JP2022107463A - Plant controller, plant control method, and program - Google Patents

Abstract

To predict the occurrence of abnormal operation in a plant under control and properly operate a final control element so that the abnormal operation does not occur, thereby improving the control effect and operation efficiency.SOLUTION: A plant under control is subjected to a first operation process with a response rate to an operation being a predetermined response rate and a second operation process with a higher response rate to an operation than that of the first operation process. The first operation process is executed by a first final control element and the second operation process is executed by a second final control element. Here, a safe operation range determination unit is provided that determines the safety operation range of the first operation process by the first final control element on the basis of the records of the first final control element. If the safe operation range determination unit determines that the first operation process by the first final control element is not in the safe operation range, the instructions of the second operation process are corrected or changed, to move the record position of the first operation process by the first final control element to a record position where the occurrence of abnormal operation is not estimated.SELECTED DRAWING: Figure 1

Description

The present invention relates to a plant control device, a plant control method and a program.

When performing rolling mill control, which is one of the plant controls, fuzzy control and neuro-fuzzy control have been conventionally applied to shape control for controlling the wavy state of a plate. Fuzzy control is applied to shape control using coolant, and neuro-fuzzy control is applied to shape control of a Sendimia rolling mill.

In the shape control to which the neuro-fuzzy control is applied, as shown in Patent Document 1, the difference between the actual shape pattern and the target shape pattern detected by the shape detector and the similarity ratio with the preset reference shape pattern are calculated. The desired process is being performed. Then, in the shape control to which the neuro-fuzzy control is applied, the control output amount for the operation end is obtained from the obtained similarity ratio by the control rule expressed by the control operation end operation amount for the preset reference shape pattern. There is.

The shape control has a plurality of control operation ends, and the control is executed by the difference in the characteristics of the plurality of control operation ends. The shape is a wavy state of the plate in the plate width direction, and the control operation end can change the shape of a specific region in the plate width direction. For example, the AS-U roll can change the shape near the saddle position to be operated, and the intermediate roll shift can change the shape of the plate end portion. When performing shape control, each control operation end is operated in combination so that shape deviation is suppressed according to the actual shape.

When the rolling mill performs rolling, a cooling material (hereinafter referred to as coolant) is required for lubrication between the material to be rolled and the rolls of the rolling mill and for cooling the heat generated by rolling. This coolant serves as an operation end for shape control, and the shape can be changed in the entire plate width direction by adjusting the injection amount of the coolant in the plate width direction. As shown in Patent Document 2, the 6-stage rolling mill has a coolant injection amount adjusting mechanism in the plate width direction, and shape control is performed by changing the injection amount using the actual shape. However, in the Sendimia rolling mill, the roll of the rolling mill is immersed in the coolant during rolling, and the coolant requires more time than AS-U or the intermediate roll shift until the effect on the shape appears. Further, since the coolant injection amount cannot be adjusted automatically, it may be necessary for the operator to operate the flow rate adjusting valve. In such cases, adjustments can only be made before the start of rolling.

During rolling in a rolling mill, an operation abnormality may occur in which the material to be rolled breaks. The fracture of the material to be rolled is often caused by the material to be rolled, but it may also be broken due to the meandering of the material to be rolled. The meandering of the material to be rolled means that the material to be rolled is displaced to one side of the rolling mill, and rolling is usually performed at the central portion of the rolling mill.
Such meandering is expected to occur depending on the position of the AS-U roll or intermediate roll shift. In shape control, AS-U and intermediate roll shifts are operated to maintain the shape of the material to be rolled to the target shape, but as a result, the mechanical state may be prone to meandering of the material to be rolled. be.

Conventionally, ordinary rolling mills such as 4-stage rolling mills and 6-stage rolling mills have an operating unit that changes the coolant injection amount in the plate width direction, in addition to the mechanical operating unit bender and leveling. Used for shape control. Unlike the Sendimia rolling mill, in a normal rolling mill, the roll of the rolling mill is not immersed in the coolant, and the effect on the shape of the coolant can be obtained in the same time as the mechanical operating means. Therefore, in the shape control in a normal rolling mill, the mechanical operating means and the coolant are treated equally, and the coolant is used as the control operating end. Even in that case, since the coolant is effective in the entire plate width direction, it competes with the mechanical operation unit, and even if the actual shape of the material to be rolled is the same, the actual position of the mechanical operation unit is often different.

FIG. 15 shows a schematic configuration of a control device of a conventional Sendimia rolling mill.
First, the arithmetic unit 901 takes a difference between the target shape d1 and the actual shape d2 of the material to be rolled obtained by the rolling mill 990, and gives this difference to the first shape control unit 902 and the second shape control unit 903. The first shape control unit 902 controls the mechanical operation end 904, which is a mechanical operation unit. The second shape control unit 903 controls the coolant operating end 905 that changes the coolant injection amount.

The rolling mill 990 executes a mechanical operation process by the mechanical operation end 904 and an operation process of the coolant injection amount by the coolant operation end 905 to perform the rolling process of the material to be rolled, and the shape record d2 of the material to be rolled. And the rolling result d3 is obtained. In this case, in the mechanical operation process by the mechanical operation end 904, the shape of the material to be rolled is changed with a relatively high-speed response by controlling the operation amount. On the other hand, the operation process of the coolant injection amount by the coolant operation end 905 has a slower response than the mechanical operation process even if the operation amount is controlled.

In the case of the configuration shown in FIG. 15, as already described, the mechanical operation process by the mechanical operation end 904 and the operation process of the coolant injection amount by the coolant operation end 905 compete with each other. At this time, even if the actual shape d2 is the same, the mechanical operation amount by the mechanical operation end 904 is not always the same. Moreover, the response speed is different between the mechanical operation process by the mechanical operation end 904 and the operation process of the coolant injection amount by the coolant operation end 905, and the range of effect in the plate width direction is different in each operation process. Therefore, there is a problem that it is difficult to appropriately control both the mechanical operation process by the mechanical operation end 904 and the operation process of the coolant injection amount by the coolant operation end 905. For example, when the operating range of the mechanically operated end 904 of high-speed response is close to the upper limit, the shape actual d2 and the rolling actual d3 cannot be controlled stably and vibration occurs, and the rolling mill which is the controlled plant. The 990 may not operate stably.

As a conventional technique for appropriately controlling the shape of such a Sendimia rolling mill, for example, as described in Patent Document 3, the relationship between the actual shape deviation of the material to be rolled and the control operation end operation amount is obtained from the actual data. There is a technique to learn and control using machine learning. In the technique described in Patent Document 3, shape control is performed by outputting a control output according to the shape deviation and operating the control operation end.

Japanese Patent No. 2804161 Japanese Patent No. 2515028 Japanese Unexamined Patent Publication No. 2018-005544

The technique described in Patent Document 3 executes shape control by learning a control operation method for a shape deviation, and does not consider the control operation end position. In actual control, the operation range is limited by the mechanical conditions of the control operation end, but it is possible to stop the control output for that control operation end and operate with another control operation end if possible. It will only be heard.

Further, when the time until the coolant as the shape control operation end affects the shape is longer than that of the mechanical operation end as in the Sendimia rolling mill, it is the same as the mechanical operation end as in the conventional case. Even if the operation command of the coolant is output, the shape is controlled by the mechanical operation end at which the influence on the shape is transmitted in a short time, and the shape control by the coolant cannot be effectively performed.

When rolling with a rolling mill, the actual position of the mechanically operated end is limited because operational abnormalities such as plate breakage occur depending on the characteristics of the material to be rolled, the rolling state, and the actual position of the mechanically operated end of shape control. Is required. However, it is extremely difficult to limit the actual position of the mechanically operated end when the mechanically operated end and the coolant are used as the operating end of the shape control.
As described above, in the conventional shape control, since the coolant is controlled based on the shape deviation as in the case of the mechanically operated end, the actual position of the mechanically operated end that leads to an operation abnormality such as plate breakage is limited. There was a problem that it could not be done.

In the explanation so far, the problem of shape control of the Sendimia rolling mill has been described, but in various plant control devices, when a control operation having a high responsiveness and a control operation having a slow responsiveness are performed at the same time, both are controlled. There is a similar problem when performing operations properly at the same time.

An object of the present invention is plant control capable of improving control effect and operation efficiency by predicting the occurrence of an operation abnormality in a controlled plant and appropriately operating the control operation end so that the operation abnormality does not occur. To provide equipment, plant control methods and programs.

In order to solve the above problems, for example, the configuration described in the claims is adopted.
The present application includes a plurality of means for solving the above problems. For example, as a plant control device, the response speed to an operation is a first operation process having a predetermined response speed to a controlled plant. , The second operation process, which has a slower response speed to the operation than the first operation process, is performed.
The first control unit that acquires the target state quantity of the controlled plant and gives instructions for the first operation process.
A second control unit that acquires the target state quantity of the controlled plant and gives instructions for the second operation process.
The first operation end that executes the first operation processing of the controlled plant according to the instruction from the first control unit, and
The second operation end that executes the second operation processing of the controlled plant according to the instruction from the second control unit,
A safety operation range determination unit that determines the safe operation range of the first operation process by the first operation end based on the results of the first operation end,
If the first operation process by the first operation end is not within the safe operation range, the instruction of the second operation process by the second control unit is corrected or changed by the judgment by the safe operation range determination unit, and the first operation end is used. It is provided with a third control unit that moves the actual position of the first operation process to the actual position where the occurrence of an operation abnormality is not estimated.

According to the present invention, it is possible to appropriately control the operating state of the controlled plant and suppress the actual position of the operating end that causes an operation abnormality. As a result, improvement of control accuracy of the controlled plant, improvement of operation efficiency, and suppression of occurrence of operation abnormality can be expected.
Issues, configurations and effects other than those described above will be clarified by the description of the following embodiments.

It is a block diagram which shows the structural example of the plant control apparatus by one Embodiment of this invention. It is a block diagram which shows the structural example when the plant control apparatus according to one Embodiment of this invention is applied to a rolling mill. It is a block diagram which shows the example of the Sendimia rolling mill. It is a block diagram which shows the example of the rolling equipment of a single stand rolling mill. It is a figure which shows the outline of the mechanical operation end by the example of one Embodiment of this invention. It is a block diagram which shows the structural example of the safe operation range determination part by the example of one Embodiment of this invention. It is a figure which shows the structural example of the neural network by the example of one Embodiment of this invention. It is a figure which shows the structural example of the neural network management table by one Embodiment of this invention. It is a figure which shows the structural example of the learning database by one Embodiment of this invention. It is a block diagram which shows the structural example of the mechanical operation end position suppression control part by one Embodiment of this invention. It is a figure which shows the outline of the mechanical operation end position abnormality region determination part by the example of one Embodiment of this invention. It is a figure which shows the structure and operation of the coolant operation end control output calculation part by one Embodiment of this invention. It is a figure which shows the operation of the coolant operation end control output selection part by one Embodiment of this invention. It is a block diagram which shows the hardware configuration example when the plant control apparatus of one Embodiment of this invention is configured by a computer. It is a block diagram which shows the structural example of the control device of the conventional rolling mill.

Hereinafter, the plant control device of one embodiment of the present invention (hereinafter, referred to as “this example”) will be described with reference to FIGS. 1 to 13.

[Overall configuration of plant control unit]
FIG. 1 shows an example of the overall configuration of the plant control device of this example.
The plant control device shown in FIG. 1 controls the controlled plant 190, and controls the controlled plant 190 by performing an operation process by the high-speed operation end (first operation end) 103 and a low-speed operation end (second operation). (End) The operation process according to 104 is executed.
The plant control device of this example acquires the first state quantity target d11, and the arithmetic unit 101 acquires the difference from the first state quantity d12. The first state quantity d12 is obtained from the controlled plant 190 as a result of the operation processing by the high-speed operation end 103 and the low-speed operation end 104. Further, the second state quantity d13 is obtained as a result of the operation processing of the high-speed operation end 103, the low-speed operation end 104, and the other operation ends added to the controlled plant 190.

The control unit 110 of the plant control device includes a first control unit 111 that controls the operation processing of the high-speed operation end 103, and a second control unit 112 that controls the operation processing of the low-speed operation end 104.
The control output of the first control unit 111 is directly supplied to the high-speed operation end 103, and controls the operation processing of the high-speed operation end 103.
The control output of the second control unit 112 is supplied to the third control unit 102, and is supplied to the low-speed operation end 104 after correcting or changing the control output as necessary.

Further, the plant control device of this example includes a safe operation range determination unit 105. The safe operation range determination unit 105 acquires the operation record of the high-speed operation end 103, determines whether or not the acquired operation record has a margin in the safe operation range, and obtains the data of the safe operation range d14 as the determination result. , Supply to the third control unit 102.
Further, the safe operation range determination unit 105 acquires the first state quantity d12 and the second state quantity d13 of the controlled plant 190. Then, the safe operation range determination unit 105 refers to the first state quantity d12 and the second state quantity d13 to determine whether or not the current operation record of the high-speed operation end 103 has a margin in the safe operation range. judge.

Here, the safe operation range determination unit 105 detects the occurrence of an operation abnormality, learns the first state quantity d12 and the second state quantity d13 at that time, and the actual position of the high-speed operation end 103, and obtains the high-speed operation end. The safe operation range d14, which is the operable range, is determined so that the operation abnormality does not occur in 103. Since the operation abnormality is not a phenomenon that occurs frequently, the safe operation range determination unit 105 continuously collects the actual data and executes learning by using machine learning or the like to obtain the safe operation range d14. preferable.
Then, the safe operation range determination unit 105 supplies the data of the determined safe operation range d14 to the third control unit 102.

When the third control unit 102 determines from the data in the safe operation range d14 that there is a margin in the safe operation range, the third control unit 102 supplies the control output of the second control unit 112 as it is to the low speed operation end 104. On the other hand, when the third control unit 102 determines from the data of the safe operation range d14 that there is no margin in the safe operation range, the third control unit 102 corrects or changes the control output of the second control unit 112 to the low speed operation end 104. Supply.
The output of the arithmetic unit 101, the operation record of the high-speed operation end 103, and the second state quantity d13 are supplied to the third control unit 102, and the third control unit 102 is supplied with the second state quantity d13 based on the information. The control output of the control unit 112 is corrected or changed.

According to the plant control device having the configuration shown in FIG. 1, the high-speed operation end 103 can be operated efficiently within a range in which an operation abnormality does not occur, and in addition to the improvement of the operation efficiency, the improvement of the control accuracy is also expected. can.

[Overall configuration when applied to the control device of a Sendimia rolling mill]
Next, the overall configuration when the plant control device of this example is applied to a Sendimia rolling mill will be described.
FIG. 2 shows the configuration of the plant control device of this example when applied to a Sendimia rolling mill.
The plant control device shown in FIG. 2 acquires the target shape d21 of the material to be rolled, and the arithmetic unit 201 acquires the difference from the actual shape d23 after rolling.

The plant control device of this example executes the operation process by the mechanical operation end 203 and the operation process by the coolant operation end 204 as the control of the rolling mill 301. The operation process by the mechanical operation end 203 mechanically changes the roll gap or the like to be rolled, and the response appearing in the shape record d23 of the material to be rolled becomes high speed. On the other hand, the operation process by the coolant operation end 204 changes the coolant injection amount, and the response appearing in the rolling result d24 of the material to be rolled is slower than the operation by the mechanical operation end 203.

The control unit 210 of the plant control device includes a first shape control unit 211 that controls the operation processing of the mechanical operation end 203, and a second shape control unit 212 that controls the operation processing of the coolant operation end 204. The first shape control unit 211 and the second shape control unit 212 control the material to be rolled so as to have the target shape d21. The target shape d21 is preset according to the characteristics of the material to be rolled and the like.
The control output of the first shape control unit 211 is directly supplied to the mechanical operation end 203, and controls the operation processing of the mechanical operation end 203.
The control output of the second shape control unit 212 is supplied to the mechanical operation end position suppression control unit 202, and is supplied to the coolant operation end 204 after correcting or changing the control output as necessary.
The configuration of the mechanical operation end position suppression control unit 202 will be described later with reference to FIG.

Further, the plant control device of this example includes a mechanical operation end safety operation range determination unit 205. The mechanical operation end safety operation range determination unit 205 acquires the mechanical operation end position result d22 which is the operation result of the mechanical operation end 203, and the acquired mechanical operation end position result d22 has a margin in the safe operation range. Determine if it is. Then, the mechanical operation end safety operation range determination unit 205 supplies the data of the mechanical operation end safety operation range d25 as the determination result to the mechanical operation end position suppression control unit 202.

Further, the mechanical operation end position suppression control unit 202 acquires the shape actual d23 and the rolling actual d24 of the rolling mill 301. Then, the mechanical operation end safety operation range determination unit 205 refers to the shape result d23 and the rolling result d24, and determines whether or not the acquired mechanical operation end position result d22 has a margin in the safe operation range. judge.

The mechanical operation end safety operation range determination unit 205 detects the occurrence of an operation abnormality, and learns the shape result d23 and the rolling result d24 at that time, and the mechanical operation end position result d22. By this learning, the mechanical operation end safe operation range determination unit 205 determines the mechanical operation end safe operation range d25, which is an operable range, so that an operation abnormality does not occur at the mechanical operation end 203. Here, the mechanical operation end safe operation range determination unit 205 continuously collects actual data and executes learning by using machine learning or the like to obtain the mechanical operation end safe operation range d25.
Then, the mechanical operation end safety operation range determination unit 205 supplies the data of the determined mechanical operation end safety operation range d25 to the mechanical operation end position suppression control unit 202.
The detailed configuration in which the mechanical operation end safe operation range determination unit 205 learns the operation abnormality and the like will be described later with reference to FIG.

When the mechanical operation end position suppression control unit 202 determines from the data of the mechanical operation end safe operation range d25 that there is a margin in the safe operation range, the control output of the second shape control unit 212 is directly transmitted to the coolant operation end 204. Supply. On the other hand, when the mechanical operation end position suppression control unit 202 determines from the data of the mechanical operation end safe operation range d25 that there is no margin in the safe operation range, the mechanical operation end position suppression control unit 202 corrects the control output of the second shape control unit 212. Alternatively, it is changed and supplied to the coolant operating end 204.
Further, the output of the arithmetic unit 201, the mechanical operation end position actual d22, and the rolling actual d24 are supplied to the mechanical operation end position suppression control unit 202, and the mechanical operation end position suppression control unit 202 is supplied with these. The control output of the second shape control unit 212 is corrected or changed based on the information of.

[Structure of Sendimia rolling mill]
Here, a configuration example of the Sendimia rolling mill will be described.
FIG. 3 shows a schematic configuration when shape control is performed in a Sendimia rolling mill.
In the Sendimia rolling mill, the actual shape of the rolled material is detected by the shape detector 14. The actual shape detected by the shape detector 14 is the most among the reference shape patterns preset by the pattern recognition unit 12 after the pattern recognition preprocessing is performed by the shape detection preprocessing unit 11 of the control device 50. It is calculated whether it is close. Then, based on the calculated reference shape pattern, the control calculation unit 13 determines the operation end and the operation amount to be operated, and executes a process of controlling the Sendimia rolling mill with the operation end and the operation amount to be operated. To.

FIG. 4 shows an example of rolling equipment of a single stand rolling mill. The Sendimia rolling mill is a type of single stand rolling mill.
The rolling equipment shown in FIG. 4 is composed of a rolling mill 301, an inlet tension reel (hereinafter referred to as “TR”) 302, and an outlet TR 303, and the material to be rolled 300 drawn from the inlet TR 302 is a rolling mill. After passing through 301, it is wound up by the exit side TR303.
The rolling mill 301 rolls the material to be rolled 300. The rolling here is a process of reducing the plate thickness of the material to be rolled 300 to a predetermined plate thickness.

The rolling mill 301 is provided with a mill speed control unit 304 for adjusting the rolling speed and a roll gap control unit 307 for adjusting the roll gap of the rolling mill 301. Further, the entry-side TR302 and the exit-side TR303 are provided with an entry-side TR control unit 305 and an exit-side TR control unit 306 for adjusting the tension generated by each.

The rolling process is carried out by adjusting the vertical roll interval of the rolling mill 301 by the roll gap control unit 307 to apply pressure to crush the material to be rolled 300, and by sending the material to be rolled 300 to the output side by the mill speed control unit 304. Will be done. At this time, on the entry side and the exit side of the rolling mill 301, a process of applying tension to the material to be rolled 300 by using the entry side TR302 and the exit side TR303 is also performed.

What is important for the rolling operation is the plate thickness of the material to be rolled 300 (outside plate thickness of the rolling mill) to be a product, and the roll gap and the entry side tension so that the material to be rolled 300 has a predetermined plate thickness. The exit tension is preset.
The entry-side tension current conversion unit 315 obtains the current required to obtain the set entry-side tension using the entry-side tension set by the entry-side tension setting unit 311, and sets the entry-side TR control unit 305. The entry-side tension is obtained by applying the entry-side tension to the entry-side TR302.
Similarly, the output side tension current conversion unit 316 obtains the current required to obtain the set output side tension by using the output side tension set by the output side tension setting unit 312, and controls the output side TR. The tension on the exit side is obtained by applying the tension to the exit side TR303 via the portion 306.

The roll gap set by the roll gap setting unit 319 is given to the roll gap control unit 307, and the roll gap is set by the roll gap control unit 307.
The rolling speed setting unit 310 determines the speed of the rolling mill 301 according to the instruction of the operator of the rolling mill, and the mill speed control unit 304 sets the speed of the rolling mill 301.

An inlet tension meter 308 and an outlet tension meter 309 are installed on the inlet and outlet sides of the rolling mill 301, and the inlet tension control unit 313 and the outlet tension control unit 313 so that the actual tension measured by them matches the set tension. The side tension control unit 314 executes the control. Further, a total plate thickness meter 317 is installed on the output side of the rolling mill 301, and the output side plate thickness control mounting unit 318 executes control so that the actual plate thickness measured there matches the set plate thickness.

In addition to the above configuration, as shown in FIG. 3 described above, a shape detector 14 for detecting the shape of the material to be rolled is installed on the outlet side of the rolling mill, and the detected shape is determined in advance. Shape control is executed so as to match the set target shape.

As already mentioned, the shape is the degree of waviness of the metal plate that is the material to be rolled. Therefore, the target shape, which is the target shape, is set in advance from the workability in the lower process of the rolling mill and the efficiency of the rolling operation in the rolling mill. Generally, tension is applied to the material to be rolled, so if there are cracks or other scratches on the edge of the plate, cracks will occur from there, and the material to be rolled will be divided in the plate width direction (plate). It is easy to break). For this reason, it is often the case that the plate edge is wavy so that the tension is not concentrated.

The waviness of the material to be rolled does not become apparent because tension is actually applied to the material to be rolled, and apparently there is no waviness, but the tension distribution changes in the plate width direction.
Here, the shape detector 14 shown in FIG. 3 estimates the waviness of the plate by measuring the tension distribution in the plate width direction and detects it as the actual shape.

[Structure and processing of shape control mechanical operation end]
FIG. 5A shows a configuration when the operation process is performed by the mechanical operation end 203 of the Sendimia rolling mill. FIG. 5 shows a cross section of the material to be rolled 300 in the plate width direction, shows only the upper configuration of the material to be rolled 300, and omits the lower configuration.
Further, FIGS. 5 (b) and 5 (c) show operation waveforms when the shape of the material to be rolled 300 is changed, respectively.

As shown in FIG. 5A, the Sendimia rolling mill is composed of a work roll 401, a first intermediate roll 402, a second intermediate roll 403, and an AS-U roll 404, sandwiching the material to be rolled 300.
The first intermediate roll 402 is provided with a taper on the roll on the opposite side in the vertical direction, and by shifting in the plate width direction, the shape of the plate end portion of the material to be rolled 300 can be affected.

The AS-U roll 404 has a configuration in which a saddle 406 is inserted between a plurality of divided rolls 405, and by changing the position of the saddle 406 (the vertical position in FIG. 5), the AS-U roll 404 The deflection can be changed in the plate width direction.
For example, as shown in FIG. 5B, when the central saddle 406 is lowered, the shape of the central portion of the material to be rolled 300 can be affected.

Here, the operation waveforms shown at the bottom of FIGS. 5 (b) and 5 (c) show changes in the thickness distribution of the material to be rolled 300 when the saddle 406 or the first intermediate roll 402 is shifted. The shape change is opposite to the plate thickness distribution.
The shape is the distribution of the degree of waviness in the plate width direction, and the fact that the waviness is large means that the material to be rolled 300 is stretched. This is because "the thickness of the protruding side plate becomes thin", "the elongation of the material to be rolled in the thinned portion is large", and "the shape of the material to be rolled becomes large" are equal.

Regarding the operation abnormality, the plate breakage of the material to be rolled 300 is a big problem. When the plate breaks, the material to be rolled 300 after the break breaks the work roll 401 and the first intermediate roll 402 of the rolling mill. Further, in some cases, the second intermediate roll 403 and the AS-U roll 404 are also damaged due to the occurrence of plate breakage. When these breaks occur, it is necessary to replace these rolls, and it takes time to remove the material to be rolled 300 remaining in the rolling mill, resulting in an extremely low operating efficiency.

Since the AS-U roll 404 presses the split roll 405 against the second intermediate roll 403 by pressing the split roll 405 with the saddle 406, the split roll 405 and the second intermediate roll 403 may not come into contact with each other depending on the position of the saddle 406. be. In such a state, the force applied to the material to be rolled 300 from the work roll 401 in that portion suddenly decreases, the material to be rolled 300 does not stretch, and the tension applied to the material to be rolled 300 in that portion increases.

When such a state occurs at the plate end portion of the material to be rolled 300, the plate breaks from the plate end portion. Further, since the tension applied to both ends of the material 300 to be rolled in the plate width direction changes, a phenomenon occurs in which the center of the material 300 to be rolled in the plate width direction deviates from the center in the plate width direction of the rolling mill, and before and after the rolling mill. It may collide with machinery and equipment, resulting in plate breakage. As described above, depending on the actual position of the mechanical operation end 203, an operation abnormality may occur.

The actual position where the operation abnormality occurs is not calculated from the machine configuration, but the plate thickness distribution in the plate width direction of the material to be rolled 300, the plate thickness on the input / output side, the rolling state such as tension and rolling load, and other shape control machines. It is difficult to predict in advance because the positional relationship with the target operation end also changes.
Therefore, in this example, the mechanical operation end safety operation range determination unit 205 saves these conditions when a rolling abnormality occurs as actual data, and compares it with the actual data at the normal time to prevent the rolling abnormality. Shape control that is likely to occur Find the actual position of the mechanically operated end.

The mechanical operation end safe operation range determination unit 205 of this example determines the mechanical operation end safe operation range by using machine learning. For the actual data when performing machine learning, the sheet thickness on the inlet / output side, the rolling state such as tension and rolling load, and the actual position of the mechanically operated end 203 are used, and for the teacher data, rolling abnormality occurrence information is used.
Information on plate breakage and emergency stop of the rolling mill is used as rolling abnormality occurrence information. Plate breakage can be determined by reducing the tension on the entry / exit side, and emergency stop uses information on the operation switch operated by the operator when some abnormality occurs in the rolling state and the operation is stopped. The information of the operation switch can be detected by the computer constituting the control device for controlling the rolling mill, and can be used as one of the actual results information. The mechanical operation end safety operation range determination unit 205 creates a neural network (NN) for determining the presence or absence of an operation abnormality by using these actual data and teacher data.

[Structure of mechanical operation end safe operation range determination part and neural network configuration]
FIG. 6 shows a configuration when the mechanical operation end safe operation range determination unit 205 is realized by machine learning.
Further, FIG. 7 shows the configuration of the neural network 502 included in the mechanical operation end safe operation range determination unit 205.
As shown in FIG. 7, the neural network 502 obtains the rolling result d24 and the mechanical operation end position result d22 from the input data creation unit 501 at the input end 502a, and outputs the operation abnormality determination value d32 from the output end 502b. The operation abnormality determination value d32 is information on plate breakage and emergency stop information, which are rolling abnormality occurrence information. The neural network 502 executes learning from the combination of these input data and output data.

Explaining the mechanical operation end safety operation range determination unit 205 shown in FIG. 6, the input data creation unit 501 collects the mechanical operation end position actual result d22 and the shape actual result d23. Further, the teacher data creation unit 505 collects the operation abnormality determination value d32 determined by the operation abnormality determination unit 506. The data collection by the input data creation unit 501 and the teacher data creation unit 505 is performed in a fixed time cycle under the control of the neural network learning control unit 503, and a set of learning data is obtained for each operation cycle. The obtained learning data is sequentially stored in the learning data database 511.
The operation abnormality determination unit 506 determines from the rolling results d24 whether or not there is a plate breakage or an emergency stop of the rolling mill, which is an operation abnormality. The operation abnormality determination value d32, which is the determination result, is information on plate breakage and emergency stop.

By the way, the rolling mill rolls various materials to be rolled 300 according to specifications to obtain products. Therefore, the rolling mill uses the work roll 401 (diameter distribution in the plate width direction), which is a machine configuration, the taper specification of the first intermediate roll 402, and the AS-U roll 404 according to the specifications of the material to be rolled 300. It is common to change the combination of the split rolls 405. Further, the plate width and the material of the material to be rolled 300 are not uniform. Therefore, it is possible to learn more efficiently by dividing the neural network 502 according to the machine configuration and the specifications of the material to be rolled 300.
Therefore, the mechanical operation end safety operation range determination unit 205 of this example includes a control rule database 512 and a neural network selection unit 504 so that a plurality of types of neural networks 502 can be switched and used. ..

FIG. 8 shows a configuration example of the control rule database 512.
As shown in FIG. 8A, the control rule database 512 stores a plurality of neural networks trained using training data composed of a combination of input data and teacher data.
Then, the neural network learning control unit 503 determines the neural network No. that requires learning. To specify. The neural network selection unit 504 has a neural network No. 1 that requires learning by the neural network learning control unit 503. Is specified, the neural network is taken out from the control rule database 512 and set in the neural network 502.
The neural network selection unit 504 uses the current rolling results d24 to match the rolling conditions and the machine configuration, and from the control rule database 512, the corresponding neural network No. Is taken out and set in the mechanical operation end position suppression control unit 202 as the control neural network d33.

FIG. 8B shows the configuration of the neural network management table stored in the control rule database 512. The management table is classified according to (B1) plate width, (B2) steel type and machine configuration (A). (B1) As the board width, for example, four categories of 3 foot width, meter width, 4 foot width, and 5 foot width are used. (B2) As the steel grade, about 10 categories of steel grade (1) to steel grade (10) are used. Regarding (A), for example, (A1) and (A2) are distinguished according to the length of the tapered portion, which is the taper specification of the first intermediate roll 402.
The above table distinction is an example, and it is necessary to set it in a timely manner according to the rolling equipment and the type of material to be produced.
The mechanical operation end safety operation range determination unit 205 uses these neural networks properly according to the rolling conditions and the mechanical configuration.

The neural network learning control unit 503 uses the training data, which is a combination of the input data and the teacher data shown in FIG. 8A, to obtain the corresponding neural network No. according to the neural network management table shown in FIG. 8B. It is stored in the learning data database 511 in association with.

FIG. 9 shows an example of training data stored in the training data database 511.
As shown in FIG. 9, the training data database 511 has a neural network No. Stores the corresponding learning data for each.

The neural net learning control unit 503 instructs the input data creation unit 501 and the teacher data creation unit 505 to take out the input data and the teacher data from the management table corresponding to the neural net from the learning data database 511. The neural network 502 uses these to perform learning. Various learning methods for neural networks have been conventionally proposed, and any learning method may be used.

Machine learning requires a large number of sets of training data, and the neural network 502 executes learning when it is stored in the training data database 511 to some extent (for example, 10000 sets).
When the learning of the neural network 502 is completed, the neural network learning control unit 503 transfers the neural network 502, which is the learning result, to the neural network No. 512 of the control rule database 512. Learning is completed by writing back to the position of.

The neural network 502 that has completed the learning outputs the operation abnormality determination value by inputting the rolling result d24 and the mechanical operation end position result d22. Therefore, the neural network 502 can predict the presence or absence of an operation abnormality by giving the expected future shape result d23 and the mechanical operation end position result d22, and search for the mechanical operation end safe operation range d25. It is possible to do.

[Structure of mechanical operation end position suppression control unit]
FIG. 10 shows the configuration of the mechanical operation end position suppression control unit 202.
The mechanical operation end position suppression control unit 202 includes a mechanical operation end position abnormality region determination unit 610 and a mechanical operation end position abnormality suppression control unit 620.
The mechanical operation end position abnormality region determination unit 610 uses the neural network 502 described with reference to FIG. 7 to estimate the mechanical operation end 203 in which an operation abnormality is predicted to occur. The neural network 502 used here is a control neural network d33 received from the mechanical operation end safe operation range determination unit 205.
The mechanical operation end position abnormality suppression control unit 620 creates an operation command for the coolant operation end 204 based on the determination result of the mechanical operation end position abnormality region determination unit 610.

During the rolling operation, the shape result d23 of the rolling mill 301 changes from moment to moment, and the first shape control unit 211 for maintaining it in the target shape d21 operates the mechanical operation end 203, and the mechanical operation end position result d22. Also changes from moment to moment. The mechanical operation end position abnormality area search unit 611 included in the mechanical operation end position abnormality area determination unit 610 creates the input data of the neural network 502 by the input data creation unit 612 using the mechanical operation end position abnormality d22. do.

FIG. 11 shows a process performed by the mechanical operation end position abnormality region determination unit 610.
In the example of FIG. 11, when the mechanical operation end 203 has n types (n is an integer), the mechanical operation end position actual d22 is as follows.
POS (k), k = 1, 2, ..., n
The n types of mechanically operated ends 203 here correspond to, for example, the total value of the number of saddles 406 of the AS-U roll 404 and the number of the first intermediate rolls 402 that can be shifted in the plate width direction. In the case of the example shown in FIG. 5, since the number of saddles is 5 and the first intermediate roll is two upper and lower rolls, n = 7.

When the mechanical operation end 203 is operated by the first shape control unit 211, the mechanical operation end 203 is operated up to a certain amount in each control cycle. Therefore, the mechanical operation end position abnormality area search unit 611 operates each mechanical operation end 203. The estimated position of the mechanical operation end position actual d22 of is created as follows. Here, for example, the amount of change in the actual position, which may be operated by controlling several times, is set to ΔPOS, and three cases are considered, one is the case where the actual position is not changed and the other is the case where the actual value is changed in the positive and negative directions.
POS (k), POS (k) ± ΔPOS, k = 1, 2, ..., n

As a result, the estimated position results of each mechanical operation end 203 can be created in 3 ⁿ ways (for example, 2187 ways in the case of n = 7). For example, when n = 7, 2187 estimated position results can be created. The estimated position results are sequentially output to the input data creation unit 612.
The input data creation unit 612 creates input data to the neural network 502 from the rolling result d24 and the estimated position d31, and outputs the input data to the neural network 502.

The neural network 502 outputs the operation abnormality determination value d32 shown in FIG. 11 (d). The operation abnormality determination value d32 is the degree of plate breakage and emergency stop. Here, the output data determination unit 613 receives the operation abnormality determination value d32 output from the neural network 502 and weights both degrees. Add and add to obtain the operation abnormality evaluation value d26. Generally, when an operation abnormality occurs, the operator implements an emergency stop, but also when a sign of plate breakage occurs. As a sign of plate breakage here, for example, there is meandering of the material to be rolled 300.
If there is no emergency stop and the plate breaks, it means that the plate breaks without any sign, and the plate break has a higher priority to suppress. Therefore, the weighting of the degree of plate breakage is increased.

The mechanical operation end position abnormality area search unit 611 stores the output estimated position d31 and the returned operation abnormality evaluation value d26, and searches for the estimated value at which the operation abnormality evaluation value d26 is maximized. As a result of the search, when the maximum value of the operation abnormality evaluation value d26 exceeds a predetermined threshold value, the mechanical operation end position abnormality area search unit 611 determines the actual position change amount at the estimated position d31 in that case. It is output as the actual position abnormal area operation end judgment value d27. Further, the operation abnormality evaluation value d26 in that case is also included in the actual position abnormality area operation end judgment value d27 as the operation abnormality evaluation maximum value.

In the above-described example, the mechanically operated end position abnormal region search unit 611 creates the estimated position d31 with three different amounts of change from the actual position of the mechanically operated end 203, but it may be created by another process. good. For example, the mechanically operated end position abnormal region search unit 611 finely controls the amount of change in the estimated position d31. The mechanical operation end position abnormality area search unit 611 may be changed in a timely manner depending on the situation, such as not performing a search in a direction in which an operation abnormality does not clearly occur. Here, the direction in which the operation abnormality clearly does not occur may be, for example, moving toward the center of the actual position of the mechanical operation end.

The mechanical operation end position abnormality suppression control unit 620 sends the actual position abnormality area operation end determination value d27, which is the output of the mechanical operation end position abnormality region determination unit 610, to the coolant operation end 204 of the second shape control unit 212. A control output to the coolant operating end 204 is created from the control command.

When it is determined that the operation abnormality does not occur even if the mechanical operation end position actual d22 changes by control, the operation using the coolant operation end 204 by the normal second shape control unit 212 is possible. When the operation abnormality evaluation value d26 is not so large, it is possible to combine the control output of the second shape control unit 212 with the abnormality suppression output d28 for suppressing the operation abnormality. Of course, when the operation abnormality evaluation value d26 is large, the abnormality suppression output d28 is preferentially output to the coolant operation end 204.

In the coolant control rule database 623, the correspondence between each mechanical operation end 203 (k) and the influencing coolant operation end 204 is predetermined. This correspondence can be obtained by actually operating the mechanical operation end 203 and the coolant operation end 204 during the rolling operation, and can also be obtained from the actual data by machine learning. Here, a case is considered in which a response is sought and registered in the coolant control rule database 623 based on the result of the actual operation.

[Coolant operation end control output calculation unit configuration and operation]
FIG. 12 shows the configuration and operation of the coolant operation end control output calculation unit 621.
In the coolant control rule database 623 (FIG. 10), the required amount of coolant flow rate change that can obtain the same effect as operating each mechanical operation end 203 (k) is registered. The database search unit 631 shown in FIG. 12 (a) has a mechanical operation end 203 (k) in which an operation abnormality occurs based on the actual position abnormality area operation end determination value d27 obtained by the mechanical operation end position abnormality area determination unit 610. ) Take out the required amount of coolant flow rate change corresponding to the actual position change amount.

Then, the output synthesizing unit 632 adds the required amount of coolant flow rate change for each mechanically operated end 203 (k) taken out, and obtains the abnormality suppression output d28.
For example, when the actual position abnormal region operation end determination value d27 shown in FIG. 11 (d) is obtained in the actual position and estimated position shown in FIGS. 11 (a) and 11 (b), as shown in FIG. 12 (b). Abnormality suppression output d28.
Since the coolant operating end 204 is lubricated and cooled necessary for rolling operation, the maximum flow rate and the minimum flow rate at each point in the plate width direction are often determined as the coolant flow rate, and an operation abnormality occurs. Anomalous suppression output d28 is obtained.

[Output selection processing in the coolant operation end control output selection section]
FIG. 13 shows an output selection process performed by the coolant operation end control output selection unit 622.
The coolant operation end control output selection unit 622 has the abnormality suppression output d28 and the second shape shown in FIG. 10 according to the magnitude of the operation abnormality evaluation maximum value (FIG. 11 (d)) in the actual position abnormality region operation end determination value d27. The shape control output d29 of the control unit 212 is selected or combined and output. The output selected or combined by the coolant operation end control output selection unit 622 is supplied to the coolant operation end 204 as the coolant operation output d30.

When the maximum value of the operation abnormality evaluation shown in FIG. 11D is small, it is unlikely that an operation abnormality will occur even if the shape control is performed as it is. Therefore, the coolant operation end control output selection unit 622 has the shape control output d29. Is directly supplied to the coolant operating end 204 as the coolant operating output d30. That is, the coolant operation output d30 = the shape control output d29.

On the other hand, when the maximum value of the operation abnormality evaluation is large, the coolant operation end control output selection unit 622 determines that there is a high possibility that an operation abnormality will occur. At this time, as shown in FIG. 13B, the abnormality suppression output d28 is generated, and the coolant operation end control output selection unit 622 maximizes the effect of the abnormality suppression output d28 within the maximum and minimum values of the coolant flow rate. Therefore, the coolant operation output d30 is set as shown in FIG. 13 (a).

If the maximum operation abnormality evaluation value is not so large, the coolant operation end control output selection unit 622 adds and outputs the shape control output d29 and the abnormality suppression output d28 as shown in FIG. 13 (c). At this time, the abnormality suppression output d28 is adjusted and added so that the flow rate at the coolant operating end is within the maximum and minimum values, and is as shown in FIG. 11 (d).
Here, the determination of whether the value of the maximum operation abnormality evaluation value is large, not so large, or small is determined using a threshold value set in advance in the coolant operation end control output selection unit 622. Further, the coolant operation end control output selection unit 622 may always add the shape control output d29 and the abnormality suppression output d28 and output the output. However, in this case, the added abnormality suppression output d28 is prevented from becoming so large.
Further, at the time of addition in the coolant operation end control output selection unit 622, weighting may be used instead of simple addition, and the weighting may be changed according to the maximum operation abnormality evaluation value.

As described above, according to the plant control device of this example, it is possible to execute good shape control while preventing an operation abnormality caused by the mechanical operation end position actual result d22 of the mechanical operation end 203. ..

[Modification example]
The present invention is not limited to the above-described embodiment, and includes various modifications. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to those having all the described configurations.

For example, in the above-described embodiment, the mechanical operation end safe operation range determination unit 205 is realized by machine learning, but by expressing it by a mathematical formula from the operator's experience, the mechanical operation end safe operation range determination unit 205 May be realized. Alternatively, the rolling state at the time of the occurrence of an operation abnormality may be stored in a database, the presence or absence of the corresponding case may be determined, and the mechanical operation end safety operation range determination unit 205 may be realized.
Further, the mechanical operation end safety operation range determination unit 205 may create a numerical model or a symbolic ethics model based on the knowledge of an operator or an operation engineer and use it at the time of machine learning.

Further, in the above-described embodiment, the mechanical operation end position abnormality suppression control unit 620 stores the results obtained by experiments or the like in advance in the coolant control rule database 623 and uses them. On the other hand, the mechanical operation end position abnormality suppression control unit 620 may create a rule base from actual data by using machine learning.
Further, in the above-described embodiment, the shape control of the rolling mill is targeted, but the present invention can also be applied to general plant control.

Further, in a block diagram such as FIG. 1, control lines and information lines are shown only those considered necessary for explanation, and not all control lines and information lines are necessarily shown in the product. In practice, it can be considered that almost all configurations are interconnected.

Further, the processing units such as the control unit described in the above-described embodiment may be configured by dedicated hardware, but by implementing a program (application) in the computer, the above-described embodiment may be implemented. The function of each processing unit described in the above may be realized.
FIG. 14 shows an example of hardware configuration when the plant control device is configured by a computer.
The plant control device (computer) 100 shown in FIG. 14 includes a CPU (Central Processing Unit) 100a, a ROM (Read Only Memory) 100b, and a RAM (Random Access Memory) 100c connected to the bus, respectively. Further, the plant control device 100 includes a non-volatile storage 100d, a network interface 100e, an input / output device 100f, and an output device 100g.

The CPU 100a is an arithmetic processing unit that reads a program code of software that realizes a function performed by the plant control device 100 from the ROM 100b and executes it.
Variables, parameters, etc. generated during the arithmetic processing are temporarily written in the RAM 100c.
For the non-volatile storage 100d, for example, a large-capacity information storage medium such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive) is used. A program (plant control program) that executes a processing function performed by the plant control device 100 is recorded in the non-volatile storage 100d. Further, data necessary for performing machine learning is recorded in the non-volatile storage 100d.

The network interface 100e transmits and receives various information to and from the outside via a LAN (Local Area Network), a dedicated line, and the like.
The input / output device 100f inputs various information from the controlled plant 190 (rolling mill 301) and outputs information for giving instructions to the operation ends 103, 104 (203, 204).
The display device 100g displays the control state of the controlled plant 190 (rolling mill 301).

Information on programs that realize each processing function performed by the plant control device 100 can be stored in a recording medium such as a semiconductor memory, an IC card, an SD card, or an optical disk, in addition to non-volatile storage such as an HDD or SSD. ..

Further, when a part or all of each processing unit of the plant control device is configured by hardware, FPGA (Field Programmable Gate Array) or ASIC (Application Specific Integrated Circuit) may be used.

11 ... Shape detection preprocessing unit, 12 ... Pattern recognition unit, 13 ... Control calculation unit, 14 ... Shape detector, 50 ... Control device, 100 ... Plant control device (computer), 101 ... Calculation unit, 102 ... Third control Unit, 103 ... High-speed operation end, 104 ... Low-speed operation end, 105 ... Safe operation range determination unit, 110 ... Control unit, 111 ... First control unit, 112 ... Second control unit, 190 ... Control target plant, 201 ... Calculation Instrument, 202 ... Mechanical operation end position suppression control unit, 203 ... Mechanical operation end, 204 ... Coolant operation end, 205 ... Mechanical operation end safe operation range determination unit, 210 ... Control unit, 211 ... First shape control unit , 212 ... 2nd shape control unit, 300 ... Material to be rolled, 301 ... Rolling machine, 302 ... Input side tension reel (Inlet side TR), 303 ... Outer side tension reel (Outside TR), 304 ... Mill speed control unit , 305 ... Enter TR control unit, 306 ... Outer tension reel control unit, 307 ... Roll gap control unit, 308 ... Enter tension meter, 309 ... Outer tension meter, 310 ... Rolling speed setting unit, 311 ... Enter side Tension setting unit, 312 ... Outer side tension setting unit, 313 ... Incoming side tension control unit, 314 ... Outer side tension control unit, 315 ... Int side tension current conversion unit, 316 ... Outer side tension current conversion unit, 317 ... Outer side plate Thickness gauge, 318 ... Outer plate thickness control mounting unit, 319 ... Roll gap setting unit, 401 ... Work roll, 402 ... 1st intermediate roll, 403 ... 2nd intermediate roll, 404 ... AS-U roll, 405 ... Split roll, 406 ... Saddle, 501 ... Input data creation unit, 502 ... Neural net, 503 ... Neural net learning control unit, 504 ... Neural net selection unit, 505 ... Teacher data creation unit, 506 ... Operation abnormality judgment unit 511 ... Learning data database 512 ... Control rule database, 610 ... Mechanical operation end position abnormality area determination unit, 611 ... Mechanical operation end position abnormality area search unit, 612 ... Input data creation unit, 613 ... Output data determination unit, 620 ... Mechanical operation End position abnormality suppression control unit, 621 ... Coolant operation end control output calculation unit, 622 ... Coolant operation end control output selection unit, 623 ... Coolant control rule database, 631 ... Database search unit, 632 ... Output synthesis unit, 901 ... Computer , 902 ... 1st shape control unit, 903 ... 2nd shape control unit, 904 ... mechanical operation end, 905 ... coolant operation end, 990 ... rolling mill, d11 ... first state quantity target, d12 ... first state quantity, d13 ... second state quantity, d14 ... safe operation range, d21 ... target type State, d22 ... Mechanical operation end position result, d23 ... Shape result, d24 ... Rolling result, d25 ... Mechanical operation end safe operation range, d26 ... Operation abnormality evaluation value, d27 ... Actual position abnormality area operation end judgment value, d28 ... Abnormality suppression output, d29 ... Shape control output, d30 ... Coolant operation output, d31 ... Estimated position, d32 ... Operation abnormality judgment value

Claims (7)

It is a plant control device that performs a first operation process having a predetermined response speed to an operation and a second operation process having a slower response speed to an operation than the first operation process for a controlled plant.
A first control unit that acquires a target state quantity of the controlled plant and gives an instruction for the first operation process.
A second control unit that acquires a target state quantity of the controlled plant and gives an instruction for the second operation process.
A first operation end that executes the first operation process of the controlled plant according to an instruction from the first control unit, and
A second operation end that executes the second operation process of the controlled plant according to an instruction from the second control unit, and
A safety operation range determination unit that determines a safe operation range of the first operation process by the first operation end based on the results of the first operation end, and a safety operation range determination unit.
When the first operation process by the first operation end is not in the safe operation range at the judgment of the safe operation range determination unit, the instruction of the second operation process by the second control unit is corrected or changed. A plant control device including a third control unit that moves the actual position of the first operation process by the first operation end to an actual position where the occurrence of an operation abnormality is not estimated. The first operation process performed by the first operation end has a faster control time response than the second operation process, and has a limited effect on the controlled state quantity of the controlled plant.
The second operation process by the second operation end has a control time response slower than that of the first operation process, and affects the entire controlled state quantity of the controlled plant. Item 1. The plant control device according to item 1. The safe operation range determination unit recognizes the occurrence of an operation abnormality by using the actual data of the controlled plant, and learns the relationship between the actual data and the operation abnormality by using the actual data at the time of the occurrence of the operation abnormality as teacher data. The plant control device according to claim 1, wherein the safe operation range is determined. The plant control device according to claim 3, wherein the relationship between the actual data and the operation abnormality is obtained by machine learning based on the collected actual data. The controlled plant is a rolling mill.
The first operation process is a mechanical shape operation process that changes the shape in the mechanical structure.
The second operation process is a coolant shape operation process that changes the shape by changing the injection amount of the coolant in the plate width direction.
The safe operation range determination unit determines the safe operation range of the first operation process based on the actual value of the mechanical position of the first operation end so as not to cause an operation abnormality.
When the occurrence of an operation abnormality is presumed by the safe operation range determination unit, the third control unit outputs the control output of the coolant shape control at the second operation end to the coolant shape control so that the operation abnormality does not occur. According to any one of claims 1 to 4, the actual position of the mechanical shape operation processing by the first operation end is moved to the actual position where the occurrence of an operation abnormality is not estimated by changing the output to perform the above. Plant control device. For the controlled plant, the arithmetic processing unit performs the first operation processing having a predetermined response speed to the operation and the second operation processing having a slower response speed to the operation than the first operation processing. It is a plant control method
A first control procedure in which the arithmetic processing unit acquires a target state quantity of the controlled plant and gives an instruction for the first operation processing.
A second control procedure in which the arithmetic processing unit acquires a target state quantity of the controlled plant and gives an instruction for the second operation processing.
A first operation execution procedure in which the arithmetic processing unit executes the first operation process of the controlled plant according to an instruction according to the first control procedure.
A second operation execution procedure in which the arithmetic processing unit executes the second operation process of the controlled plant according to the instruction according to the second control procedure.
Based on the results of the first operation process, the arithmetic processing unit determines the safe operation range of the first operation process according to the first operation execution procedure, and the safety operation range determination procedure.
If the first operation process according to the first operation execution procedure is not within the safe operation range based on the determination by the safe operation range determination procedure, the arithmetic processing unit performs the second operation process according to the second control procedure. A plant control method including a third control procedure in which an instruction is corrected or changed to move the actual position of the first operation process according to the first operation execution procedure to an actual position where the occurrence of an operation abnormality is not estimated. A program that causes a computer to execute a first operation process having a predetermined response speed to an operation and a second operation process having a slower response speed to an operation than the first operation process for a controlled plant. ,
A first control procedure for acquiring a target state quantity of the controlled plant and instructing the first operation process, and
A second control procedure for acquiring a target state quantity of the controlled plant and instructing the second operation process, and
A first operation execution procedure for executing the first operation process of the controlled plant according to an instruction according to the first control procedure, and
A second operation execution procedure for executing the second operation process of the controlled plant according to the instruction according to the second control procedure, and
Based on the results of the first operation process, the safe operation range determination procedure for determining the safe operation range of the first operation process according to the first operation execution procedure, and the safe operation range determination procedure.
If the first operation process according to the first operation execution procedure is not within the safe operation range, the instruction of the second operation process according to the second control procedure is corrected or changed by the judgment according to the safety operation range determination procedure. The third control procedure for moving the actual position of the first operation process according to the first operation execution procedure to the actual position where the occurrence of an operation abnormality is not estimated.
A program that causes the computer to execute.

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