Control system

Abstract

To provide a control system capable of maintaining control performance for a controlled object even in an environment with disturbances.SOLUTION: A control system includes: a state estimation unit that estimates a first estimated value of a first state variable indicating a state of a controlled object based on a model of the controlled object and an operation amount for controlling the controlled object; a soft sensor that estimates a second estimated value of the first state variable based on a measurement value of a sensor provided in the controlled object, a command value for the controlled object, and a signal obtained by combining noise and disturbance; and a correction unit that corrects the operation amount based on a first difference between the first and second estimated values so that the first difference is suppressed.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a control system. [Background technology]

[0002] 2. Description of the Related Art There is known a control device that controls a controlled object while estimating state variables of the controlled object based on an output from a software sensor corresponding to a predetermined input.

[0003] For example, Patent Document 1 describes a control device that includes a software sensor that receives an operation amount and estimates a control amount of a controlled object, and a controller that receives the control amount estimated by the software sensor and outputs the operation amount. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication 2019-008534 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the control device described in Patent Document 1, the output of the soft sensor does not include information on disturbance acting on the controlled object.

[0006] Therefore, since a disturbance acting on the controlled object is not reflected in the manipulated variable, there is a risk that the control performance for the controlled object will deteriorate in an environment in which the disturbance to the controlled object is large.

[0007] The present invention has been made in consideration of the above problems, and has an object to provide a control system that is capable of maintaining control performance for a controlled object even in an environment where there is a disturbance. [Means for solving the problem]

[0008] One invention for achieving the above-mentioned object is a control system including a state estimation unit that estimates a first estimate of a first state variable indicating a state of a controlled object based on a model of the controlled object and a manipulated variable for controlling the controlled object, a soft sensor that estimates a second estimate of the first state variable based on a measurement value of a sensor provided in the controlled object and a signal that combines a command value for the controlled object, noise and disturbance, and a correction unit that corrects the manipulated variable based on a first difference between the first and second estimated values ​​so that the first difference is suppressed. Effect of the Invention

[0009] According to the present invention, it is possible to provide a control system capable of maintaining control performance for a controlled object even in an environment where there is a disturbance. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram for explaining an overview of a crane 10. [Diagram 2] FIG. 2 is a diagram showing an example of the configuration of a crane 10. [Diagram 3] FIG. 2 illustrates an example of a control system 30. [Figure 4] FIG. 13 is a diagram for explaining state variables. [Diagram 5] FIG. 1 illustrates a conventional control system 32. [Figure 6] FIG. 4 is a diagram showing an example of a simulation result of the control system 30. [Figure 7] FIG. 2 is a diagram illustrating an example of a control system 31. [Figure 8] FIG. 13 is a diagram for explaining state variables. [Figure 9] FIG. 13 is a diagram for explaining the correspondence of variable names. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] At least the following points will become apparent from the description of this specification and the accompanying drawings.

[0012] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. The same or equivalent components, members, etc. shown in each drawing are designated by the same reference numerals, and duplicated descriptions will be omitted as appropriate.

[0013] == Implementation form == <<<Overview of CRANE 10>>> 1 is a diagram showing an overview of an overhead crane 10 (hereinafter simply referred to as a crane) capable of movement on three axes: traveling (x-axis), traversing (y-axis), and hoisting (z-axis). The crane 10 includes a trolley 20 that is entirely movable in the x-axis direction and that is movable in the y-axis direction along a girder (not shown), and a load 21 suspended by a wire rope that can be hoisted up or down from the trolley 20.

[0014] In the following, in this embodiment, the coordinates of the trolley 20 are expressed as (x, y, 0), and the coordinates of the suspended load 21 are expressed as (x ~ ,y ~ ,z ~ ) is expressed as "x ~ ", "y ~ "," z ~ " are the same as the symbols (1) to (3) below. Also, the swing width θ of the suspended load 21 is evaluated by the angle φ when the suspended load 21 is projected onto the xy plane, the angle α when the suspended load 21 is projected onto the xz plane, and the angle β when the suspended load 21 is projected onto the yz plane. TIFF2025005954000002.tif19150<<<Modeling of Trolley 20>>>

[0015] 2 is a diagram showing an example of the configuration of the trolley 20 and the suspended load 21. For convenience, only the minimum configuration required for modeling the trolley 20 and the suspended load 21 is shown.

[0016] The trolley 20 includes a control system 30, a motor 40, and a sensor 41. As will be described in detail later, the control system 30 receives a command value u x , the command value u in the y-axis direction y , command value u in the z-axis direction zis output to the motor 40. In the following, the command values ​​for the three axes, x-axis to z-axis, will be collectively referred to as command value u.

[0017] The motor 40 is driven by a command value u x The crane 10 itself is moved in the x-axis direction based on the command value u y Based on the command value u, the wheels of the trolley 20 are rotated to move the trolley 20 in the y-axis direction along the girder (not shown). z Based on this, the wire rope to which the load 21 is connected is wound up or down in the z-axis direction.

[0018] When the trolley 20 operates according to a command value u from the control system 30, the following equations (1) to (3) are established. In the following, in this embodiment, the "movement of the trolley 20" includes the movement of the crane 10 itself and the movement of the trolley 20 on the girder.

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[0019] Here, the crane 10 and the trolley 20 have a first-order lag characteristic, the gain of the motor 40 is "K", and the time constant of the motor 40 is "T". For this reason, for example, the gain of the motor 40 in the x-axis direction is K x The time constant of the motor 40 in the x-axis direction is T x In addition, the term on the left side of equation (1) represents the second derivative of "x" with respect to time t, and the symbol for x on the right side represents the first derivative of "x" with respect to time t.

[0020] <<<Modeling of Suspended Load 21>>> The equation of motion for the load 21 is transformed to define the mass of the load 21 as "m", the gravitational acceleration as "g", and the damping coefficient in the x direction as "D α ” and the damping coefficient in the x direction is “D β " Then, the following equations (4) and (5) hold for the suspended load 21.

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[0021] <<<State Space Model>>> Since the formulas (1) to (5) include second-order differentials, they are converted here into expressions including only first-order differentials in order to facilitate the analysis of the crane 10. Specifically, the formulas (1) to (5) are expressed as the following formula (6).

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[0022] Here, "x1", "y1", "z1", "x ~ 1," "y ~ "1" is a symbol defined to avoid the use of the second-order differential symbol. In addition, when equation (6) is rearranged into a state space model, the following equation (7) is obtained.

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[0023] In equation (7), the state vector x contains 10 state variables in the state space model. p , the command value vector u, matrix A, and matrix B are as shown below.

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[0024] In this way, the crane 10 controlled by the control system 30 can be expressed by a state space model such as that shown in equation (7).

[0025] Here, of the ten state variables, x is the position of the trolley 20 in the x-axis direction (traveling), dx / dt is the speed of the trolley 20 in the x-axis direction, Δx is the swing width of the load 21 in the x-axis direction, and dΔx / dt is the speed of the swing width of the load 21. Furthermore, y is the position of the trolley 20 in the y-axis direction (traversal), dy / dt is the speed of the trolley 20 in the y-axis direction, Δy is the swing width of the load 21 in the y-axis direction, and dΔy / dt is the speed of the swing width of the load 21. Furthermore, z is the hoisting position, and dz / dt is the hoisting speed.

[0026] 2 in this embodiment measures only the speed of the trolley 20 in the x-axis direction (dx / dt), the speed of the trolley 20 in the y-axis direction (dΔy / dt), and the hoisting speed (dz / dt) out of the 10 state variables. In other words, in the crane 10, only three state variables out of the 10 state variables are measured.

[0027] The position (x) of the trolley 20 in the x-axis direction (travel) is calculated by integrating the speed (dx / dt) over time t. The position (y) of the trolley 20 in the y-axis direction (traverse) is calculated by integrating the speed (dΔy / dt) over time t. The hoisting position (z) is calculated by integrating the hoisting speed (dz / dt) over time t.

[0028] <<<Details of control system 30>>> 3 is a block diagram showing an example of the configuration of the control system 30. The control system 30 is a continuously operating system that controls the crane 10, and includes a controller 50, adders 51 and 56, a soft sensor 53, and a state estimation unit 55. First, a block diagram of the crane 10, which is the object to be controlled, will be described here.

[0029] <<About Crane 10>> The state equation of the crane 10 is expressed by the above-mentioned equation (7), and further, the output equation of the crane 10 is expressed by equation (13).

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[0030] The crane 10 includes blocks 100, 102 to 105 which embody equations (7) and (13), and an adder 101. Block 100 is a block which multiplies an input command value by matrix B of equation (7), and adder 101 adds an output from adder 106 (described later) and an output from block 103 (described later). Block 102 integrates the output from adder 101 to calculate a state variable x p Block 103 outputs the state variable x p by the matrix A of equation (7). In this way, blocks 100, 102, 103 and adder 101 calculate equation (7) for a command value (for example, command value u) input to the crane 10.

[0031] And, the block 104 is a block corresponding to the matrix C of the above-mentioned equation (13). In this embodiment, as described above, the sensor 41 of the crane 10 measures only the speed (dx / dt) of the trolley 20 in the x-axis direction, the speed (dΔy / dt) of the trolley 20 in the y-axis direction, and the hoisting speed (dz / dt).

[0032] Block 104 then calculates the position (x) of the trolley 20 in the x-axis direction (travel) by integrating the speed (dx / dt) over time t. Block 104 also calculates the position (y) of the trolley 20 in the y-axis direction (traverse) by integrating the speed (dΔy / dt) over time t. Block 104 also calculates the hoisting position (z) by integrating the hoisting speed (dz / dt) over time t.

[0033] Therefore, block 104 converts only six of the ten state variables into measurements and the calculated position y p The output is as follows:

[0034] The six state variables here are the velocities (dx / dt, dy / dt, and dz / dt) measured by the sensor 41, as well as the positions (x, y, and z) calculated based on these measured values.

[0035] That is, the measured value and the calculated position y p is expressed as follows:

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[0036] A block 105 is a block that indicates the influence of a disturbance d and noise w acting on the crane 10. The influence of the disturbance d and noise w is output to an adder 106.

[0037] The adder 106 adds the output of the block 100 and the output of the block 105 and outputs the result to the adder 101 .

[0038] <<Regarding the controller 50>> The controller 50 includes a DSP (Digital Signal Processor) and a storage device (neither shown). The DSP executes a predetermined program stored in the storage device to realize various functions of the controller 50.

[0039] The storage device includes a non-transient (e.g., non-volatile) storage device that stores various data executed or processed by the DSP. The storage device further includes, for example, a RAM (Random-Access Memory) or the like (a memory to be described later), which is used as a temporary storage area for various programs, data, and the like.

[0040] The controller 50 receives state variables x from a controller (not shown) of the crane 10. p A predetermined target value r of the state vector x^ estimated by the state estimation unit 55 described later. p (corresponding to the "first estimated value") and the difference e, the operation amount u for controlling the crane 10 is calculated. K The correspondence between the variable names used in this specification is shown in FIG.

[0041] The controller 50 executes a program stored in the storage device, whereby the block 60, the adders 61 and 63, and the block 62 are realized.

[0042] As shown in equation (8), the state variable x p consists of 10 components. Therefore, the target value r and the state variable x p It consists of 10 components corresponding to the components of.

[0043] Block 60(K FF ) is a block in which a gain is set for feedforward control of the crane 10. Therefore, the block 60 outputs a command value u for feedforward control of the crane 10 based on the target value r. FF Output.

[0044] The adder 61 receives the target value r and the state vector x^ estimated by the state estimation unit 55. pCalculate the difference e between

[0045] Block 62 (K FB ) is a block in which a gain, a first-order delay element, etc. for feedback control of the crane 10 are set. Therefore, the block 62 outputs a command value u for feedback control of the crane 10 based on the difference e and the set gain, etc. FB The adder 63 outputs a command value u for feedforward control of the crane 10. FF and the command value u for feedback control FB Add and to get the command value u K The output is as follows:

[0046] <<About adder 51>> The adder 51 receives the command value u K and the command value u from block 57(L) described later. L The command value u from block 57 is added to the command value u. L is a command value for canceling disturbance d and noise w, which will be described later.

[0047] <<About SoftSensor 53>> The soft sensor 53 includes a DSP (Digital Signal Processor) and a storage device (neither shown). The DSP executes a predetermined program stored in the storage device to realize various functions of the soft sensor 53.

[0048] The storage device includes a non-transient (e.g., non-volatile) storage device that stores various data executed or processed by the DSP. The storage device further includes, for example, a RAM (Random-Access Memory) or the like (memory described below), which is used as a temporary storage area for various programs, data, etc. As a result of the execution of the programs, the soft sensor 53 realizes the following functions.

[0049] The soft sensor 53 detects the measured value y of the sensor 41 provided on the crane 10 (the object to be controlled). p and the signal u, which is the output from the adder 106. SS Based on and, the state variable x p (Equivalent to the "first state variable" (Figure 9)) Estimated value x pt (corresponding to the "second estimate" (Figure 9)). Note that the signal u SS is an output from block 100, and is a signal obtained by combining a command value for the controlled object, noise w, and disturbance d.

[0050] As shown in equation (8), in this embodiment, the state variable x p consists of 10 components. Also, as shown in equation (14), the measurement value y p has six components. Therefore, the soft sensor 53 outputs an estimated value x pt will be output.

[0051] In this embodiment, the measured value y p The six components of are the estimates x pt Even in this case, the estimated value x pt We refer to all components of as the "estimates".

[0052] <<State Estimation Unit 55>> The state estimation unit 55 includes a DSP (Digital Signal Processor) and a storage device (neither shown). The DSP executes a predetermined program stored in the storage device to realize various functions of the state estimation unit 55.

[0053] The storage device includes a non-transient (e.g., non-volatile) storage device that stores various data executed or processed by the DSP. The storage device further includes, for example, a RAM (Random-Access Memory) or the like (a memory to be described later), which is used as a temporary storage area for various programs, data, and the like.

[0054] The state estimation unit 55 estimates the model 70 of the crane 10 and the operation amount u from the controller 50. K and the measurement value y from the sensor 41 p and a state variable x indicating the state of the crane 10 based on p (Equivalent to the "first state variable" (Figure 9)) p (corresponding to the “first estimate” (Figure 9)).

[0055] The state estimation unit 55 also estimates the measured value y p The estimated value y^ corresponding to p (corresponding to the “third estimate” (Figure 9)) is further estimated.

[0056] Then, the state estimation unit 55 calculates the measured value y p and the estimated value y^ p The difference between ε^ p (corresponding to the "second difference" (Figure 9)) based on the difference ε^ p The estimate x^ is suppressed p Estimate.

[0057] The state estimation unit 55 of this embodiment is a Luenberger type estimator that estimates 10 state variables. In the state estimation unit 55, a model 70, an adder 71, and a block 72 are realized as a result of executing a program stored in a storage device. The model 70 is configured to include a block (not shown) that executes equations (7) and (13), similar to the crane 10. Details of the model 70 will be described later.

[0058] <<Adder 71 and block 72(K)>> Adder 71 receives the estimate y p and the estimated value y^, which is the output from model 70. p Difference from ε^ y Block 72 calculates the difference ε̂ y This block multiplies the difference ε̂ y The gain of the Kalman filter is adjusted appropriately so that

[0059] <<Details of Model 70>> The model 70 includes blocks 80, 82 to 84, and an adder 81. Here, the blocks 80, 82 to 84 are similar to the blocks 100, 102 to 104, respectively. The adder 81 is similar to the adder 101 except that it adds the output from the block 72.

[0060] By using the state estimation unit 55 having such a configuration, the block 82 estimates the estimated value x̂ p In other words, the 10 state variables shown in Figure 4 are estimated. Also, the estimated value x^ p is output to the controller 50 described above and to an adder 56 described below.

[0061] <<Adder 56 and Block 57>> The adder 56 and the block 57 are, for example, blocks for removing disturbance d and noise w.

[0062] The adder 56 receives the output x from the soft sensor 53. pt and the estimated value x^ from the state estimation unit p Block 57(L) calculates the difference ε between the command value u and the L is output to the adder 51. As a result, disturbances d and the like included in the command value u output from the adder 51 to the actual crane 10 are reduced.

[0063] The configuration of the control system 30 of this embodiment has been described above. Note that the block 57 corresponds to the "correction unit." In other words, the "correction unit" is a unit that corrects the estimated value x^ p and the estimated value x pt Based on the difference ε between the two (corresponding to the "first difference" (Figure 9)), the manipulated variable u is adjusted so that the difference ε is suppressed. K The command value u for correcting L Output.

[0064] Although the control system 30 of the present embodiment is a control system that operates continuously, it may be a control system that operates discretely. In this case, a Kalman filter type state estimator may be used instead of the Luenberger type state estimator.

[0065] <<<Simulation results>>> A comparison was made by a numerical simulation between the control system 30 of this embodiment and a conventional control system 32. First, the conventional control system 32, which is a comparative example, will be described. FIG.

[0066] The conventional control system 32 is different from the present embodiment shown in FIG. 3 in that it does not include the adder 51, the adder 56, and the block 57. That is, in the conventional control system 32, the manipulated variable u K is not corrected and is output to block 100 as is.

[0067] FIG. 6 is a diagram showing an example of a simulation result of the control system 30. Here, in the control system 30, the command value u FF Feedforward control based on the command value u FB Feedback control based on and command value u L It is assumed that disturbance feedback control (DFC) based on the above is functioning.

[0068] In Fig. 6, the solid line indicates the result of this embodiment, and the dotted line indicates the result of the conventional technology. The horizontal axis of each graph in Fig. 6 is time (seconds), which is the same for all graphs. In Fig. 6, first, (a) and (e) are the command values ​​for the speed of the trolley 20 in the x-axis and y-axis directions, respectively. Also, (i) is the command value for the hoisting speed.

[0069] Additionally, (b) and (f) are the positions of the trolley 20 in the x-axis and y-axis directions, respectively. Additionally, (j) is the hoisting position. Additionally, (c) and (g) are the measured values ​​of the swing width of the suspended load 21 in the x-axis and y-axis directions, respectively. Additionally, (d) and (h) are the measured values ​​of the swing width of the suspended load 21 in the x-axis and y-axis directions, respectively.

[0070] <Evaluation of transportation> As shown by the command values ​​in (a) and (e), the transport was controlled to accelerate, move at a constant speed, and decelerate in the positive direction of the x-axis and y-axis from 5 seconds to 12 seconds. Also, as shown by the command value in (i), the transport was controlled to accelerate, move at a constant speed, and decelerate during this period.

[0071] Regarding the control of the transport, as shown in the figure, no significant difference was confirmed in the response to control between this embodiment and the prior art. After transport, the trolley stops at the stop position in both cases ((b) and (f)), and the suspended load vibrates with a small amplitude around the equilibrium point ((d) and (h)).

[0072] <Collision evaluation> Following the evaluation of transportation, we evaluated collisions. First, at the 25-second mark, we applied a disturbance that assumed an object moving in the x-axis direction would collide with the trolley. Then, at the 30-second mark, we applied a disturbance that assumed an object moving in the y-axis direction would collide with the trolley.

[0073] In response to these disturbances, the load begins to vibrate with a significant amplitude in both this embodiment and the prior art ((d) and (h)). Here, it can be seen that the amplitude of the load is smaller in this embodiment than in the prior art, and the load quickly converges to the equilibrium point.

[0074] From the above results, it is expected that the control system 30 of this embodiment can maintain the control performance for the controlled object even in an environment with disturbance.

[0075] ==Second embodiment== 7 is a block diagram showing an example of the configuration of the control system 31 of this embodiment. Although details will be described later, the control system 31 of this embodiment includes a soft sensor 58 instead of the soft sensor 53 of the first embodiment.

[0076] Fig. 8 is a diagram for explaining state variables of this embodiment. In this embodiment, the sensor 41 of the crane 10 measures only the hoisting speed (dz / dt). That is, while the crane 10 is provided with three sensors 41 in the first embodiment, the crane 10 is provided with one sensor 41 in this embodiment. This will be described in detail below.

[0077] First, a description will be given of the block 104. The block 104 is a block corresponding to the matrix C in the above-mentioned equation (8). In this embodiment, as described above, the sensor 41 of the crane 10 measures only the hoisting speed (dz / dt).

[0078] Block 104 then calculates the winding position (z) by integrating the winding speed (dz / dt) over time t.

[0079] Therefore, block 104 converts only the winding position (z) and the winding speed (dz / dt) of the ten state variables into the measured value y p to the soft sensor 58.

[0080] The soft sensor 58 includes two soft sensors 58a and 58b. The soft sensor 58a receives a measurement value consisting of two components and a calculated winding position y p Based on the 10 state variables x p Of these, six state variables x p1 The estimate of x pt1 The measured value and the calculated winding position y p " to simply write "Measurement value y p "It is sometimes referred to as ".

[0081] The soft sensor 58a has six state variables x p1The estimate of x pt1 Of these, for the winding position (z) and winding speed (dz / dt), the output of block 104 is output as is.

[0082] The soft sensor 58a also has six state variables x p1 The estimate of x pt1 Of these, the position (x and y) and speed (dx / dt and dy / dt) of the trolley 20 are calculated and output based on the hoisting position (z) and hoisting speed (dz / dt).

[0083] These six state variables x p1 The estimate of x pt1 is the measured value y p That is, in the control system 31 of the present embodiment, the sensor 41 and the soft sensor 58a play the role of the sensor 41 in the control system 31 of the first embodiment.

[0084] The soft sensor 58b estimates the value x pt1 Based on the 10 state variables x p The estimate of x pt These 10 state variables x p The estimate of x pt The estimated value x in the first embodiment pt is the same as:

[0085] That is, the soft sensor 58 receives the measurement y p Based on this, the state variable x p1 (Equivalent to the "second state variable" (Figure 9)) Estimated value x pt1 (corresponding to the “fourth estimated value” (FIG. 9)). Here, the second state variable is composed of components that are greater in number than the number of sensors 41.

[0086] The state estimation unit 55 estimates the value x pt1 The estimated value y^ corresponding to p (corresponding to the "5th estimate" (Figure 9)) and estimate x pt1 and the estimated value y^ p The difference between ε^ p(corresponding to the "third difference" (Figure 9)) based on the difference ε^ p The estimate x^ is suppressed p Estimate.

[0087] By adopting the above-mentioned configuration, the number of sensors 41 provided in the crane 10 can be reduced.

[0088] <<<Others>>> In this embodiment, the crane 10 has been described as an example of a controlled object, but the controlled object is not limited to this. For example, the controlled object may be a refrigeration system that keeps the temperature inside the storage constant. In a refrigeration system, a method of controlling the superheat temperature at the evaporator outlet to be constant (constant superheat control) and a method of controlling the suction pressure of the compressor to be constant (constant suction pressure control) are generally used.

[0089] However, since pressure sensors are expensive, if state estimation can be performed instead of introducing a sensor, costs can be reduced. On the other hand, thermocouples for measuring superheat temperature are inexpensive, and since the characteristics of the superheat vary greatly depending on the operating conditions, it is desirable to introduce a sensor. Thus, in the refrigeration system, an embodiment in which the suction pressure is estimated using only a thermocouple sensor and a refrigeration system model is conceivable.

[0090] In such a case, the output from the thermocouple sensor corresponds to the "first state variable" and the value indicative of the pressure of the refrigeration system model corresponds to the "second state variable."

[0091] =====Summary===== The control systems 30 and 31 of the above-described embodiments include a model of a controlled object and a manipulated variable u for controlling the controlled object. K Based on this, the first state variable x p First estimate of x^ p and a state estimation unit that estimates the measured value y p and the signal u, which is a combination of the command value for the control object, noise, and disturbance. SS Based on and, the first state variable x pThe second estimate of x pt A soft sensor that estimates the first estimate x^ p and the second estimate x pt Based on the first difference ε, the manipulated variable u is calculated so that the first difference ε is suppressed. K and a correction unit that corrects the

[0092] According to this configuration, the disturbance acting on the controlled object is reflected in the manipulated variable. It is possible to maintain the control performance for the controlled object even in an environment with external disturbances.

[0093] In the control system 30 of the first embodiment, the state estimation unit p The third estimate y^ corresponding to p Further estimate the measured value y p and the third estimate y^ p The second difference ε^ p Based on the second difference ε^ p The first estimate x is chosen so that p According to this configuration, it is possible to maintain better control performance for the controlled object in an environment where there is a disturbance.

[0094] In the control system 31 of the second embodiment, the soft sensor 58 receives the measurement value y p Based on the above, a fourth estimate x of a second state variable, which is made up of components that are greater than the number of sensors 41 and indicates the state of the controlled object, is calculated. pt1 The state estimation unit estimates the fourth estimate x pt1 The fifth estimate y^ corresponding to p and the fourth estimate x pt1 and the fifth estimate y^ p The third difference ε^ p Based on the third difference ε^ p The first estimate x is chosen so that p According to this configuration, the number of sensors 41 provided in the crane 10 can be reduced.

[0095] In the control systems 30 and 31 of the embodiments, the state estimator may be a Kalman filter type or Luenberger type state estimator. With this configuration, the accuracy of state estimation by the state estimator 55 is improved.

[0096] The control systems 30 and 31 of the embodiment include a first state variable x p Given a target value r and a first estimate x p Based on the difference e, the manipulated variable u K With this configuration, it is possible to perform desired control on a controlled object in accordance with a predetermined target value.

[0097] The above-mentioned embodiment is for the purpose of facilitating understanding of the present invention, and is not intended to limit the present invention. Furthermore, the present invention can be modified or improved without departing from the spirit of the present invention, and it goes without saying that the present invention includes equivalents thereof. [Explanation of symbols]

[0098] 10. Crane 20 Trolley 21 Hanging load 30,31 Control System 40 Motor 41 Sensors 50 Controller 51,56,61,63,71,81,101 Adder 53, 58, 58a, 58b Soft Sensor 70 Models 55 State Estimation Unit 60,62,72,80,82,83,84,100,102,103,104 blocks

Claims

1. a state estimation unit that estimates a first estimate value of a first state variable indicating a state of the controlled object, based on a model of the controlled object and a manipulated variable for controlling the controlled object; a software sensor that estimates a second estimate value of the first state variable based on a measurement value of a sensor provided in the control object and a signal obtained by combining a command value for the control object, noise, and disturbance; a correction unit that corrects the manipulated variable based on a first difference between the first and second estimated values ​​so that the first difference is suppressed; a control system.

2. 2. The control system of claim 1, The state estimation unit is further estimating a third estimate corresponding to the measurement; estimating the first estimate based on a second difference between the measurement value and the third estimate such that the second difference is suppressed; Control system.

3. 2. The control system of claim 1, the soft-sensor estimates a fourth estimate of a second state variable indicative of a state of the controlled object, the second estimate having components greater than the number of the sensors, based on the measured values; The state estimation unit is estimating a fifth estimate corresponding to the fourth estimate; estimating the first estimate based on a third difference between the fourth estimate and the fifth estimate such that the third difference is suppressed; Control system.

4. 2. The control system of claim 1, The state estimation unit is a Kalman filter type or Luenberger type state estimator. Control system.

5. A control system according to any one of claims 2 to 4, a controller that outputs the manipulated variable based on a difference between a predetermined target value of the first state variable and the first estimated value. Control system.

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