JP2001084005A - Process controller and process controlling method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a process controller and a process controlling method capable of accurately controlling a process variable having a process variable whose response time delay is long, i.e., from several minutes to 20 minutes. SOLUTION: A predictive control controller 380 is provided with a control device simulation means 212 for simulating the steady-state characteristic and transient response characteristic of a normal control controller 375 and a plant simulation means 211 for simulating the steady-state characteristic and transient response characteristic of a plant 100, calculates the future value u1(t+τ) of a manipulated variable by using these simulation means 212, 211 and inputs the future value u1(t+τ) of a manipulated variable to a manipulated variable correction value calculation means 213, which calculates and outputs manipulated variable correction values w1(t), w2(t) for correcting the transient state of the manipulated variable of the controller 380.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a process control apparatus which is applied to, for example, a thermal power plant and predicts a future state of a process, determines an operation amount based on the prediction result, and controls the process.

[0002]

2. Description of the Related Art As a response characteristic of a process, there is one having a large response time delay. For example, in a thermal power plant,
The time from the change in the fuel input to the change in the main steam temperature is long, and the time constant is about several minutes to 20 minutes. In a system having a large response time delay, there is a limit in improving the control deviation (main steam temperature deviation) by only the normal feedback control.

On the other hand, there is a prediction control method in which a future process state is predicted in advance and an operation amount is determined based on the predicted value. As a predictive control method, for example, a conventional technique disclosed in the following document is known.

(1) Japanese Patent Application Laid-Open No. 9-274507 (2) Japanese Patent Application Laid-Open No. 11-085214 (3) Japanese Patent Application Laid-Open No. 11-007307 A process model is composed of the lumped parameterized model and the dead time model, and the input variables are estimated by the state observer.
A method for calculating a future value of a process quantity is disclosed.
The prior art (2) discloses a method of constructing a model in which a dead time of a process to be controlled is ignored and inputting a feedforward signal to the model to calculate a future value of a process amount. The prior art (3) discloses a method of inputting a current value of a process amount obtained by a state observer and a future disturbance amount to a model predictor and calculating a future value of the process amount. .

[0005]

However, when predicting the future value of a process having a large response time delay, the prediction accuracy of the future value of the process amount may be reduced, and the control performance of the process may be reduced. This is because an operation amount used for calculating a future value of the process amount is not predicted, and thus an error in a closed loop system between the process amount and the operation amount increases.

On the other hand, the above-mentioned prior arts (1) to (3) include means for calculating a future value of a process amount (control amount) to be controlled or a method for improving the prediction accuracy of the future value. Although the adjusting means is described, there is no description about the calculating means of the future value of the manipulated variable or the means for improving the prediction accuracy of the future value of the manipulated variable. This is because it is assumed that the prediction time is several seconds to several minutes and the operation amount is represented by a simple response waveform in the above-described conventional technology.

For example, in a thermal power plant, the manipulated variables for controlling the steam temperature include the fuel flow rate and the spray water flow rate of the steam temperature reducer. At this time, when the response waveform of the steam temperature is analyzed by frequency analysis or the like, the temperature change in the period of several minutes to 20 minutes is caused by the fuel flow rate, but the temperature change in the period of 5 seconds to 1 minute is caused by the flow rate of the spray water. You can see that it is. The spray water flow control system is a control system that combines a proportional-integral controller, a non-linear function, a switch, and the like. The spray water flow rate shows a complex response to the steam temperature. Therefore, in the related art in which the operation amount is assumed to be a simple response waveform, the error in the future value of the spray water flow rate becomes the prediction error of the steam temperature several minutes to 20 minutes ahead, and the control performance deteriorates.

An object of the present invention is to provide a process control apparatus and method capable of accurately controlling a process amount having a long response time delay of several minutes to 20 minutes.

[0009]

In order to achieve the above object, a first means is a prediction means for predicting a future value of a controlled variable to be controlled, and a predetermined value based on a prediction result by the prediction means. A control unit for executing control, the control unit comprising: an operation amount calculating unit that determines an operation amount of each process based on a future value predicted by the prediction unit, wherein the prediction unit controls the predicted control. A future value of the manipulated variable, which is an output of the control device, is predicted from a future value of the amount, and the manipulated variable calculation means is configured to determine a correction value of the manipulated variable from the predicted future value of the manipulated variable.

In this case, the operation amount calculating means may be configured to determine a correction value of the operation amount based on the future value of the control amount predicted by the prediction means in addition to the future value of the operation amount. it can. Further, the prediction means may be configured to predict a future value of the operation amount, and the operation amount calculation means may be configured to determine correction values for a plurality of operation amounts using the predicted future value.

A second means for predicting at least one of a steam temperature of the thermal power plant, a fuel flow rate of the plant, a spray flow rate of the steam temperature desuperheater, a recirculation gas flow rate and a future value of the gas distribution damper; Calculating at least one manipulated variable for determining at least one of a fuel flow rate, a steam temperature desuperheater spray flow rate, a recirculation gas flow rate, and a gas distribution damper of the plant as a manipulated variable based on the measured value of the steam temperature of the plant. Means for predicting at least one future value of a fuel flow rate, a steam temperature desuperheater spray flow rate, a recirculation gas flow rate and a gas distribution damper, and wherein the manipulated variable calculating means includes the predicting means Is configured to determine at least one correction value of the manipulated variables from the at least one future value predicted by (1).

In this case, the prediction means predicts the at least one future value and the future value of the steam temperature,
The operation amount calculation means may be configured to determine at least one correction value of the operation amounts from the at least two future values.

Further, a plurality of the predicting means are provided, and the predicting means calculates and outputs predicted values of a plurality of manipulated variables having at least one of a predicted time and a predicted cycle which are different from each other. A plurality of future values of the process amount may be predicted, and the manipulated variable calculation means may be configured to determine at least one correction value of the manipulated variables based on the predicted future value.

At least one of the predicting means predicts a future value of the process amount at the next predicted time, or the predicting means records a measured value of the operation amount in the actual machine controller as a time-series signal, At the time of calculating the future value, a time-series signal of the manipulated variable may be output as a predicted value, and the manipulated variable calculating means may determine a correction value of the manipulated variable based on the predicted future value.

In these cases, the future value is a predicted value based on a lapse of time corresponding to a period from a change in the fuel input amount to a change in the main steam temperature.

The third means is a process control method for predicting a future value of a controlled variable to be controlled and executing a predetermined control based on the predicted future value. , The future value of the manipulated variable, which is the output of the control device, is predicted, and the correction value of the manipulated variable is determined from the predicted future value of the manipulated variable.

[0017]

Embodiments of the present invention will be described below with reference to the drawings.

1. First Embodiment The first embodiment is an example in which the present invention is applied to steam temperature prediction control of a thermal power plant. Hereinafter, description will be made with reference to the drawings.

1.1 Schematic Configuration of Coal-Fired Power Plant FIG. 2 shows an example of the basic configuration of a coal-fired power plant 100 according to this embodiment. In the figure, in a coal-fired thermal power plant 100, fuel and air are supplied to a burner 160 by a boiler 150 and burned, and feed water circulated by a feed water pump 140 is evaporated by a furnace water wall 152. Further, the steam heated to the superheated state by the superheater 154 passes through the turbine control valve 121 to the high-pressure turbine 1.
The high-pressure turbine 130 is driven by 30. The steam that has passed through the high-pressure turbine 130 is heated again by the reheater 156 and enters the low-pressure turbine 120. The steam introduced into the high-pressure turbine 130 and the low-pressure turbine 120 in this manner causes the high-pressure turbine 130 and the low-pressure turbine 120
Is rotated, and power is generated by the generator 110 by this rotation.

Hereinafter, the steam at the inlet of the high-pressure turbine 130 is referred to as main steam, and the steam at the inlet of the low-pressure turbine 120 is referred to as reheat steam. In order to control the temperatures of the main steam and the reheat steam, the superheater 154a and the superheater cooler 154a are provided at the inlets of the reheater 156.
And a reheater desuperheater 156a. Temperature reducers 154a, 156
Low-temperature water after passing through the water supply pump 140 is guided to a, and is injected into high-temperature steam through the desuperheater spray water amount control valves 154b and 156b, respectively. The reheater desuperheater 156a is an emergency and operates only when the reheat steam temperature exceeds a set value.

The boiler 150 is provided with a gas recirculation fan 142 for recirculating the combustion gas, which also serves as one of the means for adjusting the steam temperature. Also,
In some plants, a partition wall is provided between the superheater and the reheater to divide the gas flow path into two, and a gas distribution damper for adjusting the distribution of each gas flow rate is provided. In this case, the gas distribution damper also serves as a means for adjusting the steam temperature.

In the thermal power plant, in addition to the above components, there are also devices such as a condenser 125 for cooling the steam after driving the turbine with cooling water 126 and a combustion exhaust gas treatment device 170. The gas that has passed through the exhaust gas treatment device 170 is released from the chimney 175 to the atmosphere.

1.2 Control Configuration 1.2.1 Detector The operating state of the plant 100 is controlled by the generator output measuring device 11.
1. Main steam temperature (superheater outlet steam temperature) measuring device 122,
Superheater inlet steam temperature measuring instrument 127, main steam pressure measuring instrument 1
23, reheat steam (reheater outlet steam temperature) temperature measuring device 12
4. Measured by a data measuring device such as a reheater inlet steam temperature measuring device 124a and transmitted to the operation control device 300. The plant is provided with other devices for measuring various process quantities, and the operation control device 300 also captures the measured values. Here, the detailed description thereof is omitted.

1.2.2 Control Device 1.2.2.1 Outline The operation control device 300 grasps the operating state of the plant based on these process data, and controls the fuel flow rate so that the plant is in a desired state. Devices such as the control valve 162, the air flow control valve 161, the turbine control valve 121, and the water supply pump 140 are controlled.

In a thermal power plant, there is a control variable having a relatively long response time, such as a steam temperature, and this control is generally considered to be difficult. Therefore, a predictive control technique that is a feature of the present invention is applied to control of the main steam temperature. The purpose of predictive control is to improve the control accuracy by predicting the future behavior of a process value having a large time constant and a slow response, and determining the manipulated variable in advance.

The functional configuration of the operation control device 300 will be described. As shown in FIG. 3, it is composed of a master control section 370 and a sub-loop control section 390 based thereon. The master controller 370 includes a normal controller 375 and a steam temperature prediction controller 380 to which the present invention is applied.
And divided into The master control unit 370 creates various operation amount command signals based on the load command signal, and determines the operation amount by adding correction based on measured values such as the steam temperature, the steam pressure, and the gas O ₂ concentration to the values.

The sub-loop control section 390 includes a turbine control controller 391 and a feed water pump controller 39
2. Fuel flow control valve controller 393, push fan controller (air control controller) 394, induction fan controller (exhaust gas control controller) 395,
There is a spray flow controller 396 and a gas recirculation flow controller 397. These controllers are mutually connected to the signal transmission network 400, and can exchange signals. The output from each controller of the sub-loop control unit 390 is sent to each actuator 101 of the plant 100 to operate the device.

The operation control device 300 has a hardware configuration shown in FIG. That is, the operation control device 300
Is connected to the signal transmission network 400 via the external input interface 301 and the output interface 302. The operation control device 300 further includes an arithmetic unit 304 and a storage unit 304, and the arithmetic processing unit 304 calculates and generates various command signals while storing the received signal in the storage device 303 as necessary. The command signal is sent to the control target via the output interface 302.

The external input interface 301 includes an external input device 9 comprising a keyboard 930 and a mouse 940.
00 and the data storage device 500 are connected. The output interface 302 has an image display device (CR
T) 910 and the magnetic disk drive 950 are connected and function as an interface with the operator.

1.2.2.2 Master Control Unit Next, a master control unit 370 to which the present invention is applied will be described with reference to FIG.

Normally, the controller 375 includes a number of controllers. Here, the first controller 201 and the second controller 202 are representative controllers for controlling the control amount y.
showed that. In the present embodiment, u1 corresponds to the fuel flow rate command, and u2 corresponds to the temperature reducer spray water flow rate command. Further, y is a control amount and corresponds to the steam temperature. The subscript t of the operation amount and the control amount is the current time, and τ is the predicted time.

The normal control controller 375 uses the switching means 203 to control the output of the plant 100
y (t) or the control amount prediction value y (t + τ) which is the output of the prediction control controller 380 is selectively input as a feedback signal, and the first controller 201 and the second controller 20
In step 2, the manipulated variables u1 (t) and u2 (t) are calculated.

The first controller 201 controls a controlled variable (steam temperature).
The operation amount (fuel flow rate command) u1 is calculated so that y becomes equal to the target value v. In the present embodiment, the controlled variable having a slow response time of several minutes to 20 minutes is controlled. The second controller 202 calculates the manipulated variable (superheater spray flow rate command) u2 such that the control variable (steam temperature) y matches the target value v, and the controlled variable with a response time of several seconds to several minutes. Control.
Conventionally, the first and second controllers 201 and 202 are formulas for realizing proportional integral control and integral control, but in the present embodiment, the form of these controllers 201 and 202 does not matter.

In this embodiment, the manipulated variable correction values w1 and w2, which are the outputs of the predictive control controllers, are added to the outputs of the first controller 201 and the second controller 202, respectively. And u'1
u'2 is input to the plant as a new manipulated variable.

1.2.2.3 Steam Temperature Prediction Controller Next, a steam temperature prediction controller 38 to which the present invention is applied.
0 will be described with reference to FIG.

The steam temperature controller 380 includes a plant simulation unit 211, a control unit simulation unit 212, and a manipulated variable correction value calculation unit 213, and performs various predictions based on these models.

The plant simulating means 211 corresponds to the plant 100
Is a reproduction of the steady-state characteristics and transient response characteristics of a control variable predicted value y1 (t + τ-Δt) and u2 (t + τ-Δt). τ) is output. At this time
Is the calculation cycle.

The control device simulating means 212
0 is a reproduction of the steady-state characteristic and the transient response characteristic, and the predicted value v (t + τ-Δt) and the predicted value y (t + τ-
Δt) is input and the manipulated variable prediction values u1 (t + τ) and u2 (t + τ) are output. v (t + τ−Δt) is given as a function or a constant of the power generation target value, and the future value is obtained from the planned value of the power generation target value.

The manipulated variable correction value calculating means 213 inputs the time series data of the control variable predicted value calculated by the plant simulating means 211 and at least one controlled variable predicted value calculated by the control device simulating means 212, and From the value of the value, manipulated variable u1
And values w1 (t) and w2 (t) for correcting u2 are output.

1.2.2.4 Model Predictive Control Next, the plant simulation means 211 and the control device simulation means 21
2 will be described with reference to the flowchart of FIG.

The steam temperature prediction controller 380 determines the time
Control amount y (t-Δt) at t-Δt, manipulated variable u1 (t-Δt), u2 (t
-Δt) and a target value v (t-Δt) are input (step 50).
1). At this time, the control amount and the operation amount are measured values of the plant 100 and the control device 300.

Next, the prediction time τ is set to 0, and the steam temperature prediction controller 380 is initialized (step 50).
2). At this time, the plant simulating means 211 and the control device simulating means 212 are initialized so that the predicted value of the controlled variable and the predicted value of the manipulated variable at the time t-Δt coincide with the measured values of the controlled variable and the manipulated variable.

Next, the plant simulation means 211 calculates a predicted control value y (t + τ) at time t + τ using the function f1 (step 503). Further, the control device simulation means 212
Calculates the manipulated variable predicted values u1 (t + τ) and u2 (t + τ) and the target value predicted value v (t + τ) at time t + τ using the functions f2, f3 and f4 (step 504). . The functions f1 to f3 are functions for reproducing the steady-state characteristics and the transient response characteristics of the plant and the control device, such as differential equations and nonlinear functions. In the figure, the control variable predicted value y (t + τ) and the manipulated variable predicted values u1 (t + τ), u2 (t
Although only a function for calculating + τ) is shown, it actually includes a function for calculating a process amount necessary and sufficient to reproduce the steady-state characteristics and the transient response characteristics of the plant and the control device. The function f4 is given as a function or a constant of the power generation target value, and the future value is obtained from the planned power generation target value.

After calculating the predicted value of the controlled variable and the predicted value of the manipulated variable, if the predicted time τ is less than the target value T of the predicted time, ie, does not reach the target value of the predicted time (N in step 505).
o), Δt is added to τ (step 506), and the above function
Steps f1 to f4 are repeatedly executed (steps 503 and 50).
4). If the predicted time τ has reached the target value T of the predicted time, that is, if τ ≧ T (Y in step 505)
es) End the repeated calculation. Plant simulation means 21
1 and the control device simulation means 212 output the control amount predicted value y from time t to time t + T and the manipulated variable predicted values u1 and u2 as time series data as a calculation result (step 5).
07).

1.2.2.5 Plant Simulating Means Next, the plant simulating means 211 shown in FIGS. 4 and 5 will be described with reference to FIG. FIG. 6 is a block diagram showing the dependency of input / output variables of a differential equation, which is a component of the plant simulation means 211, for each device constituting the thermal power plant. Arrows in the block diagram collectively represent a plurality of process quantities such as flow rate (symbol G), pressure (symbol P), and enthalpy (symbol H). In the block, the flow rate, the pressure, and the enthalpy (the temperature (symbol T) is used instead of the enthalpy in the combustion gas) are input, and the calculated values are output to other blocks.

In some blocks, an operation amount is input from the control device simulating means and a process amount is output. Hereinafter, each block will be described.

The combustion calculation block 220 calculates the air flow rate G
a, from the fuel flow rate Gc, the recirculation gas flow rate Ggr, and the recirculation gas temperature Tgr, the combustion gas flow rate Gg and the combustion gas temperature T
Calculate g. The fuel flow rate Gc corresponds to the manipulated variable u1 (t + τ) in FIGS. Regarding the combustion gas flow rate Gg and the combustion gas temperature Tg, an introduction to heat calculation III-combustion calculation-
(Yamazaki Masakazu, Energy Conservation Center, May 1994)
It is not described here.

1.2.2.5.1 Simulating method of water wall block The water wall block 221 calculates the steam temperature and the water wall pipe temperature by heat balance calculation, and includes a supply water flow rate Gs, a gas temperature Tg, and a gas flow rate. Gg and superheater pressure Psh are input, and water wall steam flow rate Gww, water wall steam enthalpy Hww, outlet gas temperature Tgww, outlet gas flow rate Ggww, water wall pressure Pw
Output w. The supply water temperature Ts is a boundary condition and is constant.

The water wall block 221 can be simulated using the following equations.

In Equation 1, the flow rate in the water wall is calculated from the flow rate of the supplied water and the pressure change in the water wall.

[0051]

(Equation 1)

In equation (2), the pressure in the water wall is calculated. The pressure in the water wall approximately adds the pressure difference from the downstream superheater pressure.

[0053]

(Equation 2)

In equation (3), the steam temperature is calculated from the steam enthalpy and the steam pressure. Here, the function fs represents a reference to the steam table, and it is assumed that the contents of the steam table (edited by the Japan Society of Mechanical Engineers, 1980) are implemented in a computer.

[0055]

(Equation 3)

In equation (4), the steam density is calculated from the steam enthalpy and the steam pressure.

[0057]

(Equation 4)

In Equation 5, the steam enthalpy is calculated from the heat balance of the steam inside the water wall.

[0059]

(Equation 5)

In Equation 6, the pipe temperature is calculated from the heat balance of the water wall pipe.

[0061]

(Equation 6)

Here, Vww is the water wall volume, ρww is the water wall density, Aww is the water wall heat transfer area, βww is the water wall convection heat transfer coefficient, Twav is the average steam temperature in the water wall, and Tm is the water wall pipe temperature. Means fs stands for steam table reference.

1.2.2.5.2 Simulating method of superheater desuperheater spray block and reheater desuperheater spray block The superheater desuperheater spray block 222 is represented as a mixed model of two kinds of fluids. Then, from the spray flow rate command Gs1 from the control device simulating means, the steam flow rate Gww and the steam enthalpy Hww calculated by the water wall block 221, the superheater desuperheater spray outlet flow rate Gsp1 and the outlet enthalpy Hs
Output p1. The spray outlet flow rate Gsp1 and the spray outlet enthalpy Hsp1, which are the outputs of the block, can be calculated by the following equations.

In the equation 7, the steam enthalpy at the outlet of the superheater desuperheater is calculated from the calorific values of the two kinds of fluids.

[0065]

(Equation 7)

In equation 8, the total flow rate of the two types of fluids is calculated.

[0067]

(Equation 8)

It should be noted that the reheater / temperature reducer spray block 225 is used.
Has a similar configuration.

1.2.2.5.3 Simulating method of superheater block and reheater block The superheater block 223 includes a superheater desuperheater spray outlet steam flow rate Gsp1, a spray outlet steam enthalpy Hsp1, and a water wall outlet combustion. Gas flow rate Ggww, water wall outlet combustion gas temperature T
gww and the high-pressure turbine control valve steam flow rate Ght are input, and the superheater outlet steam flow rate Gsh, the superheater outlet steam enthalpy Hsh, the superheater outlet gas flow rate Ggsh, the superheater outlet gas temperature Tgsh, and the superheater steam pressure Psh are output.

In equation (9), the steam pressure in the superheater is calculated from the difference between the flow rates of the steam flowing upstream and downstream of the superheater.

[0071]

(Equation 9)

In Equation 10, the average steam temperature is calculated from the average steam enthalpy in the superheater and the steam pressure.

[0073]

(Equation 10)

In equation 11, the steam density is calculated from the superheater outlet steam enthalpy and the steam pressure.

[0075]

[Equation 11]

In Equation 12, the average gas temperature is calculated from the superheater inlet gas temperature and the outlet gas temperature.

[0077]

(Equation 12)

In Equation 13, the steam enthalpy is calculated from the heat balance of the steam inside the superheater.

[0079]

(Equation 13)

In equation 14, the pipe temperature is calculated from the heat balance of the superheater pipe.

[0081]

[Equation 14]

In equation 15, the gas temperature is calculated from the heat balance of the combustion gas outside the superheater.

[0083]

(Equation 15)

Here, Vsh is the superheater volume, ρsh is the superheater steam density, Ash is the superheater heat transfer area, βsh is the convective heat transfer coefficient of water wall, Tshav is the average steam temperature in the superheater, M
sh is the superheater pipe mass, Csh is the superheater pipe specific heat, Tm
sh is the superheater pipe temperature, γsh is the convective heat transfer coefficient from the gas to the water wall, Tgshav is the average gas temperature in the superheater, Vg
sh is the superheater gas volume, ρgsh is the superheater gas density, C
gsh means superheater gas specific heat. fs represents a reference to the vapor table.

The reheater block 226 has the same configuration.

1.2.2.5.4 Simulating System for High-Pressure Turbine Block and Medium / Low-Pressure Turbine Next, the high-pressure turbine block 224 will be described.
The high-pressure turbine block 224 inputs the superheater outlet steam enthalpy Hsh and the superheater outlet pressure Psh, and receives the turbine steam flow rate Gto and the turbine outlet steam enthalpy Hto.
Is calculated.

Formula 16 calculates the main steam flow rate from the steam pressure and the turbine control valve opening. At this time, the pressure fluctuation due to the main steam temperature is corrected.

[0088]

(Equation 16)

Equations (17), (18) and (19) calculate the exit steam enthalpy from the steam enthalpy and the turbine efficiency.
The turbine efficiency η indicates the rate at which steam energy is required for driving the turbine, and is a constant that varies depending on the type of steam turbine or the plant.

[0090]

[Equation 17]

[0091]

[0092]

(Equation 18)

[0093]

[0094]

[Equation 19]

Equation 20 calculates the power generation amount from the turbine inlet enthalpy, the outlet steam enthalpy, and the steam flow rate.

[0096]

(Equation 20)

Here, Fcvh is a turbine control valve opening degree,
fht is a turbine pressure flow characteristic function, Tb is a turbine reference temperature, Ssh is steam entropy, H'to is a turbine outlet reference enthalpy, Hto is a turbine outlet steam enthalpy, and η is a turbine efficiency. Fs means a reference to the steam table.

The middle / low pressure turbine block 227 can be simulated with the same configuration, but the opening / closing valve of the middle / low pressure turbine is always 100%.

The power generation amount of the plant can be calculated from the power generation amount Eh of the high-pressure turbine and the power generation amount El of the middle-low pressure turbine by the following equation.

[0100]

(Equation 21)

1.2.2.5.5 Simulating Method of Recirculation Fan Block Next, the recirculation fan block 228 will be described.
The recirculation fan block 228 has a reheater outlet gas temperature T
The recirculation gas temperature Tgr and the recirculation flow rate Ggr are output by inputting the grh and the recirculation flow rate command GgrD. The recirculation gas temperature Tgr is equal to the reheater outlet gas temperature Tgrh, and the recirculation flow rate Ggr is equal to the recirculation flow rate command GgrD.

The plant simulation means 211 is described by a system of differential equations shown in the blocks described above.
These differential equations are executed once every calculation cycle Δt to calculate the process amount. Further, among these process quantities, the control quantity prediction value y (t + τ + Δt) is represented by the control device simulation means 2.
12 or to the manipulated variable correction value calculation means 213.

1.2.2.6 Control Device Simulating Means Next, the control device simulating means 212 shown in FIGS. 4 and 5 will be described. The control device simulation means 212 is adjusted to match the steady-state characteristics and the transient response characteristics of the normal control controller 375. However, when the configuration of the control controller 375 is known from a block diagram or the like, Is described in a program or the like, it is desirable to implement this configuration as it is in the control device simulation means 212 as it is. At this time, if the block diagram includes an unnecessary part or a control amount outside the modeling range of the plant simulation means, the controller simulation means 212 and the controller 375 output an equivalent value within the target operation range. It is sufficient to remove unnecessary portions while leaving a necessary and sufficient system to perform the process, or to input a signal for simulating these process amounts to the control device simulating means 212.

Next, a case where the control system diagram of the normal controller 375 is unknown will be described with reference to FIG. When the system diagram of the normal control controller 375 is unknown, a reference model 240 of the control device is constructed, and an error between the actual machine operation result and the reference model 240 is identified by the controller identification means 241.

The reference model 240 is the first controller 240
a and the second controller 240b, and the control constants of the first controller 240a and the second controller 240b are adjusted in advance so that the steady-state characteristics of the normal controller 375 can be reproduced. It is desirable that the configurations of the first and second controllers 240a and 240b be constructed in accordance with a plant control method described in a plant operation plan or the like.

Next, the controller identification means 241 will be described. The controller identification means 241 has two operation modes of control system identification and control system estimation. First, the operation method at the time of control system identification will be described. At the time of control system identification, control system errors Δu1 (t) and Δu2 (t) in the reference model are calculated from the difference between the manipulated variables u1a (t) and u2a (t) of the reference model. The controller identification means 241 includes a control deviation Δy (t), a control system error Δu1
(t) and Δu2 (t), and adjust the internal parameters of the controller identification means 241 so as to output the errors Δu1 (t) and Δu2 (t) from the control deviation Δy (t) using the least square method or the like. I do. The outputs Δu1a (t) and Δu2a (t) of the controller identification means 241 are Δu1
(t) and Δu2 (t) are output as they are, and
2 outputs the same response as the controller 375.

When the prediction control controller 380 starts the prediction control, the controller identification means 241 operates in the control system estimation mode. The controller identification means 241 calculates the control deviation Δy
(t), and outputs control system error estimated values Δu1a (t) and Δu2a (t). At this time, the control system errors Δu1 (t) and Δu2 (t) are input, but the values are ignored.

In the control system estimation mode, the output value of the control device simulation means 212 is obtained by the following equation.

[0109]

(Equation 22)

[0110]

(Equation 23)

As a method of realizing the controller identification means 241, ARMAX (Auto
Regressive Moving Average eXogenius) model or neural network can be used. ARMA
The method of realizing the X model is detailed in FORTRAN 77 time series analysis programming (Genshiro Kitagawa, Iwanami Shoten, April 1994). In addition, the realization method by the neural network is a neurocomputer (Shigiri Kiriya et al., Technical Review, 89
February).

1.2.2.7 Operation Amount Correction Value Calculation Means Next, the operation amount correction value calculation means 213 in FIG. 1 will be described with reference to FIG. Manipulated variable correction value calculation means 213
Input the operation amount prediction values u1 (t), ..., u1 (t + T), analyze the waveform of u1, and adjust the operation amount correction values w1 (t) and w2 (t) for u1 and u2.
The operation amount waveform separation means 250 and the first
And second gain compensating means 251a, 251b, phase compensating means 252, and first and second data output means 25.
4a and 254b.

The waveform separating means 250 calculates the manipulated variable predicted value u1
From the time series data of (t), ..., u1 (t + T) and the manipulated variable reference value us, a deviation from the reference value of the manipulated variable predicted value is obtained, and this deviation is determined as a frequency equal to or higher than the separation target frequency fHz. Component data p1
.., p1 (t + T) and data p2 (t),..., p2 (t + T) of frequency components lower than the frequency fHz. In the present embodiment, since u1 is the superheater desuperheater spray flow rate, it means that the predicted value of the spray flow rate is separated into the low frequency component p1 of the spray flow rate and the high frequency component p2 of the spray flow rate. As a method of realizing the waveform separating means 250, there is a method using a fast Fourier transform, a wavelet transform, a low frequency filter, or the like. In the present embodiment, any method may be used.

The first gain compensating means 251a applies gain compensation to the separated high frequency component of the manipulated variable p1.
The gain Ka is obtained from the sensitivity of the temperature to the spray flow rate by the following equation.

[0115]

(Equation 24)

Here, the gain Ka may be calculated from the design value of the plant or the operation results. Also, the gain Ka
May be used as a function of the power generation load, and the gain may be changed for each power generation load. The operation amount q1 is obtained by the following equation by the gain compensation of the operation amount p1.

[0117]

(Equation 25)

Since the manipulated variable q1 calculated by Equation 25 is time-series data, the time-series data is temporarily recorded in the data output means 254a and output as w1 (t) at each time t + τ.

On the other hand, the second gain compensating means 251b
The gain correction is similarly applied to the low frequency component of the separated operation amount p2. The gain Kb is obtained from the sensitivity of the temperature to the fuel flow rate by the following equation.

[0120]

(Equation 26)

Here, the gain Kb may be calculated from the design value of the plant or the operation results. Also, the gain Kb
May be used as a function of the power generation load, and the gain may be changed for each power generation load. The operation amount q2 is obtained by the following equation by the gain compensation of the operation amount p2.

[0122]

[Equation 27]

Since the manipulated variable q2 is a low frequency component of the spray flow rate, in the present embodiment, the phase of the spray flow rate is further converted by adding phase compensation to q2 to a correction value of the fuel flow rate.
Here, the operation amount r2 is obtained by adding a phase advance compensation so that the operation amount q2 compensates for the phase difference TL, with the phase difference of the steam temperature with respect to the fuel flow rate being TL. The operation amount r2 is obtained by the following equation.

[0124]

[Equation 28]

Here,

[0126]

(Equation 29)

The phase lead compensation may use a time differential value or an incomplete differential value of the manipulated variable q2.

Since the manipulated variable r2 obtained by Equation 29 is time-series data, its value is temporarily recorded in the data output means 254b and output as w2 (t) at each time t + τ.

According to the embodiment described above, the manipulated variable correction values w1 (t) and w2 (t) are calculated from the time t to the target time T. Therefore, the manipulated variable correction value calculation means 21
The predictive control controller 380 including 3
It operates only once, and then outputs a correction value until time T.

The above operation is an operation method of the prediction control controller 380, and the control amount and the process amount may be predicted for each calculation step, and the correction value may be sequentially calculated as a result. In the operation that calculates the correction value sequentially for each calculation interval time, prediction with higher accuracy is possible compared to the above operation,
The calculation load on the prediction control controller 380 increases. Therefore, it is desirable to select a prediction method according to the processing capacity of the computer.

1.2.3 Prediction Control by Prediction Controller An example of the result of the prediction control by the prediction control controller 380 shown in the present embodiment will be described with reference to FIG. In this embodiment, the normal controller 375 inputs the measured steam temperature to the controller, and the predictive controller 38
In the case of 0, the superheater desuperheater spray flow rate correction value w1 (t) and the fuel flow rate correction value w2 (t) were calculated from the predicted value y of the superheater steam temperature.
Therefore, FIG. 9 shows the result of the preceding control based on the manipulated variable correction values w1 (t) and w2 (t).

In FIG. 9, an operation plan value in which the superheater steam temperature target value v changes like a ramp when the power generation load of the plant fluctuates is given.
Reference numeral 80 predicts a superheater steam temperature future value y, a superheater desuperheater spray flow rate future value u1, and a fuel flow rate future value u2. According to the figure, the future value y of the superheater steam temperature shows a characteristic that the temperature once decreases when the load changes and then increases, and θup ° C in the positive direction and θup in the negative direction.
It is predicted that a control deviation of low ° C will occur. This is considered to be due to the high sensitivity of the spray flow rate immediately after the load change, and the excessive flow rate of the spray water. Therefore, in the present embodiment, for the purpose of reducing the control deviation, the future spray flow rate u1 is input to the manipulated variable correction value calculation means 213, and the fuel flow correction value w2 and the superheater desuperheater spray flow correction value w1 are obtained. .

FIG. 10 shows the operation amount correction value calculating means 21.
3 shows the calculation results of the fuel flow correction value w2 and the superheater desuperheater spray flow correction value w1 in FIG. The waveform separating means 250
Separates p2 and p1 from the superheater desuperheater spray flow u1, and obtains q1 and q2 respectively by the gain compensation means.
Further, the phase compensating means 252 inputs q2 and calculates r2.
Q1 and q2 are input to the first and second data output means 254a and 254b, and the manipulated variable correction values w1 and w2 are output to the normal controller 375, respectively.

FIG. 11 shows the control result of the superheater steam temperature based on the manipulated variable correction values w1 (t) and w2 (t).

With the manipulated variable correction values w1 (t) and w2 (t), the fuel flow rate and the desuperheater spray flow rate are corrected to the waveforms u′2 and u′1, and as a result, the control deviation of the superheater steam temperature Was reduced to θ′up in the positive direction and θ′low in the negative direction. This is because the flow rate in the transient state of the fuel flow rate and the desuperheater spray flow rate was simultaneously corrected.If only one of them was corrected, the temperature increase effect by the fuel flow rate and the temperature increase by the desuperheater spray flow rate were observed. The relative balance of the rise suppression effect is lost, and the control deviation of the superheater steam temperature becomes a conventional level or an increasing direction.

[0136] 2. Second Embodiment A second embodiment of the present invention will be described with reference to FIGS. In this embodiment, the operation amount correction value calculation means 213 in the first embodiment is changed from the configuration shown in FIG. 8 to the configuration shown in FIG. 12, and a plurality of operation amounts are separated by performing waveform separation. It aims at making the operation amount mutually non-interfering. The configuration of the other components is the same as that of the above-described first embodiment, and a duplicate description will be omitted.

As can be seen from FIG. 12, the manipulated variable correction value calculating means 213 according to the present embodiment is different from the first and second waveform separating means 250a and 250b in place of the waveform separating means 250 in the first embodiment. First and second phase compensating means 252a and 252b are used instead of phase compensating means 252, and first and second gain compensating means 251a and 251b
The third and fourth gain compensating means 251 with respect to 51b
c, 252d, and the waveform synthesizing means 253a, 253d.
53b is added. With this configuration, the signal obtained by the first gain compensating unit 251a and the output of the second gain compensating unit 251b are applied to the phase compensating unit 252a.
And a signal obtained by the fourth gain compensator 251d and a signal obtained by the phase compensator 252b with respect to the output of the third gain compensator 251c. Are synthesized by the waveform synthesizing means 254b, and the manipulated variable correction value w1
And w2, and the first and second data output means 254
a, 254b.

In the description of this embodiment, a plurality of predicted values of the manipulated variables are input, but one of the inputs may be a predicted value of the control amount of the plant. Further, the plant simulation means 211 according to the present invention also functions as a state monitor of the plant. Therefore, the predicted value of the process amount that cannot be observed in the plant may be used as one input in FIG.

Further, in the present invention, the control device simulating means 2
Reference numeral 12 also predicts a change in the operation amount due to interlock, upper / lower limit setting, and the like. Therefore, the manipulated variable correction value calculation means 213
For example, information such as whether an interlock has occurred, whether an operation amount or a control amount has deviated from upper and lower limit values, or the like may be input. At this time, a means for early detection of a plant abnormal event or a control error due to a malfunction of the normal control controller may be added to the manipulated variable correction value calculating means 213 to output a preceding manipulated variable for eliminating the abnormal event. Good.

In the present invention, the control device simulating means 2
The control unit 12 may accumulate the operation data of the past operation amount and output the operation data corresponding to the control amount target value as the operation amount prediction value. The manipulated variable correction value calculation means 213 receives the manipulated variable predicted value and the control variable predicted value, and outputs a manipulated variable corrected value from these values.

3. Third Embodiment In the first and second embodiments described above, the plant simulation means 211 and the control device simulation means 212 are provided one by one in the prediction control controller 380, respectively. And control device simulation means 21
2 is provided in the prediction control controller 380. FIG. 13 shows an embodiment of the prediction control controller 380 in this case. The other components are configured in the same manner as the above-described first embodiment or the second embodiment, and thus redundant description will be omitted.

In FIG. 13, the predictive control controller 380 described in FIG.
, A first controller simulation unit 212 and a second controller simulation unit 212a, and a manipulated variable correction value calculation unit 213.

The second plant simulation means 211a, like the first plant simulation means 211, reproduces the steady-state characteristics and the transient response characteristics of the plant 100 by using a differential equation or the like, and the operation amount prediction value u1 (t + τ2 -Δt) and u2 (t + τ2-Δt) are input to output a control amount prediction value y (t + τ2). At this time
Is the calculation cycle.

The second control device simulating means 212a, like the first control device simulating means 212, reproduces the steady-state characteristics and the transient response characteristics of the control device 200, and the predicted value v (t + τ2-Δt) and predicted control amount y (t + τ2-Δt)
And outputs the manipulated variable prediction values u1 (t + τ2) and u2 (t + τ2). v (t + τ2-Δt) is given as a function or a constant of the power generation target value, and the future value is obtained from the planned value of the power generation target value. That is, the first control device simulation means 2
12 and the first plant simulation means 211 constitute a closed loop circuit at t + τ1, and the second control device simulation means 21
2a and the second plant simulation means 211a constitute a closed loop circuit at t + τ2.

In such a predictive control controller 380, by independently operating the two closed-loop circuits, it is possible to calculate the amount of process and the amount of operation at different times and different calculation intervals.

In this embodiment, the first control device simulating means 212 and the first plant simulating means 211 operate at time t + T1.
Calculate the future values of the process amount and the operation amount at. In addition, the second control device simulation means 212a and the second plant simulation means 211a calculate the process amount and the operation amount at the time t + Δt, that is, the process amount and the operation amount in the next cycle. At this time, the second control device simulation means 21
2a inputs all the process amounts U (t + Δt) in the control device simulating means to the first control device simulating means 212 after time t + Δt seconds, and calculates the first control device simulating means 212 after time t + Δt seconds. The state is made to match the second control device simulation means 212a. Similarly, the second plant simulation means 211a inputs all the process amounts Y (t + Δt) in the plant simulation means to the first plant simulation means 211 after the time t + Δt seconds, and the first plant simulation means 211a after the time t + Δt seconds. The state of the plant simulation means 211 is made to match the state of the second plant simulation means 211a.

The above-mentioned second plant simulation means 211a
By the operation of the second control device simulating means 212a, the first control device simulating means 212 and the first plant simulating means 211 perform the initial value of the process amount required when performing the prediction calculation at every calculation cycle Δt. Can be obtained, and a prediction calculation can be performed for each calculation cycle Δt.

Although this embodiment shows an example in which two plant simulation means 211 and 211a and two control device simulation means 212 and 212a are provided, it is possible to arrange more simulation means. Needless to say.

4. Fourth Embodiment FIG. 14 shows still another embodiment of the prediction control controller 380 in the present invention. In this embodiment, the plant control means 214 is provided in the predictive control controller 380 in the third embodiment, and the other components are configured in the same manner as in the first to third embodiments. Omitted.

In FIG. 14, the control amount y (t) of the plant 100
And the operation amounts u1 (t) and u2 of the normal controller 375
(t) is input, and the control amount predicted value output from the second plant simulation means 211a in the plant adjustment means 214 matches the measured values yR, u1R, u2R of the plant 100 and the normal control controller 375. The adjustment parameter α is changed as follows. The adjustment parameter α is input to the first plant simulation means 211 to suppress a decrease in prediction accuracy due to aging of the plant.

The details of the plant adjusting means 214 are as follows.
Automatic adjustment of ACC plant dynamic characteristics simulator (Osawa,
Matsumoto et al. And three others are detailed in JSME 74th Ordinary General Meeting Lecture Papers (III), pp. 83-84), and are omitted here.

In the embodiment described above, the present invention is applied to the steam temperature prediction control of a thermal power plant. However, the present invention is not limited to the steam temperature prediction control, and the control amount having a long response delay time. Many plant control methods with For example, fluctuations in the gas composition of coal gas at a coal gasification plant that gasifies coal to produce gas turbine fuel or fuel cell fuel, and steam temperature fluctuations at a garbage power plant that generates electricity using thermal energy obtained from refuse combustion And the like are control amounts having a long response delay time, but the present invention can also be applied to these controls.

As described above, according to each of these embodiments, the prediction control controller 380 outputs the future predicted value of the control amount and the future predicted value of the operation amount, and the operation amount correction value calculation means 213 outputs Since the correction value of the manipulated variable is determined using a plurality of predicted values, predictive control can be performed in consideration of the overall characteristics of the normal controller 375.

Further, the manipulated variable correction value calculated by the manipulated variable correction value calculation means 213 corrects the output of the conventional normal controller 375, so that it can be easily added to the conventional normal controller 375. .

The manipulated variable correction value calculated by the manipulated variable correction value calculating means 213 can be used as a dynamic advance control command in the conventional normal controller 375. The optimum dynamic preceding control command can be automatically calculated without adjustment by operation.

[0156]

As described above, according to the present invention, there is provided the operation amount calculating means for determining the operation amount of each process on the basis of the future value predicted by the prediction means, and the prediction means comprises the control amount of the predicted control amount. Since the future value of the manipulated variable, which is the output of the control device, is predicted from the future value, and the manipulated variable calculation means determines the correction value of the manipulated variable from the predicted future value of the manipulated variable, The means determines a correction value of the operation amount from the future value of the control amount predicted by the prediction means in addition to the future value of the operation amount, and the operation amount calculation means calculates the predicted future value. Since the correction values of a plurality of manipulated variables are determined using these values, it is possible to predict a future value of a process having a large response time delay and control the accuracy with high accuracy. In particular, it is possible to accurately control a process amount having a response time delay as long as several minutes to 20 minutes.

Further, according to the present invention, a prediction for predicting at least one future value of a steam temperature of a thermal power plant, a fuel flow rate of the plant, a spray flow rate of a steam temperature cooler, a recirculation gas flow rate and a gas distribution damper. Means and at least one operation for determining at least one of a fuel flow rate, a steam temperature desuperheater spray flow rate, a recirculation gas flow rate and a gas distribution damper of the plant as a manipulated variable based on the measured steam temperature of the plant. Amount predicting means, wherein the predicting means predicts at least one future value of a fuel flow rate, a steam temperature desuperheater spray flow rate, a recirculated gas flow rate and a gas distribution damper, and the manipulated variable calculating means includes: Since at least one correction value of the manipulated variables is determined from the at least one future value predicted by the prediction means,
In a thermal power plant, it is possible to predict a future value of a process having a large response time delay and control the value with high accuracy. In particular, thermal power plants that take a long time to change the main steam temperature after changing the fuel input, fluctuations in the gas composition of coal gas in coal gasification plants, and garbage generated by thermal energy obtained from garbage combustion As in a power plant, a process amount having a long response time delay of several minutes to 20 minutes can be accurately controlled.

In addition, according to the present invention, when the future value of the control amount to be controlled is predicted and the predetermined control is executed based on the predicted future value, the future value of the predicted control amount is Predict the future value of the manipulated variable that is the output of the control device from
Since the correction value of the manipulated variable is determined from the predicted future value of the manipulated variable, it is possible to provide a process control method for predicting the future value of a process having a large response time delay and performing accurate control.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a prediction controller of a thermal power plant according to a first embodiment of the present invention.

FIG. 2 is an explanatory diagram showing a configuration of a thermal power plant according to the first embodiment.

FIG. 3 is a block diagram illustrating a relationship between a configuration of a control device and a plant according to the first embodiment.

FIG. 4 is a block diagram illustrating a hardware configuration of a control device according to the first embodiment.

FIG. 5 is a flowchart illustrating a processing procedure of a plant simulation unit and a control device simulation unit according to the first embodiment.

FIG. 6 is a block diagram illustrating a configuration of a plant simulation unit according to the first embodiment.

FIG. 7 is a block diagram showing an implementation example of a control device simulation means when the system of a normal controller is unknown.

FIG. 8 is a block diagram illustrating a configuration of a manipulated variable correction value calculation unit according to the first embodiment.

FIG. 9 is an explanatory diagram illustrating an example of a prediction result of a plant simulation unit and a control device simulation unit according to the first embodiment.

FIG. 10 is an explanatory diagram illustrating an example of a calculation result of the manipulated variable correction value calculation unit according to the first embodiment.

FIG. 11 is an explanatory diagram illustrating an example of a plant control result according to the first embodiment.

FIG. 12 is a block diagram illustrating a configuration of an operation amount correction value calculation unit according to the second embodiment.

FIG. 13 is a block diagram illustrating a configuration of a prediction control controller according to a third embodiment.

FIG. 14 is a block diagram illustrating a configuration of a prediction control controller according to a fourth embodiment.

[Explanation of symbols]

REFERENCE SIGNS LIST 100 Plant 201, 202 Controller 203 Switching means 211, 211a Plant simulation means 212, 212a Controller simulation means 213 Operation amount correction value calculation means 220 Combustion calculation block 221 Water wall model 222 Superheater desuperheater spray model 223 Superheater model 224 High pressure turbine model 225 Reheater desuperheater spray model 226 Reheater model 227 Medium / low pressure turbine model 228 Recirculation fan model 250, 250a, 251b Waveform separation means 251a, 251b, 251c, 251d Gain compensation means 252, 252a, 252b Phase compensation means 254a, 254b Data output means 300 Operation control device 375 Normal control controller 380 Predictive control controller

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Akihiko Yamada 7-2-1, Omika-cho, Hitachi City, Ibaraki Prefecture Inside Power and Electricity Research Laboratory, Hitachi, Ltd. 7-2-1, Hitachi, Ltd. Power and Electricity Development Laboratory (72) Inventor Toshihiko Harashima 5-2-1, Omika-cho, Hitachi City, Ibaraki Pref. Hitachi, Ltd., Omika Works (72) Inventor Kikuchi Shinya 5-2-1 Omika-cho, Hitachi City, Ibaraki F-term (reference) at Hitachi, Ltd. Omika Plant 3L021 AA05 CA06 DA04 DA05 DA26 DA27 EA01 FA08 FA16 5H004 GA02 GB04 HA01 HB01 HB02 JA04 JB07 KA65 KA69 KB24 KB28 KC28 KC28 KD46 LA12 LA18 9A001 HH03 HH32 JJ73 KK32 KK55

Claims (10)

[Claims] 1. A process control apparatus comprising: a prediction unit for predicting a future value of a control amount to be controlled; and a control unit for performing predetermined control based on a prediction result by the prediction unit. Means for calculating an operation amount of each process based on a future value predicted by the means, wherein the prediction means calculates a future value of an operation amount which is an output of the control device from the predicted future value of the control amount. A process control device, wherein the manipulated variable calculation means determines a correction value of the manipulated variable from a predicted future value of the manipulated variable. 2. The operation amount calculation unit determines a correction value of the operation amount from a future value of the operation amount and a future value of the control amount predicted by the prediction unit. 2. The process control device according to 1. 3. The method according to claim 2, wherein the predictor predicts a future value of the manipulated variable, and the manipulated variable calculator determines correction values of a plurality of manipulated variables using the predicted future value. 3. The process control device according to 1 or 2. 4. A predicting means for predicting at least one future value of a steam temperature of a thermal power plant, a fuel flow rate of the plant, a steam desuperheater spray flow rate, a recirculation gas flow rate and a gas distribution damper; At least one operation amount calculating means for determining at least one of a fuel flow rate, a steam temperature desuperheater spray flow rate, a recirculation gas flow rate and a gas distribution damper of the plant as an operation amount based on the measured value of the steam temperature. The predicting means includes at least one of a fuel flow rate, a steam temperature desuperheater spray flow rate, a recirculation gas flow rate, and a gas distribution damper.
A process control device predicting two future values, wherein the manipulated variable calculating means determines at least one correction value of the manipulated variables from the at least one future value predicted by the predicting means. 5. The predicting means predicts the at least one future value and a future value of the steam temperature, and the manipulated variable calculating means determines at least one of the manipulated variables from the at least two future values. 5. The process control device according to claim 4, wherein one correction value is determined. 6. A plurality of the predicting means, wherein the predicting means calculates and outputs predicted values of a plurality of manipulated variables having at least one of a predicted time and a predicted cycle which are different from each other. The method according to claim 4, wherein a plurality of future values of the process amount are predicted, and the operation amount calculation unit determines at least one correction value of the operation amount based on the predicted future value. 6. The process control device according to 5. 7. The process control apparatus according to claim 6, wherein at least one of said prediction means predicts a future value of a process amount at a next prediction time. 8. The predicting means records the measured value of the manipulated variable in the actual machine controller as a time-series signal, and outputs a time-series signal of the manipulated variable as a predicted value at the time of calculating a future value. And determining a correction value of the operation amount based on the predicted future value.
7. The process control device according to any one of items 6 to 6. 9. The system according to claim 1, wherein the future value is a predicted value based on a lapse of time corresponding to a time from a change in the fuel input amount to a change in the main steam temperature.
The process control device according to any one of claims 1 to 4. 10. A process control method for predicting a future value of a control amount to be controlled and executing a predetermined control based on the predicted future value, wherein the control device determines a future value of the control amount based on the predicted future value of the control amount. A process control method comprising predicting a future value of an operation amount as an output, and determining a correction value of the operation amount from the predicted future value of the operation amount.