the largest f (Z q), q belongs to [1, n ], namely X=Z q, f(X)=f(Zq), then using a new solution Z q and an old solution Z as the upper and lower bounds of a local optimization range, carrying out local optimization by using an ant colony optimization algorithm, and outputting an optimal solution X=Z a,f(X)=f(Za), wherein a belongs to [1, n ]; and when the set maximum iteration number reaches 100, outputting an optimal solution to obtain the optimal PID control parameters of the microbial fuel cell.
7. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, realizes the steps of the PID control method of a microbial fuel cell according to any one of claims 1-5.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the steps of the PID control method of a microbial fuel cell according to any of claims 1-5 when executing the program.
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