WO2016125734A1 - 制御システム、制御装置、制御方法及び非一時的記憶媒体 - Google Patents

制御システム、制御装置、制御方法及び非一時的記憶媒体 Download PDF

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WO2016125734A1
WO2016125734A1 PCT/JP2016/052897 JP2016052897W WO2016125734A1 WO 2016125734 A1 WO2016125734 A1 WO 2016125734A1 JP 2016052897 W JP2016052897 W JP 2016052897W WO 2016125734 A1 WO2016125734 A1 WO 2016125734A1
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control
dither signal
amount
disturbance
extreme value
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PCT/JP2016/052897
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English (en)
French (fr)
Japanese (ja)
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理 山中
由紀夫 平岡
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株式会社東芝
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Priority to CN201680008335.5A priority Critical patent/CN107250929B/zh
Publication of WO2016125734A1 publication Critical patent/WO2016125734A1/ja

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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric

Definitions

  • Embodiments described herein relate generally to a control system, a control device, a control method, and a non-transitory storage medium.
  • control target process an operation amount input to a process to be controlled
  • control target process an estimation model for estimating a control amount of the control target process. It was common to be based on control.
  • a technique called extreme value control that does not use an estimation model of a process to be controlled has attracted attention in the control of the operation amount.
  • the extreme value control is a method of searching for an operation amount so that the control amount of the process to be controlled approaches an optimum value by intentionally changing the operation amount. Since extreme value control does not use an estimation model of a controlled object process, it is possible to easily control an operation amount for a controlled object process represented by a complicated estimated model.
  • the problem to be solved by the present invention is to provide a control system, a control device, a control method, and a non-temporary storage medium capable of performing extreme value control while suppressing the influence on plant operation.
  • the control system of the embodiment is a control system that controls an operation amount given to a control target process based on a disturbance, and is a disturbance signal acquisition unit, a control amount information acquisition unit, a dither signal generation unit, an evaluation value calculation unit, and an extreme value Has a control unit.
  • the disturbance signal acquisition unit acquires a disturbance signal indicating the disturbance.
  • the control amount information acquisition unit acquires control amount information indicating a control amount of the control target process.
  • the dither signal generation unit generates a dither signal for changing an operation amount given to the control target process with reference to the disturbance signal in the control of the control target process.
  • the evaluation value calculation unit calculates an evaluation value serving as an index for evaluating the control amount of the process to be controlled based on the control amount information.
  • the extreme value control unit varies the operation amount based on the dither signal generated by the dither signal generation unit, and controls the operation amount while searching for the extreme value of the evaluation value.
  • the functional block diagram which shows the function structure of the control system 100 of 1st Embodiment. Schematic for demonstrating the concept of extreme value control. Schematic for demonstrating the concept of extreme value control. Schematic for demonstrating the concept of extreme value control. Schematic for demonstrating the concept of extreme value control.
  • the block diagram which shows a general extreme value control system. The block diagram which shows the extreme value control system in the control system 100 of 1st Embodiment. The flowchart figure which shows the flow of the extreme value control by the control system 100 of 1st Embodiment. The figure which shows the specific example of the water treatment plant controlled using the control system 100 of 1st Embodiment.
  • the functional block diagram which shows the function structure of the control system 100a of 2nd Embodiment. The figure which shows the specific example of the transition pattern produced
  • FIG. 1 is a functional block diagram illustrating a functional configuration of the control system 100 according to the first embodiment.
  • a control target 200 in FIG. 1 represents a facility such as a factory or a plant in which a control target process to be controlled by the control system 100 is mounted.
  • the control target 200 includes various measurement devices that measure the control amount of the control target process and the disturbance acting on the control target process.
  • the control target 200 outputs measurement information acquired by measurement of various measurement devices to the control system 100.
  • the control system 100 determines an operation amount to be given to the control target process based on the measurement information output from the control target 200.
  • the control target 200 changes the control amount of the control target process by inputting the operation amount determined by the control system 100 to the control target process.
  • the control system 100 includes a CPU (Central Processing Unit) connected via a bus, a memory, an auxiliary storage device, and the like.
  • the control system 100 executes a control program stored in a memory or an auxiliary storage device.
  • the control system 100 includes a measurement information acquisition unit 110 (an example of a disturbance signal acquisition unit and a control amount information acquisition unit), an operation amount output unit 120, a dither signal generation unit 130, and an evaluation amount calculation unit 140 (evaluation value) by executing a control program.
  • An example of a calculation unit and an apparatus including the extreme value control unit 150 function.
  • All or some of the functions of the control system 100 may be realized by using hardware such as ASIC (Application Specific Integrated Circuit), PLD (Programmable Logic Device), and FPGA (Field Programmable Gate Array).
  • the control program may be recorded on a computer-readable recording medium.
  • the computer-readable recording medium is, for example, a portable medium such as a flexible disk, a magneto-optical disk, a ROM, a CD-ROM, or a storage device such as a hard disk built in the computer system.
  • the control program may be transmitted via a telecommunication line.
  • the measurement information acquisition unit 110 and the operation amount output unit 120 are configured to include a communication interface for connecting to a network such as a LAN (Local Area Network).
  • the measurement information acquisition unit 110 communicates with the control target 200 and acquires measurement information from the control target 200.
  • the measurement information acquisition unit 110 outputs a signal indicating disturbance (hereinafter referred to as “disturbance signal”) included in the acquired measurement information to the dither signal generation unit 130.
  • the measurement information acquisition unit 110 outputs information indicating the control amount (hereinafter referred to as “control amount information”) included in the acquired measurement information to the evaluation amount calculation unit 140.
  • the operation amount output unit 120 communicates with the control target 200 and outputs the operation amount generated by the extreme value control unit 150 to the control target 200.
  • the dither signal generation unit 130 acquires the disturbance signal output from the measurement information acquisition unit 110.
  • the dither signal generation unit 130 refers to the acquired disturbance signal and generates a dither signal for changing the operation amount given to the process to be controlled.
  • the dither signal generation unit 130 outputs the generated dither signal to the extreme value control unit 150.
  • the evaluation amount calculation unit 140 calculates an evaluation amount necessary for the extreme value control performed by the extreme value control unit 150 based on the control amount information output from the measurement information acquisition unit 110.
  • the evaluation amount calculation unit 140 outputs evaluation amount information indicating the calculated evaluation amount to the extreme value control unit 150.
  • Extreme value control is a control method in which the operation amount is searched so that the control amount of the process to be controlled approaches the optimum value.
  • the control amount of the control target process is evaluated based on an arbitrary evaluation criterion corresponding to the purpose of the control target process, and the operation amount input to the control target process is controlled based on the evaluation result.
  • the evaluation amount information is information indicating an evaluation amount calculated based on this evaluation criterion, and is calculated based on the control amount information measured for the process to be controlled.
  • the evaluation amount may be calculated as an operation cost required for plant operation, or may be calculated as another evaluation value.
  • the operation amount is controlled so that the control amount of the process to be controlled decreases the operation cost.
  • the control amount of the process to be controlled converges to the optimum value.
  • the extreme value control does not require an estimation model for directly estimating the control amount of the control target process, so that the operation amount of any control target process can be easily controlled.
  • the extreme value control unit 150 determines that the control amount of the process to be controlled transitions to the optimum value based on the evaluation amount information output from the evaluation amount calculation unit 140 and the dither signal output from the dither signal generation unit 130. The operation amount is determined so as to go. The extreme value control unit 150 outputs operation amount information indicating the determined operation amount to the operation amount output unit 120.
  • FIG. 2A to 2D are schematic diagrams for explaining the concept of extreme value control.
  • the horizontal axis represents the operation amount
  • the vertical axis represents the evaluation amount.
  • the relationship between the operation amount given to the process to be controlled and the control amount that changes according to the given operation amount is unknown.
  • the relationship between the manipulated variable and the evaluated value is also unknown, but for the sake of easy understanding of the explanation, it is assumed that the relationship between the evaluated value and the manipulated variable at a certain timing is expressed as a curve 10.
  • the evaluation amount indicated by the curve 10 has a minimum point at the point 11.
  • the evaluation amount is considered as a cost
  • the process to be controlled is controlled with a control amount that makes the cost smaller, so the target operation amount is the operation amount at the point 11.
  • the extreme value control unit 150 changes the manipulated variable with the dither signal shown in FIG. 2B, with the point 12 on the curve 10 as an initial value, for example.
  • the extreme value control unit 150 has a smaller cost. The operation amount is increased so that
  • the extreme value control unit 150 when the evaluation amount shows a change in phase with the dither signal, that is, when the evaluation amount increases with an increase in the operation amount, the extreme value control unit 150 has a lower cost. So as to reduce the operation amount. By repeatedly increasing and decreasing the operation amount as described above, the extreme value control unit 150 controls the operation amount while searching for the optimum operation amount (the operation amount at the point 11 in the figure). This is the basic concept of extreme value control.
  • the extreme value control system controlled by such extreme value control is generally represented by a block diagram shown in FIG.
  • FIG. 3 is a block diagram showing a general extreme value control system.
  • s represents a Laplace operator.
  • S / (s + ⁇ 2) is a high-pass filter, and “ ⁇ 1 / s + ⁇ 1” is a low-pass filter.
  • K / s represents an integrator, and k is the gain of the integrator.
  • a ⁇ sin ⁇ t is a dither signal generator. The dither signal affects both the manipulated variable and the controlled variable.
  • 2A to 2D a signal obtained by applying a dither signal to the control amount is a signal indicating the evaluation amount shown in FIGS. 2C and 2D. The signal indicating the evaluation amount gives the integrator a direction to increase or decrease the operation amount.
  • the integrator outputs a signal indicating the operation amount based on the direction of increase / decrease of the operation amount and the intensity of the signal indicating the evaluation amount.
  • the dither signal acts on a signal indicating the operation amount output from the integrator, and slightly changes the operation amount.
  • the various parameters relating to the extreme value search are the gain k of the integrator, the cutoff frequency ⁇ 1 of the low-pass filter, the cutoff frequency ⁇ 2 of the high-pass filter, the amplitude a of the dither signal, and the frequency ⁇ of the dither signal.
  • the gain k of the integrator the cutoff frequency ⁇ 1 of the low-pass filter
  • the cutoff frequency ⁇ 2 of the high-pass filter the amplitude a of the dither signal
  • the frequency ⁇ of the dither signal For example, the following five guidelines are known for setting these parameters.
  • the frequency ⁇ of the dither signal is set sufficiently smaller than the response speed of the plant. That is, when the time constant of the plant is T, ⁇ ⁇ 2 ⁇ / T is set.
  • the amplitude of the dither signal is set sufficiently smaller than the normal movement of the manipulated variable, and is set sufficiently smaller than the frequency of the dither signal. That is, a ⁇ ⁇ is set.
  • the gain of the integrator is set sufficiently smaller than the frequency of the dither signal. That is, it is set so that k ⁇ ⁇ .
  • the cut-off frequency of the low-pass filter is set sufficiently higher than the frequency of the dither signal, and the cut-off frequency of the high-pass filter is set sufficiently lower than the frequency of the dither signal. That is, it sets so that ⁇ 2 ⁇ ⁇ ⁇ ⁇ 1.
  • the pointer 4 is described in Non-Patent Document 1, and it has been pointed out that the dither signal used for the extreme value search does not have to be sinusoidal. Further, it is shown through numerical examples that when the signal intensity P is large, the convergence speed of the extreme value search is faster when the dither signal is rectangular rather than sinusoidal.
  • the dither signal is an important signal in the extreme value search.
  • forcibly inputting a dither signal to the controlled process from the outside is not always preferable from the viewpoint of plant operation.
  • the dither signal is a signal for searching for the optimum value of the operation amount in the plant operation, and is not necessarily a signal necessary for the plant operation. Rather, giving such a signal to the process to be controlled disturbs the operation of the plant, which may be a risk of plant operation.
  • the control system 100 generates a dither signal by using a disturbance originally applied to the plant.
  • FIG. 4 is a block diagram showing an extreme value control system in the control system 100 of the first embodiment.
  • the dither signal generation unit 130 serving as a dither signal generator refers to the disturbance signal. It is a point that generates a signal.
  • the dither signal generation unit 130 is configured as a bandpass filter, and generates a dither signal by extracting a signal in a predetermined frequency band from the disturbance signal.
  • the control amount of the control target process often fluctuates according to the inflow amount of water to be treated, and is called inflow ratio control that changes the operation amount according to the inflow amount.
  • Control methods are often used.
  • inflow ratio control it is considered that changing the operation amount in accordance with disturbance is an operation generally permitted in normal plant operation.
  • the dither signal generated by using the disturbance applied to the plant is highly compatible with the plant operation, and it is considered that the extreme value control using such a dither signal is generally allowed.
  • FIG. 5 is a flowchart showing a flow of extreme value control by the control system 100 of the first embodiment.
  • the measurement information acquisition unit 110 acquires measurement information from the control target 200 (step S101).
  • the measurement information acquisition unit 110 outputs a disturbance signal included in the measurement information to the dither signal generation unit 130.
  • the measurement information acquisition unit 110 outputs control amount information included in the measurement information to the evaluation amount calculation unit 140.
  • the dither signal generation unit 130 generates a dither signal with reference to the disturbance signal output from the measurement information acquisition unit 110 (step S102).
  • the dither signal generation unit 130 outputs the generated dither signal to the extreme value control unit 150.
  • the evaluation amount calculation unit 140 calculates the evaluation amount at that time of the process to be controlled based on the control amount information output from the measurement information acquisition unit 110 (step S103).
  • the evaluation amount calculation unit 140 outputs evaluation amount information indicating the calculated evaluation amount to the extreme value control unit 150.
  • the extreme value control unit 150 performs extreme value control of the process to be controlled based on the evaluation amount information output from the evaluation amount information calculation unit 140 and the dither signal output from the dither signal generation unit 130 (step S104). ).
  • the extreme value control unit 150 determines whether or not the evaluation amount has converged as a result of the extreme value control (step S105). When it is determined that the evaluation amount has converged (step S105—YES), the extreme value control unit 150 ends the process. On the other hand, when it is determined that the evaluation amount has not converged (step S105—NO), the process returns to step S101, and the control system 100 continues the extreme value control.
  • FIG. 6 is a diagram illustrating a specific example of a water treatment plant controlled using the control system 100 of the first embodiment.
  • a water treatment plant 300 in FIG. 6 is a plant that performs a biological wastewater treatment process.
  • the biological wastewater treatment process performed by the water treatment plant 300 is a process to be controlled by the control system 100.
  • the water treatment plant 300 is provided with the first settling basin 310, the anaerobic tank 320, the anoxic tank 330, the aerobic tank 340, and the final settling basin 350. Transported by each pump.
  • the step inflow pump 410 (step inflow P in the figure) is a pump that bypasses the sewage that first flows into the sedimentation basin 310 into the anoxic tank 330.
  • the step inflow pump 410 is provided with a step flow rate sensor 411, and the flow rate of sewage that has been bypassed into the anoxic tank 330 by the step inflow pump 410 is measured.
  • the circulation pump 420 (circulation P in the figure) is a pump that circulates water between the anoxic tank 330 and the aerobic tank 340.
  • the circulation pump 420 is provided with a circulation flow rate sensor 421 and measures the flow rate of water circulated by the circulation pump 420.
  • the flocculant charging pump 430 (flocculation P in the figure) is a pump for charging the flocculant into the inflow portion of the final sedimentation basin 350 in order to remove phosphorus and improve the sludge sedimentation characteristics.
  • the flocculant charging pump 430 is provided with an injection amount sensor 431, and the amount of the flocculant charged by the flocculant charging pump 430 is measured.
  • the return sludge pump 440 (return P in the figure) is a pump that returns the sludge settled in the final sedimentation basin 350 to the anaerobic tank 320.
  • the return sludge pump 440 is provided with a return flow rate sensor 441, and the amount of sludge returned by the return sludge pump 440 is measured.
  • the surplus sludge extraction pump 450 (surplus P in the figure) is a pump that extracts excess sludge that has settled in the final sedimentation tank 350.
  • the excess sludge extraction pump 450 is provided with an excess sludge flow rate sensor 451, and the amount of sludge extracted by the excess sludge extraction pump 450 is measured.
  • the blower 460 is a blower that supplies oxygen to the aerobic tank 340.
  • the blower 460 is provided with an air volume sensor 461, and the air volume supplied by the blower 460 is measured.
  • various sensors are also installed in each facility such as the first sedimentation basin 310.
  • the contents measured by the sensors installed in each facility are as follows.
  • the inflow sensor 311 measures the inflow of water that first flows into the sedimentation basin 310.
  • the anaerobic tank phosphoric acid sensor 321 measures the concentration of phosphoric acid (PO4-P) in the anaerobic tank 320.
  • the anaerobic tank MLSS sensor 322 measures the MLSS concentration in the anaerobic tank 320.
  • the anaerobic tank ORP sensor 323 measures the oxidation-reduction potential difference (ORP) in the anaerobic tank 320.
  • the oxygen-free tank nitric acid sensor 331 measures the concentration of nitric acid (NO3-N) in the oxygen-free tank 330.
  • the aerobic tank DO sensor 341 measures the dissolved oxygen (DO) concentration in the aerobic tank 340.
  • the aerobic tank ammonia sensor 342 measures the ammonia (NH 4 -N) concentration in the aerobic tank 340.
  • the aerobic tank phosphoric acid sensor 343 measures the phosphoric acid (PO4-P) concentration in the aerobic tank 340.
  • the aerobic tank COD sensor 344 measures the COD concentration in the aerobic tank 340.
  • the discharge TN sensor 351 measures the total nitrogen (TN) concentration that is an index of the discharged water quality in the vicinity of the final sedimentation basin 350 or the discharge port.
  • the discharge TP sensor 352 measures the total phosphorus (TP) concentration serving as an index of the discharged water quality in the final sedimentation basin 350 or the vicinity of the discharge port.
  • the excess sludge concentration sensor 361 measures the concentration of excess sludge extracted by the excess sludge extraction pump 450.
  • control amount information of the biological wastewater treatment process is acquired by the various sensors installed in the water treatment plant 300 performing predetermined measurements.
  • the control system 100 that controls the water treatment plant 300 having such a configuration includes, as the evaluation amount calculation unit 140, the blower cost calculation unit 141, the return P cost calculation unit 142, the circulation P cost calculation unit 143, and the surplus P cost.
  • a calculation unit 144, an aggregation cost calculation unit 145, and an inflow cost calculation unit 146 are provided.
  • the control system 100 includes an aeration air amount control unit 151, a return total amount control unit 152, a circulation flow rate control unit 153, a surplus flow rate control unit 154, a flocculant input amount control unit 155, and a step as the extreme value control unit 150.
  • An inflow control unit 156 is provided.
  • control system 100 includes a water quality constraint cost conversion unit 160.
  • control system 100 controls the amount of operation of each pump and blower 460 for each pump and blower.
  • extreme value control performed for each pump and blower will be described.
  • the blower cost calculation unit 141 calculates the power consumption cost by the blower 460 based on the air volume measured by the air volume sensor 461.
  • the relationship between the air volume and the power consumption is obtained from the specification information of the blower 460.
  • the unit price of power is known information. Therefore, the power consumption cost can be calculated from the power consumption corresponding to the measured air volume and the power unit price.
  • the blower cost calculation unit 141 calculates an ammonia load amount represented by the product of the ammonia concentration measured by the aerobic tank ammonia sensor 342 and the discharge flow rate of the water discharged from the water treatment plant 300.
  • the discharge flow rate of the water discharged from the water treatment plant 300 is obtained by subtracting the excess sludge flow rate from the inflow amount to the water treatment plant 300.
  • the blower cost calculation unit 141 calculates the ammonia water quality cost by converting the calculated ammonia load amount into a cost based on the concept of drainage levy.
  • the drainage levy is a levy imposed on the person who drains according to the amount of drainage.
  • the cost required for water treatment is calculated using the concept of water distribution levy.
  • the idea of imposing a fixed levy on the amount of drainage is also described in Non-Patent Document 2 and Non-Patent Document 3.
  • the blower cost calculation unit 141 calculates a COD water quality cost obtained by converting the COD load amount into a cost based on the COD concentration and the discharge flow rate measured by the aerobic tank COD sensor 344.
  • the blower cost calculation unit 141 calculates the blower cost represented by the sum of the power consumption cost, the ammonia water quality cost, and the COD water quality cost as an evaluation amount for extreme control of the operation amount of the blower 460.
  • the water quality constraint cost conversion unit 160 compares the total nitrogen concentration measured by the discharge TN sensor 351 and the total phosphorus concentration measured by the discharge TP sensor 352 with the water quality regulation value, thereby limiting the water quality regulation. Calculate the water quality constraint cost by converting the condition into cost.
  • a penalty function method that is a method of incorporating a constraint condition as a cost in an optimization problem may be used.
  • the method described in the nonpatent literature 4 may be used.
  • the dither signal generation unit 130 generates a dither signal for extreme value search based on the inflow amount to the water treatment plant measured by the inflow amount sensor 411.
  • the time constant given to the water quality by the blower air volume is about 10 to several tens of minutes. Therefore, if this time constant is T, the dither signal generation unit 130 cuts a response component faster than the plant response speed 2 ⁇ / T with a high-pass filter. At this time, the dither signal 130 may be applied together with a high-pass filter that removes a periodic fluctuation pattern, if necessary.
  • a component that is slower than the response speed of the plant and that changes at a speed faster than the periodic fluctuation of the inflow rate is extracted from the disturbance signal. Then, a dither signal for extreme value control of the aeration air volume is generated by a band-pass filter whose gain is designed so that the amplitude of the dither signal satisfies the above design guidelines 2 and 4.
  • the aeration air volume control unit 151 is based on the blower cost calculated by the blower cost calculation unit 141, the water quality constraint cost calculated by the water quality constraint cost conversion unit 160, and the dither signal generated by the dither signal generation unit 130.
  • the operation amount of the blower 460 is subjected to extreme control so as to minimize the partial cost related to the operation of the blower 460 out of the total cost required for the operation of the water treatment plant.
  • the return P cost calculation unit 142 calculates the power consumption cost by the return sludge pump 440 based on the flow rate measured by the return flow rate sensor 441. The relationship between the flow rate and the power consumption is obtained from the specification information of the return sludge pump 440. The unit price of power is known information. Therefore, the power consumption cost can be calculated from the power consumption corresponding to the measured flow rate and the power unit price.
  • the return P cost calculation unit 142 calculates a nitric acid load represented by the product of the nitric acid concentration measured by the oxygen-free tank nitric acid sensor 331 and the discharge flow rate of the water discharged from the water treatment plant 300.
  • the return P cost calculation unit 142 calculates a nitrate water quality cost obtained by converting the calculated nitric acid load amount into a cost based on the concept of drainage levy.
  • the return P cost calculation unit 142 calculates a phosphor water quality cost obtained by converting the phosphoric acid load amount into a cost based on the phosphoric acid concentration and the discharge flow rate measured by the aerobic tank phosphoric acid sensor 321.
  • the return P cost calculation unit 142 calculates the return pump cost represented by the sum of the power consumption cost, the nitrate water quality cost, and the phosphorous water quality cost as an evaluation amount for extreme control of the operation amount of the return pump 440.
  • the return total amount control unit 152 converts the return pump cost calculated by the return P cost calculation unit 142, the water quality constraint cost calculated by the water quality constraint cost conversion unit 160, and the dither signal generated by the dither signal generation unit 130. Based on the total cost required for the operation of the water treatment plant, the amount of operation of the return pump 440 is subjected to extreme control so as to minimize the partial cost related to the operation of the return pump 440.
  • the circulation P cost calculation unit 143 calculates the power consumption cost by the circulation pump 420 based on the flow rate measured by the circulation flow rate sensor 421.
  • the relationship between the flow rate and the power consumption is obtained from the specification information of the circulation pump 420.
  • the unit price of power is known information. Therefore, the power consumption cost can be calculated from the power consumption corresponding to the measured flow rate and the power unit price.
  • the circulation P cost calculation unit 143 calculates a nitric acid load represented by the product of the nitric acid concentration measured by the oxygen-free tank nitric acid sensor 331 and the discharge flow rate of the water discharged from the water treatment plant 300.
  • the circulation P cost calculation unit 143 calculates a nitrate water quality cost by converting the calculated nitrate load amount into a cost based on the concept of drainage levy.
  • the circulation P cost calculation unit 143 calculates the circulation pump cost represented by the sum of the power consumption cost and the nitrate water quality cost as an evaluation amount for extreme control of the operation amount of the circulation pump 420.
  • the circulation flow rate control unit 153 converts the circulation pump cost calculated by the circulation P cost calculation unit 143, the water quality constraint cost calculated by the water quality constraint cost conversion unit 160, and the dither signal generated by the dither signal generation unit 130. Based on the total cost required for the operation of the water treatment plant, the amount of operation of the return pump 440 is controlled so as to minimize the partial cost related to the operation of the circulation pump 420.
  • the surplus P cost calculation unit 144 calculates the power consumption cost by the surplus sludge extraction pump 450 based on the surplus sludge flow rate measured by the surplus sludge flow rate sensor 451.
  • the relationship between the flow rate and the power consumption can be obtained from the spec information of the excess sludge extraction pump 450.
  • the unit price of power is known information. Therefore, the power consumption cost can be calculated from the power consumption corresponding to the measured flow rate and the power unit price.
  • the surplus P cost calculation unit 144 calculates the surplus sludge disposal cost based on the surplus sludge concentration measured by the surplus sludge concentration sensor 361, the surplus sludge flow rate measured by the surplus sludge sensor 451, and the sludge disposal unit price. calculate. Further, the surplus P cost calculation unit 144 calculates a phosphate load represented by the product of the phosphoric acid concentration measured by the aerobic tank phosphoric acid sensor 343 and the discharge amount of water discharged from the water treatment plant 300. calculate. The surplus P cost calculation unit 144 calculates a phosphor water quality cost obtained by converting the calculated phosphoric acid load amount into a cost based on the concept of drainage levy.
  • the surplus P cost calculation unit 144 uses the sum of the power consumption cost, surplus sludge disposal cost, and phosphorous water quality cost to evaluate the surplus sludge extraction pump 450 as an evaluation value for extreme control of the operation amount of the surplus sludge extraction pump 450. Calculate as
  • the surplus flow rate control unit 154 includes the surplus sludge extraction pump cost calculated by the surplus P cost calculation unit 144, the water quality constraint cost calculated by the water quality constraint cost conversion unit 160, and the dither signal generated by the dither signal generation unit 130. Based on the above, the operation amount of the excess sludge extraction pump 450 is subjected to extreme control so as to minimize the partial cost related to the operation of the excess sludge extraction pump 450 out of the total cost required for the operation of the water treatment plant.
  • the coagulation cost calculation unit 145 calculates the coagulant chemical cost by the coagulant injection pump 430 based on the input amount of the coagulant measured by the injection amount sensor 431.
  • the flocculant chemical cost can be calculated from the input amount of the flocculant and the chemical unit price.
  • the agglomeration cost calculation unit 145 calculates the excess sludge disposal cost based on the excess sludge concentration measured by the excess sludge concentration sensor 361, the excess sludge flow rate measured by the excess sludge flow rate sensor 451, and the sludge disposal unit price. calculate. Further, the aggregation cost calculation unit 145 calculates a phosphate load represented by the product of the phosphoric acid concentration measured by the aerobic tank phosphoric acid sensor 343 and the discharge amount of water discharged from the water treatment plant 300. To do. The aggregation cost calculation unit 145 calculates a phosphor water quality cost obtained by converting the calculated phosphoric acid load amount into a cost based on the concept of drainage levy.
  • the coagulation cost calculation unit 145 calculates the coagulation cost represented by the sum of the coagulant chemical cost, the excess sludge disposal cost, and the phosphorous water quality cost as an evaluation amount for extreme control of the operation amount of the coagulant charging pump 430. .
  • the flocculant input amount control unit 155 converts the aggregation cost calculated by the aggregation cost calculation unit 145, the water quality constraint cost calculated by the water quality constraint cost conversion unit 160, and the dither signal generated by the dither signal generation unit 130. Based on the total cost required for the operation of the water treatment plant, the amount of operation of the flocculant charging pump 430 is subjected to extreme value control so as to minimize the partial cost related to the operation of the flocculant charging pump 430.
  • the inflow cost calculation unit 146 calculates the power consumption cost by the step inflow pump 410 based on the flow rate measured by the step flow rate sensor 411.
  • the relationship between the flow rate and the power consumption is obtained from the specification information of the step inflow pump 410.
  • the unit price of power is known information. Therefore, the power consumption cost can be calculated from the power consumption corresponding to the measured air volume and the power unit price.
  • the inflow cost calculation unit 146 calculates an ammonia load amount represented by the product of the ammonia concentration measured by the aerobic tank ammonia sensor 342 and the discharge flow rate of the water discharged from the water treatment plant 300.
  • the discharge flow rate of the water discharged from the water treatment plant 300 is obtained by subtracting the excess sludge flow rate from the inflow amount to the water treatment plant 300.
  • the inflow cost calculation unit 146 calculates an ammonia water quality cost by converting the calculated ammonia load amount into a cost based on the concept of drainage levy.
  • the inflow cost calculation unit 146 calculates the nitrate water quality cost by converting the nitric acid load amount into a cost based on the nitric acid concentration measured by the anoxic tank nitric acid sensor 331 and the discharge flow rate. Similarly, the inflow cost calculation unit 146 calculates a phosphor water quality cost obtained by converting the phosphoric acid load amount into a cost based on the phosphoric acid concentration and the discharge flow rate measured by the aerobic tank phosphoric acid sensor 321.
  • the inflow cost calculation unit 146 calculates the inflow cost represented by the sum of the power consumption cost, the ammonia water quality cost, the nitrate water quality cost, and the phosphorous water quality cost as an evaluation amount for extreme control of the operation amount of the step inflow pump 410. To do.
  • the step inflow control unit 156 is based on the inflow cost calculated by the inflow cost calculation unit 146, the water quality constraint cost calculated by the water quality constraint cost conversion unit 160, and the dither signal generated by the dither signal generation unit 130.
  • the operation amount of the step inflow pump 410 is subjected to extreme value control so as to minimize the partial cost related to the operation of the step inflow pump 410 out of the total cost required for the operation of the water treatment plant.
  • control system 100 configured in a multi-loop configuration, for example, it is possible to implement extreme value control related to a plurality of manipulated variables in individual one-loop controllers, so that a simple and highly extensible extreme value control system can be configured. it can.
  • the dither signal generation unit 130 generates a dither signal by using the amount of water flowing into the water treatment plant 300 as a disturbance.
  • the dither signal is generated.
  • the signal generator 130 may generate the dither signal with any other event as a disturbance.
  • the dither signal includes SS (floating solid), COD (scientific oxygen demand), TN (total nitrogen), TP (total phosphorus), and absorbance spectrum. (Including UV), fluorescence spectrum (EEM), etc. may be generated as disturbances, and various influent water quality loads represented by products of water concentration and inflow measured by various water quality sensors are generated as disturbances. May be.
  • the control system 100 in order to maintain the final water quality of the wastewater-treated water, the control system 100 includes the water quality constraint cost conversion unit 160 that converts the constraints imposed on the wastewater treatment into costs.
  • the control system 100 may not include the water quality constraint cost conversion unit 160.
  • the various evaluation amounts calculated in the above specific examples may be calculated based on evaluation criteria and measurement information different from the above.
  • these evaluation criteria may not be used for calculation of the evaluation amount, but may be incorporated as a constraint condition such as a water quality constraint cost.
  • the dither signal generation unit 130 may generate a dither signal for each operation amount.
  • the dither signal generation unit 130 may generate different dither signals for each operation amount according to the influence of each operation amount on the control amount of the process to be controlled. This is effective when the time constant of the change in the evaluation amount with respect to the change in each operation amount is different, and is in accordance with the design guidelines for the various parameters of the extreme value control described above.
  • the control system 100 does not apply the dither signal necessary for the extreme value control of the process to be controlled to a disturbance that is originally applied to the plant, instead of a signal that is forcibly input from the outside. Generate by using.
  • the control system 100 of the embodiment can perform extreme value control of the process to be controlled while suppressing the influence on the plant operation.
  • the dither signal generation unit 130 may be configured to generate a dither signal in a time zone in which disturbance is likely to change.
  • the dither signal generation unit 130 may be configured to generate a dither signal when the amount of fluctuation per unit time exceeds a predetermined threshold, or disturbance is likely to fluctuate from the daily fluctuation pattern.
  • the dither signal may be generated in a time zone that is considered to be.
  • the dither signal generation unit 130 may generate a dither signal by referring to the disturbance signal as described above, or may generate a signal of another aspect such as a sine wave or a rectangular wave as the dither signal. .
  • the time zone in which disturbances are likely to fluctuate may be set according to the characteristics of the process to be controlled. For example, when the process to be controlled is a traffic control system, the above time zone is set based on the fluctuation pattern of the traffic volume. May be. For example, when the process to be controlled is a system that supplies resources such as a water distribution system and a power supply system, the time period may be set based on a resource consumption pattern.
  • the dither signal generation unit 130 may be configured to generate a dither signal based on the fluctuation amount of the disturbance.
  • the dither signal generation unit 130 may be configured to generate a dither signal when the fluctuation amount of the disturbance signal is equal to or less than a predetermined threshold.
  • the control amount of the controlled process is controlled.
  • the amplitude of the fluctuation is preferably large.
  • the dither signal generation unit 130 generates a dither signal when the fluctuation amount of the disturbance signal is equal to or greater than a predetermined threshold. It may be configured.
  • the dither signal generation unit 130 may be configured to generate a dither signal based on prediction of disturbance fluctuation. For example, the dither signal generation unit 130 generates a dither signal when the predicted value of the fluctuation amount of the disturbance exceeds a predetermined threshold value or when it is equal to or less than the predetermined threshold value. By configuring the dither signal generation unit 130 in this way, the control system 100 can perform extreme value control of the process to be controlled more quickly. Any method may be used as a method of predicting the fluctuation of the disturbance. For example, in the case of extreme value control of the water treatment plant 300, the fluctuation may be predicted by applying an autoregressive model or the like to the inflow amount. Further, as described above, the amount of inflow into the water treatment plant 300 often has a periodic variation pattern. Therefore, disturbance fluctuations may be predicted based on such fluctuation patterns. For example, the periodic variation pattern can be obtained by taking statistics of past measurement data.
  • the extreme value control method of this embodiment is a process of changing the input (operation amount) according to the output (control amount) of the process, and if the disturbance applied to the process can be measured or predicted,
  • the present invention can also be applied to processes other than processing processes.
  • FIG. 7 is a functional block diagram illustrating a functional configuration of the control system 100a according to the second embodiment.
  • the control system 100a of the second embodiment includes a measurement information acquisition unit 110a instead of the measurement information acquisition unit 110, a point including an extreme value control unit 150a instead of the extreme value control unit 150, and a history information storage unit 170. Is different from the control system 100 of the first embodiment in that In the description of FIG. 7, the same reference numerals as those in FIG.
  • the history information storage unit 170 is configured using a storage device such as a magnetic hard disk device or a semiconductor storage device.
  • the history information storage unit 170 stores control amount information measured in the past for the process to be controlled as history information.
  • the measurement information acquisition unit 110a acquires measurement information from the control target 200 and stores the control amount information included in the measurement information in the history information storage unit 170 as history information in association with the timing at which the control amount information is acquired. .
  • the extreme value control unit 150a performs the same extreme value control as the extreme value control unit 150 for the process to be controlled. Further, the extreme value control unit 150a determines an initial value of the operation amount in the extreme value search based on the history information. For example, the extreme value control unit 150a generates a daily transition pattern of the control amount of the process to be controlled based on the history information. For example, the extreme value control unit 150a generates a transition pattern as shown in FIG.
  • FIG. 8 is a diagram illustrating a specific example of the transition pattern generated based on the history information.
  • FIG. 8 shows an example of a transition pattern generated based on the measured value of the aeration air volume, which is one of the controlled variable information acquired for the controlled process, taking the water treatment plant 300 as an example.
  • representative values such as the average value, trim average value, and median value of the measurement values measured at the same time in a predetermined period in the past may be used.
  • a measurement value indicated by the information may be used.
  • the extreme value control unit 150a performs an extreme value search by setting a value corresponding to the execution timing of extreme value control in the generated transition pattern as an initial value of the manipulated variable. In addition, when an abrupt change or a discontinuous transition is observed in the generated transition pattern, the extreme value control unit 150a can change the transition pattern by an arbitrary interpolation method so as to alleviate such a change amount and the discontinuity. You may adjust.
  • the control system 100a of the second embodiment configured as described above sets the initial value of the operation amount in the extreme value control of the process to be controlled based on the control amount information measured in the past. By setting the initial value of the manipulated variable in the extreme value control in this way, the control system 100a improves the convergence speed of the extreme value search in the extreme value control of the process to be controlled in which the controlled variable periodically varies. be able to.
  • the extreme value control unit 150a performs an extreme value search by regarding the difference value between the measurement value indicated by the control amount information at the execution timing of the extreme value control and the measurement value indicated by the control amount information acquired in the past as an operation amount. May be.
  • the measurement value indicated by the control amount information acquired in the past may be a measurement value in the extreme value control of the previous control cycle, or may be a measurement value in the past at the same time.
  • the control system 100a can suppress the discontinuity of the change in the operation amount at the initial stage of the extreme value control. It becomes possible.
  • a disturbance signal acquisition unit that acquires a disturbance signal indicating disturbance
  • a control amount information acquisition unit that acquires control amount information indicating a control amount of the control target process
  • the control In the control of the target process, a dither signal generation unit that generates a dither signal for changing an operation amount given to the control target process with reference to the disturbance signal, and the control target process based on the control amount information
  • An evaluation value calculation unit that calculates an evaluation value that serves as an index for evaluating the control amount of the control unit, and a search for an extreme value of the evaluation value by varying the operation amount based on the dither signal generated by the dither signal generation unit
  • an extreme value control unit that performs extreme value control for adjusting the manipulated variable while controlling the extreme value while suppressing the influence on the plant operation. Door can be.

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6098010A (en) * 1997-11-20 2000-08-01 The Regents Of The University Of California Method and apparatus for predicting and stabilizing compressor stall
JP5300827B2 (ja) * 2010-11-18 2013-09-25 株式会社東芝 生物学的廃水処理装置
JP2014135851A (ja) * 2013-01-10 2014-07-24 Kyushu Univ 共振周波数探索装置、共振周波数探索方法及びプログラム

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6098010A (en) * 1997-11-20 2000-08-01 The Regents Of The University Of California Method and apparatus for predicting and stabilizing compressor stall
JP5300827B2 (ja) * 2010-11-18 2013-09-25 株式会社東芝 生物学的廃水処理装置
JP2014135851A (ja) * 2013-01-10 2014-07-24 Kyushu Univ 共振周波数探索装置、共振周波数探索方法及びプログラム

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