Rolling mill gauge control system based on augmented structure and control method, device and medium thereof

Abstract

The application discloses a rolling mill thickness control system based on an augmented structure and a control method, equipment and medium thereof, and the system comprises a position sensor, a thickness sensor and a hydraulic sensor, and an augmented structure joint estimator and a thickness controller are further included.The position sensor is used to collect rolling mill oil cylinder piston displacement measurement values; the thickness sensor is used to collect rolling piece outlet thickness measurement values; the hydraulic sensor is used to collect load pressure measurement values; the augmented structure joint estimator is used to estimate the state of the rolling mill thickness control system based on the rolling mill oil cylinder piston displacement measurement values, the rolling piece outlet thickness measurement values and the load pressure measurement values; and the thickness controller is used to calculate the current applied to a servo amplifier as a control signal of the servo amplifier based on the estimated state of the rolling mill thickness control system; and the servo amplifier is used to control the rolling piece outlet thickness.The application can reduce downtime and maintenance costs, isolate the influence of sensor failure on the system, improve the intelligent level of the system, and meet the complex control requirements of high reliability and high efficiency.

Description

Technical Field

[0001] This invention relates to automatic control technology, specifically to a mill thickness control system based on an augmented structure, and its control method, equipment, and medium. Background Technology

[0002] With the widespread application of thin strip steel, countries are increasingly stringent in their requirements for the thickness accuracy of plate and strip steel. Many enterprises have introduced modern control theory into their production processes, deeply integrating it with rolling mill manufacturing, thereby promoting the rapid improvement of thickness control technology. However, rolling mills are inevitably subject to external interference during operation, such as roll eccentricity, poor steel meshing, or steel spillage, which not only increases the complexity of control system design but may also lead to system instability.

[0003] To meet the stringent requirements of high-precision strip steel production, especially nanometer-level thickness control, traditional linear control systems are increasingly showing their limitations, while nonlinear control technology is gaining attention due to its better alignment with practical needs. Simultaneously, rolling mill thickness control systems frequently face challenges from interference and potential faults, and traditional control strategies struggle to cope with these complexities, limiting system performance improvements. Currently, automation and intelligent control technologies have become important development directions. Intelligent safety control methods, with their ability to handle system nonlinearity, dynamic changes, and fault problems, provide an effective solution for improving control performance and reliability. This technology not only helps improve system accuracy and efficiency but also reduces production costs, aligning with the development needs of modern industry. Therefore, in-depth research into the application of nonlinear control and intelligent safety control in rolling mill thickness control systems has significant theoretical and practical value.

[0004] Traditional methods used in existing rolling mill thickness control systems lack robustness against potential interference and faults. The system is prone to failure or shutdown when a fault occurs, and cannot proactively estimate and isolate faults to improve reliability and safety. Furthermore, due to limitations such as sensor size and installation location, not all system states are measurable, and traditional methods mostly do not involve system state estimation, only using limited information to design control strategies. Therefore, developing joint estimation and safety control technologies for rolling mill thickness control systems to improve system reliability and safety has become crucial for achieving intelligent control of these systems. Currently, research on joint estimation techniques for rolling mill thickness control systems is scarce, thus necessitating the development of such methods. After estimating and reconstructing the system state and faults using joint estimation techniques, how to isolate fault signals while utilizing the reconstructed state information to control the system is also a challenge that needs to be addressed. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a mill thickness control system based on an augmented structure, along with its control method, equipment, and medium. Based on the nonlinear dynamic model of the mill thickness control system, a joint estimation technique based on an augmented structure is developed for mill thickness control systems suffering from sensor failures to simultaneously reconstruct the system state and sensor faults. Based on the reconstructed system state and sensor faults, a safety control scheme is constructed, achieving sensor fault isolation and stable system control.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A mill thickness control system based on augmented structure, comprising:

[0008] Position sensors are used to collect measured values ​​of piston displacement in rolling mill cylinders;

[0009] Thickness sensor, used to collect the thickness measurement value of the rolled piece at the exit;

[0010] Hydraulic sensors are used to acquire load pressure measurements.

[0011] An augmented structure joint estimator is used to estimate the state of the mill thickness control system based on mill cylinder piston displacement measurements, workpiece exit thickness measurements, and load pressure measurements.

[0012] A thickness controller is used to calculate the current applied to the servo amplifier based on the estimated state of the mill thickness control system, and to serve as the control signal for the servo amplifier.

[0013] Servo amplifier, used to control the thickness of the rolled product exit.

[0014] To optimize the above technical solution, the specific measures also include:

[0015] Furthermore, the augmented structure joint estimator is designed based on the augmented structure auxiliary estimation system, which is obtained by augmenting sensor faults based on the dynamic model of the rolling mill thickness control system.

[0016] This invention also proposes a control method for a mill thickness control system based on an augmented structure, comprising the following steps:

[0017] Step 1: Based on the dynamic model of the rolling mill thickness control system, augment sensor faults are obtained to obtain an augmented structure-assisted estimation system;

[0018] Step 2: Design an augmented structure joint estimator based on the augmented structure-aided estimation system;

[0019] Step 3: Initialize the augmented structure joint estimator, set the control gain and auxiliary design matrix of the joint estimator; initialize the thickness controller, set the control gain of the thickness controller;

[0020] Repeat steps 4 through 7.

[0021] Step 4: Collect sensor data from the mill thickness control system, including piston displacement measurement, load pressure measurement, and workpiece exit thickness measurement, and transmit them to the augmented structure joint estimator to estimate the state of the mill thickness control system.

[0022] Step 5: Input the latest estimated status of the mill thickness control system into the thickness controller;

[0023] Step 6: The thickness controller calculates the current to be applied to the servo amplifier based on the latest estimated state of the mill thickness control system, and uses this as the control signal for the servo amplifier;

[0024] Step 7: Input the control signal into the servo amplifier to control the thickness of the rolled piece at the exit.

[0025] To optimize the above technical solution, the specific measures also include:

[0026] Furthermore, the dynamic model of the rolling mill thickness control system is as follows:

[0027]

[0028] C = [0 0 1 0]

[0029]

[0030] In the formula, It is the state vector of the rolling mill thickness control system. It is the first derivative of x(t), X P (t) is the actual value of the piston displacement in the rolling mill cylinder, X D It is the expected value of the piston displacement in the rolling mill cylinder. It is X P The first derivative of (t), P L (t) is the actual value of the mill load pressure, P D It is the expected load pressure, H O (t) is the actual thickness of the rolled piece at the exit, H D Here, A is the expected thickness at the exit of the rolled piece, B is the system matrix, u(t) is the control signal, φ(x,t) is the nonlinear characteristic of the system, y(t) is the sensor output signal, C is the output matrix, N is the sensor fault matrix, and f is the input matrix. s (t) represents a sensor fault. b1, b2, b3, b4, b5, b6, b7, and g are symbols used for simplicity. M T It is the effective mass of the moving parts of the rolling mill roll system, K T It is the load elastic stiffness coefficient, B PA is the viscosity coefficient of the moving parts. P Where α is the effective area of ​​the hydraulic cylinder piston, W is the plastic stiffness coefficient of the rolled piece, α is the bulk modulus of elasticity, V is the total volume of the hydraulic cylinder oil chamber, and K is the effective area of ​​the hydraulic cylinder piston. C It is the servo flow amplification factor, C T It is the leakage coefficient of the hydraulic cylinder, T H It is the inertial time constant, K SV It is the total magnification factor, K SV =K Q K V K P K Q It is the flow amplification factor, K V It is the valve core displacement amplification factor, K P φ1(x,t) is the amplification factor of the valve core displacement, φ2(x,t) is the first unknown nonlinear term, φ3(x,t) is the second unknown nonlinear term, and φ3(x,t) is the third unknown nonlinear term.

[0031] Further, in step 1, the expression for the augmented structure-assisted estimation system is as follows:

[0032]

[0033] In the formula, x(t) is the state vector of the rolling mill thickness control system. f is the first derivative of x(t). s (t) represents a sensor fault. It is f s The first derivative of (t), E1 is the auxiliary design matrix, I is the identity matrix, C is the output matrix, N is the sensor fault matrix, A is the system matrix, B is the input matrix, u(t) is the control signal, φ(x,t) is the nonlinear characteristic of the system, and y(t) is the sensor output signal.

[0034] Further, in step 2, the expression for the augmented structure joint estimator is as follows:

[0035]

[0036] In the formula, It is an estimate of the state of the augmented structure-aided estimation system. yes The first derivative of E1 is given by E1, where E1 is the auxiliary design matrix, I is the identity matrix, C is the output matrix, N is the sensor fault matrix, A is the system matrix, and B is the input matrix. It is an estimate of the state of the rolling mill thickness control system. This is an estimate of sensor fault, where u(t) is the control signal. This is an estimate of the nonlinearity of the rolling mill thickness control system, where L is the control gain of the joint estimator, and y(t) is the sensor output signal. It is the estimated output of the mill thickness control system.

[0037] Furthermore, in step 3, the expression for the thickness controller is as follows:

[0038]

[0039] In the formula, K1 is the estimated state of the mill thickness control system, K1 is the control gain of the thickness controller, and u(t) is the control signal, i.e., the current to be applied to the servo amplifier.

[0040] The present invention also proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the control method of the mill thickness control system based on the augmented structure as described above.

[0041] The present invention also proposes a computer-readable storage medium storing a computer program, characterized in that the computer program enables a computer to execute the control method of the mill thickness control system based on the augmented structure as described above.

[0042] The beneficial effects of this invention are as follows: This invention develops a joint estimation technique based on augmented structures for rolling mill thickness control systems suffering from sensor failures, enabling online reconstruction of system state and sensor faults, laying the foundation for subsequent safety control. This invention also develops a safety control scheme based on augmented structures, which can reduce downtime and maintenance costs, isolate the impact of sensor failures on the system, improve the system's intelligence level, and is suitable for the complex control requirements of modern industry demanding high reliability and high efficiency. Attached Figure Description

[0043] Figure 1 This is a structural diagram of the mill thickness control system based on the augmented structure proposed in this invention.

[0044] Figure 2 This is a graph showing the thickness error at the exit of the rolled product.

[0045] Figure 3 This is a load pressure error curve.

[0046] Figure 4 This is a graph showing the piston displacement error.

[0047] Figure 5 This is a graph of the control signal. Detailed Implementation

[0048] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0049] Example 1

[0050] This invention proposes a mill thickness control system based on an augmented structure, the structure of which is as follows: Figure 1 As shown, it includes:

[0051] Position sensors are used to collect measured values ​​of piston displacement in rolling mill cylinders;

[0052] Thickness sensor, used to collect the thickness measurement value of the rolled piece at the exit;

[0053] Hydraulic sensors are used to acquire load pressure measurements.

[0054] An augmented structure joint estimator is used to estimate the state of the mill thickness control system based on the measured values ​​of the mill cylinder piston displacement, the measured value of the rolled piece exit thickness, and the measured value of the load pressure. The augmented structure joint estimator is designed based on an augmented structure auxiliary estimation system, which is obtained by augmenting sensor faults based on the dynamic model of the mill thickness control system.

[0055] A thickness controller is used to calculate the current applied to the servo amplifier based on the estimated state of the mill thickness control system, and to serve as the control signal for the servo amplifier.

[0056] Servo amplifier, used to control the thickness of the rolled product exit.

[0057] Example 2

[0058] This invention proposes a control method for a mill thickness control system based on an augmented structure, comprising the following steps:

[0059] Step 1: Based on the dynamic model of the rolling mill thickness control system, augment sensor faults are introduced to obtain an augmented structure-assisted estimation system; the dynamic model of the rolling mill thickness control system is as follows:

[0060]

[0061] C = [0 0 1 0]

[0062]

[0063] In the formula, It is the state vector of the rolling mill thickness control system. It is the first derivative of x(t), X P (t) is the actual value of the piston displacement in the rolling mill cylinder, X D It is the expected value of the piston displacement in the rolling mill cylinder. It is X P The first derivative of (t), P L (t) is the actual value of the mill load pressure, P D It is the expected load pressure, H O (t) is the actual thickness of the rolled piece at the exit, H D Here, A is the expected thickness at the exit of the rolled piece, B is the system matrix, u(t) is the control signal, φ(x,t) is the nonlinear characteristic of the system, y(t) is the sensor output signal, C is the output matrix, N is the sensor fault matrix, and f is the input matrix. s (t) represents a sensor fault. b1, b2, b3, b4, b5, b6, b7, and g are symbols used for simplicity. M T It is the effective mass of the moving parts of the rolling mill roll system, K T It is the load elastic stiffness coefficient, B P A is the viscosity coefficient of the moving parts. P Where α is the effective area of ​​the hydraulic cylinder piston, W is the plastic stiffness coefficient of the rolled piece, α is the bulk modulus of elasticity, V is the total volume of the hydraulic cylinder oil chamber, and K is the effective area of ​​the hydraulic cylinder piston. C It is the servo flow amplification factor, C T It is the leakage coefficient of the hydraulic cylinder, T H It is the inertial time constant, K SV It is the total magnification factor, K SV =K Q K V K P K Q It is the flow amplification factor, K V It is the valve core displacement amplification factor, K P φ1(x,t) is the amplification factor of the valve core displacement, φ2(x,t) is the first unknown nonlinear term, φ3(x,t) is the second unknown nonlinear term, and φ3(x,t) is the third unknown nonlinear term. It satisfies ||φ i (x,t)||2≤ψ||x(t)||, i=1,2,3,ψ is a known positive constant.

[0064] The expression for the augmented structure-aided estimation system is as follows:

[0065]

[0066] In the formula, x(t) is the state vector of the rolling mill thickness control system. f is the first derivative of x(t). s (t) represents a sensor fault. It is f sThe first derivative of (t), E1 is the auxiliary design matrix, and E1 should be selected to make... Full rank; in practical applications, E1 can be chosen as the identity matrix. I is the identity matrix, C is the output matrix, N is the sensor fault matrix, A is the system matrix, B is the input matrix, u(t) is the control signal, φ(x,t) is the nonlinear characteristic of the system, and y(t) is the sensor output signal.

[0067] Step 2: Design an augmented structure joint estimator based on the augmented structure-aided estimation system; the expression for the augmented structure joint estimator is as follows:

[0068]

[0069] In the formula, It is an estimate of the state of the augmented structure-aided estimation system. yes The first derivative of E1 is given by E1, where E1 is the auxiliary design matrix, I is the identity matrix, C is the output matrix, N is the sensor fault matrix, A is the system matrix, and B is the input matrix. It is an estimate of the state of the rolling mill thickness control system. This is an estimate of sensor fault, where u(t) is the control signal. This is an estimate of the nonlinearity of the rolling mill thickness control system, where L is the control gain of the joint estimator, and y(t) is the sensor output signal. It is the estimated output of the mill thickness control system.

[0070] Step 3: Initialize the augmented structure joint estimator, setting its control gain and auxiliary design matrix; initialize the thickness controller, setting its control gain; the expression for the thickness controller is as follows:

[0071]

[0072] In the formula, K1 is the estimated state of the mill thickness control system, K1 is the control gain of the thickness controller, and u(t) is the control signal, i.e., the current to be applied to the servo amplifier.

[0073] Repeat steps 4 through 7.

[0074] Step 4: Collect sensor data from the mill thickness control system, including piston displacement measurement, load pressure measurement, and workpiece exit thickness measurement, and transmit them to the augmented structure joint estimator to estimate the state of the mill thickness control system. Because of sensor failure, the measured piston displacement, load pressure, and workpiece exit thickness may not be accurate, so the augmented structure joint estimator needs to reconstruct the system state and sensor failure.

[0075] Step 5: Update the latest estimated status of the mill thickness control system. Input thickness controller;

[0076] Step 6: The thickness controller calculates the current to be applied to the servo amplifier based on the latest estimated state of the mill thickness control system, and uses this as the control signal for the servo amplifier;

[0077] Step 7: Input the control signal into the servo amplifier to control the thickness of the rolled piece at the exit.

[0078] Example 3

[0079] This invention proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the control method of the mill thickness control system based on the augmented structure as described in Embodiment 2.

[0080] Example 4

[0081] The present invention proposes a computer-readable storage medium storing a computer program that causes a computer to execute a control method for a mill thickness control system based on an augmented structure as described in Embodiment 2.

[0082] The effectiveness of this invention will be demonstrated below.

[0083] First, we prove the effectiveness of the augmented structure joint estimator by selecting a composite energy function of the following form:

[0084] V(t) = e x T (t)Pe x (t)

[0085] Among them, e x Let P be the state estimation error. P is the Lyapunov matrix.

[0086] Calculate the derivative of the composite energy function:

[0087]

[0088] Where the operator He(X) = X T +X, and The matrix notation was introduced to simplify the expression.

[0089] Assumption Therefore, the above formula can be further rewritten as:

[0090]

[0091] Where θ1 is a positive constant and τ is a positive constant.

[0092] Therefore, if a suitable gain L is set so that If the condition is met, then the designed augmented structure joint estimator is effective.

[0093] The effectiveness of the thickness controller is demonstrated as follows:

[0094] Choose the following composite energy function:

[0095] V(t) = x T (t)Px(t)

[0096] Calculate the derivative of V:

[0097]

[0098] Substituting the control signal u(t) output by the thickness controller, the above equation can be scaled down to:

[0099]

[0100] Note that ||φ(x,t)||2≤ψ||x(t)||2. Therefore, the above equation can be further rewritten as:

[0101]

[0102] It has already been proven that the estimation error converges. Therefore, if an appropriate gain K1 is set so that... If the conditions are met, then the thickness control system of the rolling mill is asymptotically stable under the thickness controller designed in this invention.

[0103] The relevant parameter values ​​in the embodiments of the present invention are as follows:

[0104] Table 1 Simulation Parameters

[0105] Parameter Value Parameter Value <![CDATA[T H ]]> 0.125 V 6.39×10^-3 W 9.434×10^9 α 8000 <![CDATA[M T ]]> 2.36×10^5 <![CDATA[K C ]]> 7.8×10^-3 <![CDATA[K T ]]> 5.3×10^9 <![CDATA[C T ]]> 2.4×10^-4 <![CDATA[B P ]]> 3.64×10^7 <![CDATA[K Q ]]> 14.15 <![CDATA[A P ]]> 0.41 <![CDATA[K V ]]> 1 <![CDATA[K P ]]> 0.002 ψ 0.02

[0106] The thickness error at the exit of the rolled piece is as follows Figure 2 Load pressure error such as Figure 3 Piston displacement error such as Figure 4 Control signals such as Figure 5 As can be seen from the graph, all errors eventually approach zero.

[0107] In the embodiments disclosed in this application, a computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0108] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0109] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principle of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A mill thickness control system based on an augmented structure, characterized in that, include: Position sensors are used to collect measured values ​​of piston displacement in rolling mill cylinders; Thickness sensor, used to collect the thickness measurement value of the rolled piece at the exit; Hydraulic sensors are used to acquire load pressure measurements. An augmented structure joint estimator is used to estimate the state of the mill thickness control system based on measurements of the mill cylinder piston displacement, the workpiece exit thickness, and the load pressure. The augmented structure joint estimator is designed based on an augmented structure auxiliary estimation system, which is obtained by augmenting sensor faults based on the dynamic model of the mill thickness control system. The expression of the augmented structure joint estimator is as follows: In the formula, It is an estimate of the state of the augmented structure-aided estimation system. yes The first derivative, It is an auxiliary design matrix. I C is the identity matrix, C is the output matrix, and N is the sensor fault matrix. A It is a system matrix. B It is the input matrix. It is an estimate of the state of the rolling mill thickness control system. It is an estimate of sensor malfunction. It is a control signal. It is an estimation of the nonlinearity of the rolling mill thickness control system. It is the control gain of the joint estimator. It is the sensor output signal. It is the estimated output of the mill thickness control system; A thickness controller is used to calculate the current applied to the servo amplifier based on the estimated state of the mill thickness control system, and to serve as the control signal for the servo amplifier. Servo amplifier, used to control the thickness of the rolled product exit.

2. A control method for a mill thickness control system based on an augmented structure, characterized in that, Includes the following steps: Step 1: Based on the dynamic model of the rolling mill thickness control system, augment sensor faults are obtained to obtain an augmented structure-assisted estimation system; Step 2: Design an augmented structure joint estimator based on the augmented structure-aided estimation system; the expression of the augmented structure joint estimator is as follows: In the formula, It is an estimate of the state of the augmented structure-aided estimation system. yes The first derivative, It is an auxiliary design matrix. I C is the identity matrix, C is the output matrix, and N is the sensor fault matrix. A It is a system matrix. B It is the input matrix. It is an estimate of the state of the rolling mill thickness control system. It is an estimate of sensor malfunction. It is a control signal. It is an estimation of the nonlinearity of the rolling mill thickness control system. It is the control gain of the joint estimator. It is the sensor output signal. It is the estimated output of the mill thickness control system; Step 3: Initialize the augmented structure joint estimator, set the control gain and auxiliary design matrix of the joint estimator; initialize the thickness controller, set the control gain of the thickness controller; Repeat steps 4 through 7. Step 4: Collect sensor data from the mill thickness control system, including piston displacement measurement, load pressure measurement, and workpiece exit thickness measurement, and transmit them to the augmented structure joint estimator to estimate the state of the mill thickness control system. Step 5: Input the latest estimated status of the mill thickness control system into the thickness controller; Step 6: The thickness controller calculates the current to be applied to the servo amplifier based on the latest estimated state of the mill thickness control system, and uses this as the control signal for the servo amplifier; Step 7: Input the control signal into the servo amplifier to control the thickness of the rolled piece at the exit.

3. The control method for the mill thickness control system based on the augmented structure as described in claim 2, characterized in that, The dynamic model of the rolling mill thickness control system is as follows: In the formula, It is the state vector of the rolling mill thickness control system. yes The first derivative, This is the actual value of the piston displacement in the rolling mill cylinder. It is the expected value of the piston displacement in the rolling mill cylinder. yes The first derivative, This is the actual value of the rolling mill load pressure. It is the expected load pressure value. This is the actual value of the thickness at the exit of the rolled piece. This is the expected thickness of the rolled piece at the exit. A It is a system matrix. B It is the input matrix. It is a control signal. It is the nonlinear characteristic of the system. This represents the sensor output signal, where C is the output matrix and N is the sensor fault matrix. It's a sensor malfunction. b 1, b 2, b 3, b 4, b 5, b 6, b 7, g These are all symbols designed for the purpose of conveying conciseness. It is the effective mass of the moving parts of the rolling mill roll system. It is the load elastic stiffness coefficient. It is the viscosity coefficient of the moving parts. It is the effective area of ​​the hydraulic cylinder piston. It is the plastic stiffness coefficient of the rolled piece. It is the bulk modulus of elasticity. It is the total volume of the hydraulic cylinder's oil chamber. It is the servo flow amplification factor. It is the leakage coefficient of the hydraulic cylinder. It is the inertial time constant. It is the overall magnification factor. , It is the flow amplification factor. It is the valve core displacement amplification factor. It is the amplification factor of the valve core displacement. It is the first unknown nonlinear term. It is the second unknown nonlinear term. It is the third unknown nonlinear term.

4. The control method for the mill thickness control system based on the augmented structure as described in claim 2, characterized in that, In step 1, the expression for the augmented structure-assisted estimation system is as follows: In the formula, It is the state vector of the rolling mill thickness control system. yes The first derivative, It's a sensor malfunction. yes The first derivative, It is an auxiliary design matrix. I C is the identity matrix, C is the output matrix, and N is the sensor fault matrix. A It is a system matrix. B It is the input matrix. It is a control signal. It is the nonlinear characteristic of the system. It is the sensor output signal.

5. The control method for the mill thickness control system based on the augmented structure as described in claim 2, characterized in that, In step 3, the expression for the thickness controller is as follows: In the formula, It is an estimate of the state of the rolling mill thickness control system. It is the control gain of the thickness controller. It is a control signal, that is, the current that should be applied to the servo amplifier.

6. An electronic device, characterized in that, include: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the control method for a mill thickness control system based on an augmented structure as described in any one of claims 2-5.

7. A computer-readable storage medium storing a computer program, characterized in that, The computer program causes the computer to execute the control method of the mill thickness control system based on the augmented structure as described in any one of claims 2-5.

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