Intelligent control method and system of rolling mill thickness control system based on event triggering, storage medium and equipment

Abstract

The invention discloses an intelligent control method and system of a rolling mill thickness control system based on event triggering, a storage medium and equipment, and the method comprises the steps: based on an expected value of the outlet thickness of an aluminum alloy rolled piece, according to a virtual controller in the rolling mill thickness control system and a virtual control variable required by the controller, combining with a nonlinear dynamic model of the rolling mill thickness control system; calculating a virtual controller signal and a controller signal; the deviation between the controller signal and an original controller signal of the rolling mill thickness control system is calculated, and if the two norm of the deviation is smaller than the dynamic threshold value of the event generator, the rolling mill thickness control system operates according to the original controller signal; otherwise, the calculated controller signal is transmitted to a hydraulic servo valve of the rolling mill thickness control system, and the piston displacement and the load pressure of a hydraulic cylinder in the rolling mill thickness control system and the outlet thickness of the aluminum alloy rolled piece are adjusted by adjusting the hydraulic flow and the pressure. The signal transmission frequency can be reduced through event triggering on the premise of not reducing the performance of the thickness control system of the rolling mill.

Description

Technical Field

[0001] The present invention relates to the technical field of rolling mill thickness control, and in particular to an intelligent control method, system, storage medium and equipment of a rolling mill thickness control system based on event triggering. Background Art

[0002] With the widespread use of aluminum alloy thin strips, the requirements for the precision of aluminum alloy plates and strips are getting higher and higher. Some companies combine modern control theory with rolling mill production in the actual production of aluminum alloy plates and strips, which has led to the rapid development of rolling mill thickness control technology.

[0003] Many enterprises use linear control systems for rolling mill thickness control in actual production. However, the rolling mill will be affected by external interference during operation, and the rollers will have eccentricity, steel biting and steel throwing during operation. These phenomena will increase the difficulty of designing the controller of the rolling mill thickness control system, and even cause the instability of the rolling mill thickness control system. In order to meet the requirements of thickness accuracy of aluminum alloy strip steel, especially some high-precision nano-level aluminum alloy strip steel, the use of nonlinear control systems is more in line with the actual situation. In addition, in order to meet the needs of industrial development and provide strong support for intelligent manufacturing and efficient management, remote control has been widely used in rolling mill thickness control systems in recent years. Remote control can significantly improve the level of automation and thickness accuracy, reduce human errors, realize real-time monitoring and feedback adjustment, realize centralized control and data integration optimization process, thereby improving production efficiency. At the same time, it also reduces safety risks and is conducive to remote diagnosis and maintenance. Therefore, it is of great significance to study the remote intelligent control technology of rolling mill thickness control nonlinear control system.

[0004] The remote intelligent control of existing rolling mill thickness control systems is mostly based on a time-driven periodic sampling communication mode. In this communication mode, the signal communication of each component of the rolling mill thickness control system will generate a large number of redundant signals, which may cause the communication network to be blocked or even paralyzed. In addition, unconditional signal transmission will lead to ineffective use of resources, which is not conducive to improving the overall resource utilization efficiency of the rolling mill thickness control system. Therefore, how to improve the reliability of remote control by reducing the communication frequency while maintaining the stability and efficiency of the rolling mill thickness control system has become the key to realizing the intelligent control of the rolling mill thickness control system. Summary of the invention

[0005] In response to the problems existing in the prior art, the present invention provides an intelligent control method, system, storage medium and equipment for a rolling mill thickness control system based on event triggering. Through event triggering control, the signal transmission frequency can be reduced, the reliability of remote control can be improved, and the use of communication resources can be reduced without reducing the performance of the rolling mill thickness control system.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] An intelligent control method for a rolling mill thickness control system based on event triggering comprises the following steps:

[0008] Step S1, establishing a nonlinear dynamic model of the rolling mill thickness control system according to the rolling mill thickness control system roll system moving component parameters, hydraulic cylinder parameters, valve core parameters and aluminum alloy rolled piece material parameters;

[0009] Step S2, calculating a controller signal according to the expected value of the outlet thickness of the aluminum alloy rolled piece and the virtual control variable of the thickness controller in the thickness control system of the rolling mill, combined with the nonlinear dynamic model of the thickness control system of the rolling mill;

[0010] Step S3, transmitting the calculated controller signal to the event generator, calculating the deviation between the controller signal and the original controller signal of the rolling mill thickness control system, if the second norm of the deviation is less than the dynamic threshold of the event generator, the rolling mill thickness control system operates according to the original controller signal; otherwise, transmitting the calculated controller signal to the hydraulic servo valve of the rolling mill thickness control system, adjusting the piston displacement, load pressure and outlet thickness of the aluminum alloy rolled piece of the hydraulic cylinder in the rolling mill thickness control system by adjusting the hydraulic flow and pressure;

[0011] Step S4, repeat steps S2-S3 until shutdown.

[0012] Furthermore, the establishment process of the nonlinear dynamic model of the rolling mill thickness control system in step S1 is specifically as follows:

[0013]

[0014] Wherein, z1 represents the outlet thickness of aluminum alloy rolled piece, z2 represents the piston displacement of the hydraulic cylinder in the thickness control system of the rolling mill, z3 represents the derivative of z2, z4 represents the load pressure of the thickness control system of the rolling mill, φ1(z2,z3), φ2(z2,z3), φ3(z2,z3) represent the first unknown nonlinear term, the second unknown nonlinear term, and the third unknown nonlinear term, respectively, u represents the controller signal in the thickness control system of the rolling mill, T H represents the inertia time constant, W represents the plastic stiffness coefficient of aluminum alloy rolled piece, M T It represents the effective mass of the roller moving parts in the thickness control system of the rolling mill, K T Indicates the load elastic stiffness coefficient in the rolling mill thickness control system, B P Indicates the viscosity coefficient of the moving parts in the thickness control system of the rolling mill, A P represents the effective area of ​​the hydraulic cylinder piston in the rolling mill thickness control system, V represents the total volume of the hydraulic cylinder oil chamber in the rolling mill thickness control system, α represents the bulk elastic modulus of the hydraulic cylinder oil chamber, and K C represents the servo flow amplification factor, C represents the leakage coefficient of the hydraulic cylinder, K Q Indicates the flow amplification factor, K VIndicates the overall valve core amplification factor, K P Indicates the amplification factor of the valve core displacement.

[0015] Furthermore, step S2 includes the following sub-steps:

[0016] Step S2.1, initialize the thickness controller gain in the rolling mill thickness control system, and set the expected value z of the aluminum alloy rolled piece exit thickness d ;

[0017] Step S2.2, collecting the aluminum alloy rolled piece outlet thickness z1, the hydraulic cylinder piston displacement z2 and the rolling mill load pressure z4 of the rolling mill thickness control system and transmitting them to a remote thickness controller;

[0018] Step S2.3: Based on the expected value z of the aluminum alloy rolled piece exit thickness d , determine the virtual control variables required for the thickness controller The thickness controller includes three virtual controllers and one controller, v1, v2 and v3 represent the first virtual controller signal, the second virtual controller signal and the third virtual controller signal respectively, and q1, q2, q3 and q4 represent the first virtual control variable, the second virtual control variable, the third virtual control variable and the fourth virtual control variable respectively;

[0019] Step S2.4, combine the first virtual control variable, the second virtual control variable, the third virtual control variable, and the fourth virtual control variable with the nonlinear dynamic model of the rolling mill thickness control system to calculate the first virtual controller signal v1, the second virtual controller signal v2, the third virtual controller signal v3 and the controller signal u.

[0020] Furthermore, in step S2.4, the calculation process of the first virtual controller signal v1, the second virtual controller signal v2, the third virtual controller signal v3 and the controller signal u is:

[0021]

[0022] Among them, S1 represents the first activation function, represents the estimated value of the weight W1 of S1, represents the estimated value of the bias η1 of S1, φ1(z2,z3)=W1 T S1+η1; S2 represents the second activation function, represents the estimated value of the weight W2 of S2, represents the estimated value of the bias η2 of S2, S3 represents the third activation function, represents the estimated value of the weight W3 of S3, represents the estimated value of the bias η3 of S3, S4 represents the fourth activation function, represents the estimated value of the weight W4 of S4, represents the estimated value of the bias η4 of S4, K1 represents the first virtual controller gain, K2 represents the second virtual controller gain, K3 represents the third virtual controller gain, and K4 represents the controller gain; τ represents a positive constant, Represents the upper threshold of the event generator.

[0023] Furthermore, the dynamic threshold value calculation process of the event generator in step S3 is as follows: the dynamic threshold value θ of the event generator is determined according to the deviation between the calculated controller signal and the original controller signal of the rolling mill thickness control system:

[0024]

[0025] in, represents the upper limit of the threshold of the event generator, θ represents the lower limit of the threshold of the event generator, ω represents the normal constant, e u Indicates the deviation between the calculated controller signal and the original controller signal of the rolling mill thickness control system.

[0026] Furthermore, the present invention also provides an intelligent control system for a rolling mill thickness control system based on event triggering, comprising: a rolling mill thickness control system, a sensor module, a thickness controller, an event generator and an actuator;

[0027] The sensor module transmits the collected aluminum alloy rolled piece outlet thickness, hydraulic cylinder piston displacement and rolling mill load pressure of the rolling mill thickness control system to the thickness controller;

[0028] The thickness controller calculates a controller signal by combining the collected aluminum alloy rolled piece outlet thickness, the piston displacement of the hydraulic cylinder and the rolling mill load pressure of the rolling mill thickness control system with the nonlinear dynamics model of the rolling mill thickness control system, and transmits the controller signal to the event generator;

[0029] The event generator receives the controller signal, calculates the deviation between the controller signal and the original controller signal of the rolling mill thickness control system, determines the dynamic threshold of the event generator, and compares the binary norm of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system with the dynamic threshold of the event generator;

[0030] The actuator drives the operation of the rolling mill thickness control system according to the comparison result.

[0031] Furthermore, if the binary norm of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system is less than the dynamic threshold of the event generator, the actuator drives the operation of the rolling mill thickness control system according to the original controller signal; otherwise, the actuator adjusts the hydraulic flow and pressure of the hydraulic servo valve of the rolling mill thickness control system according to the calculated actuator signal, and adjusts the piston displacement, load pressure and outlet thickness of the hydraulic cylinder in the rolling mill thickness control system.

[0032] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the intelligent control method of a rolling mill thickness control system based on event triggering.

[0033] Furthermore, the present invention also provides an electronic device, characterized in that it includes: 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, the intelligent control method of the rolling mill thickness control system based on event triggering is implemented.

[0034] Compared with the prior art, the present invention has the following beneficial effects: the intelligent control method and system of the rolling mill thickness control system based on event triggering of the present invention determines the controller signal based on the nonlinear dynamic model of the rolling mill thickness control system, realizes adaptive aluminum alloy rolled piece exit thickness tracking, and constructs the event-triggered dynamic threshold based on the controller signal. By calculating the bi-norm of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system and comparing it with the dynamic threshold, it is determined whether the current controller signal needs to be transmitted. There is no need to frequently adjust the control signal of the rolling mill thickness control system, which reduces the mechanical wear of the rolling mill thickness control system and improves the resource utilization efficiency of the rolling mill thickness control system. Compared with the existing static event triggering scheme, it can further reduce the transmission frequency of the signal, improve the reliability of remote control, and reduce the communication burden. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of an intelligent control system of a rolling mill thickness control system based on event triggering of the present invention;

[0036] Figure 2 A schematic diagram of controller signals of an intelligent control method for a rolling mill thickness control system based on event triggering according to the present invention;

[0037] Figure 3 A schematic diagram of piston displacement of a hydraulic cylinder of a rolling mill thickness control system using the intelligent control method of the rolling mill thickness control system based on event triggering of the present invention;

[0038] Figure 4 A schematic diagram of the rolling mill load pressure of a rolling mill thickness control system using the intelligent control method of the rolling mill thickness control system based on event triggering of the present invention;

[0039] Figure 5 The figure is a schematic diagram for comparing the actual value and expected value of the exit thickness of an aluminum alloy rolled piece using the intelligent control method of a rolling mill thickness control system based on event triggering of the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is further explained below in conjunction with the accompanying drawings.

[0041] like Figure 1 The present invention is a schematic diagram of an intelligent control system of a rolling mill thickness control system based on event triggering, and the intelligent control system includes: a rolling mill thickness control system, a sensor module, a thickness controller, an event generator and an actuator; the sensor module transmits the collected aluminum alloy rolled piece outlet thickness of the rolling mill thickness control system, the piston displacement of the hydraulic cylinder and the rolling mill load pressure to the remote thickness controller through the communication module; the thickness controller combines the collected aluminum alloy rolled piece outlet thickness of the rolling mill thickness control system, the piston displacement of the hydraulic cylinder and the rolling mill load pressure with the nonlinear dynamic model of the rolling mill thickness control system to calculate the controller signal, and transmits the controller signal to the event generator; the event generator receives the controller signal, calculates the controller signal and the original controller signal of the rolling mill thickness control system Deviation, determine the dynamic threshold of the event generator, and compare the two norms of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system with the dynamic threshold of the event generator, and transmit the comparison result to the actuator through the communication module; the actuator drives the operation of the rolling mill thickness control system according to the comparison result, specifically, if the two norms of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system are less than the dynamic threshold of the event generator, the actuator drives the operation of the rolling mill thickness control system according to the original controller signal; otherwise, the actuator adjusts the hydraulic flow and pressure of the hydraulic servo valve of the rolling mill thickness control system according to the calculated actuator signal, and adjusts the piston displacement, load pressure and outlet thickness of the hydraulic cylinder in the rolling mill thickness control system. The present invention determines whether the current controller signal needs to be transmitted by calculating the two norms of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system and comparing them with the dynamic threshold, without frequently adjusting the control signal of the rolling mill thickness control system, reducing the mechanical wear of the rolling mill thickness control system, and improving the resource utilization efficiency of the rolling mill thickness control system. Compared with the existing static event triggering scheme, it can further reduce the transmission frequency of the signal, improve the reliability of remote control, and reduce the communication burden.

[0042] In a technical solution of the present invention, an intelligent control method of a rolling mill thickness control system based on event triggering is also provided, comprising the following steps:

[0043] Step S1: Establish a nonlinear dynamic model of the thickness control system of the rolling mill according to the parameters of the rolling mill moving parts, the hydraulic cylinder parameters, the valve core parameters and the material parameters of the aluminum alloy rolled product. The parameters of the rolling mill moving parts include: the effective mass M of the rolling mill moving parts; T , load elastic stiffness coefficient K T , Viscosity coefficient B of roller moving parts P , hydraulic cylinder parameters include: effective area A of hydraulic cylinder piston P , the total volume V of the hydraulic cylinder oil chamber, the bulk elastic modulus α of the hydraulic cylinder oil chamber, the leakage coefficient C of the hydraulic cylinder, the servo flow amplification coefficient K of the hydraulic cylinder C , the flow magnification factor K of the hydraulic cylinder Q , valve core parameters include: valve core overall magnification factor K V , valve core displacement amplification factor K P , the material parameters of aluminum alloy rolled pieces include: the plastic stiffness coefficient W of aluminum alloy rolled pieces, so as to establish the nonlinear dynamic model of the rolling mill thickness control system:

[0044]

[0045] Wherein, z1 represents the outlet thickness of aluminum alloy rolled piece, z2 represents the piston displacement of the hydraulic cylinder in the thickness control system of the rolling mill, z3 represents the derivative of z2, z4 represents the load pressure of the thickness control system of the rolling mill, φ1(z2,z3), φ2(z2,z3), φ3(z2,z3) represent the first unknown nonlinear term, the second unknown nonlinear term, and the third unknown nonlinear term, respectively, u represents the controller signal in the thickness control system of the rolling mill, T H represents the inertia time constant.

[0046] Step S2, according to the expected value of the aluminum alloy rolled piece outlet thickness and the virtual control variable of the thickness controller in the rolling mill thickness control system, combined with the nonlinear dynamic model of the rolling mill thickness control system, the controller signal is calculated to achieve adaptive aluminum alloy rolled piece outlet thickness tracking, specifically including the following sub-steps:

[0047] Step S2.1, initialize the thickness controller gain in the rolling mill thickness control system, and set the expected value z of the aluminum alloy rolled piece exit thickness d ;

[0048] Step S2.2, collecting the aluminum alloy rolled piece outlet thickness z1, the hydraulic cylinder piston displacement z2 and the rolling mill load pressure z4 of the rolling mill thickness control system and transmitting them to the remote thickness controller through the communication module;

[0049] Step S2.3: Based on the expected value z of the aluminum alloy rolled piece exit thickness d , determine the virtual control variables required for the thickness controller The thickness controller includes three virtual controllers and one controller, v1, v2 and v3 represent the first virtual controller signal, the second virtual controller signal and the third virtual controller signal respectively, and q1, q2, q3 and q4 represent the first virtual control variable, the second virtual control variable, the third virtual control variable and the fourth virtual control variable respectively;

[0050] Step S2.4, the first virtual control variable, the second virtual control variable, the third virtual control variable, and the fourth virtual control variable are respectively combined with the nonlinear dynamic model of the rolling mill thickness control system to calculate the first virtual controller signal v1, the second virtual controller signal v2, the third virtual controller signal v3 and the controller signal u:

[0051] i. The nonlinear dynamic model of the rolling mill thickness control system And the first virtual control variable q1 = z1-z d We can get:

[0052]

[0053] According to the second virtual control variable q2=z2-v1, equation (1) is equivalent to:

[0054]

[0055] Among them, φ1(z2,z3) can be approximated by formula (3):

[0056] φ1(z2,z3)=W1 T S1+η1 (3)

[0057] Among them, S1 represents the first activation function, W1 represents the weight of S1, η1 represents the bias of S1, represents the estimation error of W1, represents the estimated value of W1, represents the estimation error of η1, represents the estimated value of η1, based on which, formula (2) can be rewritten as:

[0058]

[0059] According to formula (4), the first virtual controller signal v1 is obtained as follows:

[0060]

[0061] Wherein, K1 represents the first virtual controller gain, and K1>0.

[0062] Substituting the first virtual controller signal into equation (4), we get:

[0063]

[0064] According to Lyapunov theory, the composite energy function V1 of formula (7) is selected:

[0065]

[0066] Combine (6) to calculate the derivative of V1: Constructing the first estimation law We can get: Among them, Γ1 and γ1 are both positive constants.

[0067] According to Lyapunov theory, if K1>0, then This shows that the rolling mill thickness control system is asymptotically stable, thus proving that the first virtual controller signal v1 designed by the present invention can make the nonlinear dynamic model of the rolling mill thickness control system Stablize.

[0068] ii. The nonlinear dynamic model of the rolling mill thickness control system And the second virtual control variable q2=z2-v1 can be obtained:

[0069]

[0070] According to the third virtual control variable q3=z3-v2, equation (8) is equivalent to:

[0071]

[0072] in, It can be approximated by formula (10):

[0073]

[0074] Among them, S2 represents the second activation function, W2 represents the weight of S2, η2 represents the bias of S2, represents the estimation error of W2, represents the estimated value of W2, represents the estimation error of η2, represents the estimated value of η2. Based on this, equation (9) can be rewritten as:

[0075]

[0076] According to formula (11), the second virtual controller signal v2 is obtained:

[0077]

[0078] Wherein, K2 represents the second virtual controller gain, and K2>0.

[0079] Substituting the second virtual controller of equation (12) into equation (11), we can obtain:

[0080]

[0081] According to Lyapunov theory, the composite energy function is selected in the following form:

[0082]

[0083] Combined with (13), we can calculate the derivative of V2: Constructing the Second Estimation Law Available Among them, Γ2 and γ2 are both positive constants.

[0084] According to Lyapunov theory, if K2>0, then This shows that the rolling mill thickness control system is asymptotically stable, thus proving that the second virtual controller signal v2 designed by the present invention can make the nonlinear dynamic model of the rolling mill thickness control system Stablize.

[0085] iii. The nonlinear dynamic model of the rolling mill thickness control system And the third virtual control variable q3 = z3-v2 can be obtained:

[0086]

[0087] According to the fourth virtual control variable q4=z4-v3, equation (14) is equivalent to:

[0088]

[0089] in, Approximation (16):

[0090]

[0091] Among them, S3 represents the third activation function, W3 represents the weight of S3, η3 represents the bias of S3, represents the estimated error of W3, represents the estimated value of W3, represents the estimation error of η3, represents the estimated value of η3, based on which, equation (15) can be rewritten as:

[0092]

[0093] According to formula (17), the third virtual controller signal v3 is obtained:

[0094]

[0095] Substituting the third virtual controller into equation (17), we obtain:

[0096]

[0097] Wherein, K3 represents the third virtual controller gain, and K3>0.

[0098] According to Lyapunov theory, the composite energy function is selected in the following form:

[0099]

[0100] Combined with formula (19), the derivative of V3 is calculated as: Constructing the third estimation law Available Among them, Γ3 and γ3 are both positive constants.

[0101] According to Lyapunov theory, if K3>0, then This shows that the rolling mill thickness control system is asymptotically stable, thus proving that the third virtual controller signal v3 designed by the present invention can make the nonlinear dynamic model of the rolling mill thickness control system Stablize.

[0102] iv. The nonlinear dynamic model of the rolling mill thickness control system And the fourth virtual control variable q4=z4-v3 can be obtained:

[0103]

[0104] in, Approximation (21):

[0105]

[0106] Among them, S4 represents the fourth activation function, W4 represents the weight of S4, η4 represents the bias of S4, represents the estimated error of W4, represents the estimated value of W4, represents the estimation error of η4, represents the estimated value of η4. Based on this, equation (20) can be rewritten as:

[0107]

[0108] According to formula (22), the controller signal u is obtained:

[0109]

[0110] Where K4 represents the controller gain, K4>0; therefore, Expressed by formula (24):

[0111]

[0112] According to formula (24), the event-triggered controller signal u is obtained:

[0113]

[0114] Among them, τ represents a positive constant, Represents the upper threshold of the event generator.

[0115] Step S3, transmitting the calculated controller signal to the event generator, calculating the deviation between the controller signal and the original controller signal of the rolling mill thickness control system, if the second norm of the deviation is less than the dynamic threshold of the event generator, the rolling mill thickness control system operates according to the original controller signal; otherwise, transmitting the calculated controller signal to the hydraulic servo valve of the rolling mill thickness control system, and adjusting the piston displacement, load pressure and outlet thickness of the aluminum alloy rolled piece of the hydraulic cylinder in the rolling mill thickness control system by adjusting the hydraulic flow and pressure; through the above-mentioned event triggering method, there is no need to frequently adjust the control signal of the rolling mill thickness control system, reduce the mechanical wear of the rolling mill thickness control system, improve the resource utilization efficiency of the rolling mill thickness control system, can further reduce the transmission frequency of the signal, improve the reliability of remote control, and reduce the communication burden.

[0116] The dynamic threshold calculation process of the event generator in the present invention is: the dynamic threshold θ of the event generator is determined according to the deviation between the calculated controller signal and the original controller signal of the rolling mill thickness control system:

[0117]

[0118] in, Indicates the upper threshold of the event generator. θ represents the lower limit of the threshold of the event generator, ω represents the normal constant, e u Indicates the deviation between the calculated controller signal and the original controller signal of the rolling mill thickness control system.

[0119] Substituting the event-triggered controller signal u into equation (24), we obtain:

[0120]

[0121] According to Lyapunov theory, the composite energy function is selected in the following form:

[0122]

[0123] Combining (25) with the event trigger mechanism, the derivative of V4 is calculated:

[0124]

[0125] Constructing the fourth estimation law Among them, Γ4 and γ4 are both positive integers. Since ||e u When ||2≥θ, the calculated controller signal is transmitted to the rolling mill thickness control system, so ||e u ||2 is always smaller than the upper bound of the dynamic threshold θ Based on this, the above formula can be expanded to: According to the properties of the hyperbolic tangent function tanh: for any constant δ, According to this property, the above formula can be expanded to: According to Lyapunov theory, if K4>0, then It is shown that the rolling mill thickness control system is bounded and stable under the event-triggered intelligent control method of the present invention.

[0126] Step S4, repeat steps S2-S3 until shutdown.

[0127] Table 1 shows the parameters of the rolling mill thickness control system in one embodiment of the present invention. The nonlinear dynamic model of the rolling mill thickness control system is constructed according to these parameters, and the operation of the rolling mill thickness control system is driven according to the intelligent control method of the rolling mill thickness control system based on event triggering of the present invention. Figure 2 This is a schematic diagram of the controller signal driving the rolling mill thickness control system. Figure 2 From the enlarged diagram in the figure, we can see that the controller signal is not transmitted continuously, but is transmitted to the rolling mill thickness control system after being verified by the event trigger mechanism; Figure 3 and Figure 4 They are schematic diagrams of the piston displacement of the hydraulic cylinder of the rolling mill thickness control system driven by the corresponding controller signal and the rolling mill load pressure. It can be seen that the piston displacement of the hydraulic cylinder of the rolling mill thickness control system and the rolling mill load pressure follow the signal changes in the rolling mill thickness control system, thereby adjusting the rolling mill outlet thickness. The signal changes in the rolling mill thickness control system are caused by the controller signal after the event trigger mechanism is verified; Figure 5 The schematic diagram of the comparison between the actual value and the expected value of the thickness of the aluminum alloy rolled piece at the exit of the intelligent control method of the rolling mill thickness control system based on event triggering of the present invention is shown. It can be seen that the actual value and the expected value of the thickness of the aluminum alloy rolled piece at the exit are basically consistent, indicating that the intelligent control method of the present invention can successfully achieve the control of the thickness of the aluminum alloy rolled piece. At the same time, the present invention can reduce the transmission frequency of the controller signal, improve the reliability of remote control, and reduce the occupancy of the network bandwidth. In addition, the intelligent control method of the rolling mill thickness control system based on event triggering of the present invention is also suitable for the thickness control of other plates in the manufacturing process except aluminum alloy plates, such as magnesium materials, copper materials, etc.

[0128] Table 1: Parameters of rolling mill thickness control system

[0129] Parameters | value parameter value <![CDATA[T H (s)]]> 0.125 <![CDATA[V(n 3 )]]> 6.39×10^-3 W(N / s) 9.434×10^9 α(MPa) 800 <![CDATA[M T (kg)]]> 2.36×10^5 <![CDATA[K C (pu)]]> 7.8×10^-8 <![CDATA[K T (N / m)]]> 5.3×10^9 <![CDATA[C(n 3 / (Pa·s))]]> 2.4×10^-12 <![CDATA[B P (N / m)]]> 3.64×10^7 <![CDATA[K Q (pu)]]> 14.15 <![CDATA[A P (m 2 )]]> 0.41 <![CDATA[K V (pu)]]> 1 <![CDATA[K P (pu)]]> 0.002

[0130] In a technical solution of the present invention, a computer-readable storage medium is also provided, storing a computer program, wherein the computer program enables a computer to execute the intelligent control method of the rolling mill thickness control system based on event triggering.

[0131] In a technical solution of the present invention, an electronic device is also provided, 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, the intelligent control method of the rolling mill thickness control system based on event triggering is implemented.

[0132] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0133] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0134] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. An intelligent control method for a rolling mill thickness control system based on event triggering, characterized in that: The steps include: Step S1, establishing a nonlinear dynamic model of the rolling mill thickness control system according to the rolling mill thickness control system roll system moving component parameters, hydraulic cylinder parameters, valve core parameters and aluminum alloy rolled piece material parameters; Step S2, calculating a controller signal according to the expected value of the outlet thickness of the aluminum alloy rolled piece and the virtual control variable of the thickness controller in the thickness control system of the rolling mill, combined with the nonlinear dynamic model of the thickness control system of the rolling mill; Step S3, transmitting the calculated controller signal to the event generator, calculating the deviation between the controller signal and the original controller signal of the rolling mill thickness control system, if the second norm of the deviation is less than the dynamic threshold of the event generator, the rolling mill thickness control system operates according to the original controller signal; otherwise, transmitting the calculated controller signal to the hydraulic servo valve of the rolling mill thickness control system, adjusting the piston displacement, load pressure and outlet thickness of the aluminum alloy rolled piece of the hydraulic cylinder in the rolling mill thickness control system by adjusting the hydraulic flow and pressure; Step S4, repeat steps S2-S3 until shutdown.

2. The intelligent control method of a rolling mill thickness control system based on event triggering according to claim 1 is characterized in that: The process of establishing the nonlinear dynamic model of the rolling mill thickness control system in step S1 is specifically as follows: Wherein, z1 represents the outlet thickness of aluminum alloy rolled piece, z2 represents the piston displacement of the hydraulic cylinder in the thickness control system of the rolling mill, z3 represents the derivative of z2, z4 represents the load pressure of the thickness control system of the rolling mill, φ1(z2,z3), φ2(z2,z3), φ3(z2,z3) represent the first unknown nonlinear term, the second unknown nonlinear term, and the third unknown nonlinear term, respectively, u represents the controller signal in the thickness control system of the rolling mill, T H represents the inertia time constant, W represents the plastic stiffness coefficient of aluminum alloy rolled piece, M T It represents the effective mass of the roller moving parts in the thickness control system of the rolling mill, K T Indicates the load elastic stiffness coefficient in the rolling mill thickness control system, B P Indicates the viscosity coefficient of the moving parts in the thickness control system of the rolling mill, A P represents the effective area of ​​the hydraulic cylinder piston in the rolling mill thickness control system, V represents the total volume of the hydraulic cylinder oil chamber in the rolling mill thickness control system, α represents the bulk elastic modulus of the hydraulic cylinder oil chamber, and K C represents the servo flow amplification factor, C represents the leakage coefficient of the hydraulic cylinder, K Q Indicates the flow amplification factor, K V Indicates the overall valve core amplification factor, K P Indicates the amplification factor of the valve core displacement.

3. The intelligent control method of a rolling mill thickness control system based on event triggering according to claim 2 is characterized in that: Step S2 includes the following sub-steps: Step S2.1, initialize the thickness controller gain in the rolling mill thickness control system, and set the expected value z of the aluminum alloy rolled piece exit thickness d ; Step S2.2, collecting the aluminum alloy rolled piece outlet thickness z1, the hydraulic cylinder piston displacement z2 and the rolling mill load pressure z4 of the rolling mill thickness control system and transmitting them to a remote thickness controller; Step S2.3: Based on the expected value z of the aluminum alloy rolled piece exit thickness d , determine the virtual control variables required for the thickness controller The thickness controller includes three virtual controllers and one controller, v1, v2 and v3 represent the first virtual controller signal, the second virtual controller signal and the third virtual controller signal respectively, and q1, q2, q3 and q4 represent the first virtual control variable, the second virtual control variable, the third virtual control variable and the fourth virtual control variable respectively; Step S2.4, combine the first virtual control variable, the second virtual control variable, the third virtual control variable, and the fourth virtual control variable with the nonlinear dynamic model of the rolling mill thickness control system to calculate the first virtual controller signal v1, the second virtual controller signal v2, the third virtual controller signal v3 and the controller signal u.

4. The intelligent control method of a rolling mill thickness control system based on event triggering according to claim 3 is characterized in that: The calculation process of the first virtual controller signal v1, the second virtual controller signal v2, the third virtual controller signal v3 and the controller signal u in step S2.4 is: Among them, S1 represents the first activation function, represents the estimated value of the weight W1 of S1, represents the estimated value of the bias η1 of S1, φ1(z2,z3)=W1 T S1+η1; S2 represents the second activation function, represents the estimated value of the weight W2 of S2, represents the estimated value of the bias η2 of S2, S3 represents the third activation function, represents the estimated value of the weight W3 of S3, represents the estimated value of the bias η3 of S3, S4 represents the fourth activation function, represents the estimated value of the weight W4 of S4, represents the estimated value of the bias η4 of S4, K1 represents the first virtual controller gain, K2 represents the second virtual controller gain, K3 represents the third virtual controller gain, and K4 represents the controller gain; τ represents a positive constant, Represents the upper threshold of the event generator.

5. The intelligent control method of a rolling mill thickness control system based on event triggering according to claim 4 is characterized in that: The dynamic threshold calculation process of the event generator in step S3 is: determine the dynamic threshold θ of the event generator according to the deviation between the calculated controller signal and the original controller signal of the rolling mill thickness control system: in, represents the upper limit of the threshold of the event generator, θ represents the lower limit of the threshold of the event generator, ω represents the normal constant, e u Indicates the deviation between the calculated controller signal and the original controller signal of the rolling mill thickness control system.

6. An intelligent control system for a rolling mill thickness control system based on event triggering, characterized in that: include: Rolling mill thickness control system, sensor module, thickness controller, event generator and actuator; The sensor module transmits the collected aluminum alloy rolled piece outlet thickness, hydraulic cylinder piston displacement and rolling mill load pressure of the rolling mill thickness control system to the thickness controller; The thickness controller calculates a controller signal by combining the collected aluminum alloy rolled piece outlet thickness, the piston displacement of the hydraulic cylinder and the rolling mill load pressure of the rolling mill thickness control system with the nonlinear dynamics model of the rolling mill thickness control system, and transmits the controller signal to the event generator; The event generator receives the controller signal, calculates the deviation between the controller signal and the original controller signal of the rolling mill thickness control system, determines the dynamic threshold of the event generator, and compares the binary norm of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system with the dynamic threshold of the event generator; The actuator drives the operation of the rolling mill thickness control system according to the comparison result.

7. The intelligent control system of the rolling mill thickness control system based on event triggering according to claim 6 is characterized in that: If the binary norm of the deviation between the controller signal and the original controller signal of the rolling mill thickness control system is less than the dynamic threshold of the event generator, the actuator drives the operation of the rolling mill thickness control system according to the original controller signal; otherwise, the actuator adjusts the hydraulic flow and pressure of the hydraulic servo valve of the rolling mill thickness control system according to the calculated actuator signal, and adjusts the piston displacement, load pressure and exit thickness of the aluminum alloy rolled piece of the hydraulic cylinder in the rolling mill thickness control system.

8. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the intelligent control method of the rolling mill thickness control system based on event triggering as described in any one of claims 1-5.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the intelligent control method of the rolling mill thickness control system based on event triggering as described in any one of claims 1 to 5 is implemented.

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