Multi-device collaborative control method, device, terminal device and computer storage medium

Abstract

The present application relates to the technical field of automated equipment, and particularly to a multi-device collaborative control method, device, terminal device, and computer storage medium. The method includes: obtaining target status data sent by adjacent devices at a target moment based on a preset multi-device collaborative control model, where the adjacent devices refer to the leading device or other follower devices; determining the current moment when the target status data is received, and reading the current status data of the target follower device at the current moment; calculating the target moment, the current moment, the target status data, and the current status data according to a preset consistency control protocol algorithm to obtain the control gain of the target follower device relative to the leading device; superimposing the control gain on the current status data to perform collaborative control on the target follower device in synchronization with the leading device. The present application improves the consistency of multi-device collaborative movement.

Description

Technical Field

[0001] The present application relates to the technical field of automation equipment, and particularly to a multi-device collaborative control method, device, terminal device, and computer storage medium. Background Art

[0002] Distributed collaborative control relies on information interaction between multiple motion devices. In actual engineering, the information of multiple motion devices is often connected through a limited link or a wireless network. Therefore, multiple devices form an information exchange network. By using the information sensed by sensors and the information transmitted by other devices in the information network, multiple motion devices finally achieve an orderly collaborative motion state.

[0003] In existing multi-device control systems, the more common control strategies are mostly centralized control strategies. Such centralized control strategies have great defects. On the one hand, by regarding multiple motion devices as a whole through this centralized control strategy, the obtained mathematical model is relatively complex, which leads to complex computational complexity and requires a centralized computing device with powerful computing capabilities. On the other hand, there is also a phenomenon of poor consistency in the collaborative motion of multiple motion devices through the centralized control strategy.

[0004] In summary, while reducing the computational complexity of the multi-device control system, how to improve the consistency of the collaborative motion of multiple motion devices is a technical problem that urgently needs to be solved at present. Summary of the Invention

[0005] The main purpose of the present application is to provide a multi-device collaborative control method, device, terminal device, and computer storage medium, aiming to improve the consistency of multi-device collaborative motion.

[0006] To achieve the above object, the present application provides a multi-device collaborative control method. The multi-device collaborative control method is applied to a target following device in a multi-device collaborative control system. The multi-device collaborative control system further includes: a leader device and other following devices. Among them, a communication connection is established between the target following device and the leader device, or the target following device establishes a communication connection with the leader device through the other following devices;

[0007] The multi-device collaborative control method includes:

[0008] Obtaining target state data sent by an adjacent device at a target moment based on a preset multi-device collaborative control model, where the adjacent device is a leader device or other following devices;

[0009] Determining the current moment when the target state data is received, and reading the current state data of the target following device at the current moment;

[0010] Calculate the control gain of the target following device relative to the leader device by using a preset consistency control protocol algorithm on the target time, the current time, the target state data, and the current state data;

[0011] Superimpose the control gain on the current state data, and perform collaborative control on the target following device in synchronization with the leader device.

[0012] Optionally, a state buffer is provided inside the target following device. The step of calculating the control gain of the target following device relative to the leader device by using a preset consistency control protocol algorithm on the target time, the current time, the target state data, and the current state data includes:

[0013] Obtain the buffered state data of the target following device at the target time through the state buffer, and determine the delay time when the buffered state data is received;

[0014] Calculate the current state weighted term of the target following device by using the consistency control protocol algorithm on the current state data, the target state data, and the buffered state data at the node of the current time;

[0015] Obtain the past time node of the target following device according to the first difference between the current time and the target time, and calculate the past state weighted term of the target following device by using the consistency control protocol algorithm on the current state data, the target state data, and the buffered state data at the past time node;

[0016] Obtain the delay time node of the target following device according to the second difference between the first difference and the delay time, and calculate the delay state weighted term of the target following device by using the consistency control protocol algorithm on the current state data, the target state data, and the buffered state data at the delay time node;

[0017] Calculate the control gain of the target following device relative to the leader device according to the current state weighted term, the past state weighted term, and the delay state weighted term.

[0018] Optionally, the step of calculating the control gain of the target following device relative to the leader device according to the current state weighted term, the past state weighted term, and the delay state weighted term includes:

[0019] Determine the adjacency matrix coefficients of the multi-device collaborative control system according to a preset topological graph, and obtain the adjacency coefficient between the target following device and the leader device;

[0020] In the multi-device collaborative control model, determine the input matrix of the target following device according to the adjacency matrix coefficients and the adjacency coefficient;

[0021] Calculate according to the adjacency matrix coefficients, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leader device.

[0022] Optionally, the step of calculating according to the adjacency matrix coefficients, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leader device includes:

[0023] Calculate according to a preset gain calculation formula for the adjacency matrix coefficients, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leader device, where the gain calculation formula is:

[0024]

[0025] Among them, the u i (t) refers to the input matrix, α, β, χ are preset weighting coefficients, x i (t)-x j (t) and x i (t)-x0(t) refer to the current state weighting term, x i (t-d)-x j (t-d) and x i (t-d)-x0(t-d) refer to the past state weighting term, x i (t-d-τ)-x j (t-d-τ) and x i (t-d-τ)-x0(t-d-τ) refer to the time-delay state weighting term, a ij (κ(t)) refers to the adjacency matrix coefficient, b i (κ(t)) is the adjacency coefficient, and K(κ(t)) refers to the control gain of the target following device relative to the leader device.

[0026] Optionally, the multi-device collaborative control system further includes: a mover guide rail, and the target following device is connected to the gear part of the mover guide rail. The method further includes:

[0027] Obtain the position angle of the target following device relative to the mover guide rail, and read the phase current input into the target following device;

[0028] Determine the phase inductance of the target following device according to the position angle and the phase current;

[0029] Construct the multi-device collaborative control model according to the phase inductance and the position angle.

[0030] Optionally, the step of determining the phase inductance of the target following device according to the position angle and the phase current includes:

[0031] Judge whether the position angle belongs to a preset first threshold interval;

[0032] When it is determined that the position angle belongs to the first threshold interval, obtain the first inductance calculation function corresponding to the first threshold interval;

[0033] Calculate the position angle and the phase current according to the first inductance calculation function to obtain the phase inductance of the target following device.

[0034] Optionally, after the step of judging whether the position angle belongs to a preset first threshold interval, the method includes:

[0035] When it is determined that the position angle does not belong to the first threshold interval, detect whether the position angle belongs to a preset second threshold interval, where the first threshold interval is smaller than the second threshold interval;

[0036] After it is determined that the position angle belongs to the second threshold interval, obtain the second inductance calculation function corresponding to the second threshold interval, and calculate the position angle and the phase current according to the second inductance calculation function to obtain the phase inductance of the target following device;

[0037] After it is determined that the position angle does not belong to the second threshold interval, it is determined that the position angle is in a preset third threshold interval, and the position angle and the phase current are calculated according to the third inductance calculation function corresponding to the third threshold interval to obtain the phase inductance of the target following device, where the third threshold interval is larger than the second threshold interval.

[0038] In addition, to achieve the above object, the present application further provides a multi-device collaborative control device. The multi-device collaborative control device of the present application includes:

[0039] An acquisition module, configured to acquire target status data sent by an adjacent device at a target moment based on a preset multi-device collaborative control model, where the adjacent device is the leading device or the other follower devices;

[0040] A reading module, configured to determine a current moment when the target status data is received, and read current status data of the target follower device at the current moment;

[0041] A calculation module, configured to calculate the target moment, the current moment, the target status data, and the current status data according to a preset consistency control protocol algorithm to obtain a control gain of the target follower device relative to the leading device;

[0042] An overlay module, configured to overlay the control gain on second status data to perform collaborative control on the target follower device in synchronization with the leading device.

[0043] Each functional module of the multi-device collaborative control device of the present application implements the steps of the multi-device collaborative control method of the present application as described above when running.

[0044] In addition, to achieve the above object, the present application further provides a terminal device, where the terminal device includes a memory, a processor, and a multi-device collaborative control program stored on the memory and executable on the processor. When the multi-device collaborative control program is executed by the processor, the steps of the above multi-device collaborative control method are implemented.

[0045] In addition, to achieve the above object, the present application further provides a computer storage medium, where a multi-device collaborative control program is stored on the computer storage medium. When the multi-device collaborative control program is executed by a processor, the steps of the above multi-device collaborative control method are implemented.

[0046] In this application, the multi-device collaborative control method is applied to the target following device in a multi-device collaborative control system. The multi-device collaborative control system further includes: a leader device and other following devices. Among them, a communication connection is established between the target following device and the leader device, and the target following device is connected to the leader device through other following devices. The target following device first obtains the target state data sent by the adjacent device at the target moment based on a preset multi-device collaborative control model. Here, the adjacent device refers to the leader device connected to the target following device or other following devices connected to the target following device. Then, it determines the current moment when the target state data is received and reads the current state data of the target following device at the current moment. Next, it calculates the target moment, the current moment, the target state data, and the current state data according to a preset consensus control protocol algorithm to obtain the control gain of the target following device relative to the leader device. Finally, it superimposes the control gain on the current state data to perform collaborative control on the target following device synchronously with the leader device.

[0047] Different from the traditional multi-device collaborative control method, this application designs a multi-device collaborative control model. The target following device can obtain the target state data sent by the adjacent device at the target moment based on this multi-device collaborative control model, thus effectively liberating the multi-device collaborative control system from the need for high-performance centralized computing units. In other words, the complex centralized information processing and calculation in the existing centralized control strategy are dispersed to each device (i.e., the target following device or the leader device) in the multi-device collaborative control, thereby effectively reducing the complexity of the operation of the multi-device collaborative control system. Then, the target following device calculates the target moment, the current moment, the target state data, and the current state data according to a preset consensus control protocol algorithm to obtain the control gain of the target following device relative to the leader device. Finally, it superimposes the control gain on the current state data, and then can perform collaborative control on the target following device synchronously with the leader device, thereby effectively avoiding the technical problem of poor stability and reliability in the multi-device collaborative control in the prior art by improving the consistency of the multi-device collaborative movement. Brief Description of the Drawings

[0048] Figure 1 It is a schematic flowchart of the first embodiment of the multi-device collaborative control method of this application;

[0049] Figure 2 It is a motor control strategy diagram related to the solution of the embodiment of this application;

[0050] Figure 3 It is a topology diagram related to the solution of the embodiment of this application;

[0051] Figure 4It is a schematic diagram of the position between the following device and the mover guide rail involved in the embodiment solution of the present application;

[0052] Figure 5 It is a graph showing the change of mutual inductance with position involved in the embodiment solution of the present application;

[0053] Figure 6 It is an effect diagram of tracking involved in the embodiment solution of the present application;

[0054] Figure 7 It is a schematic diagram of tracking error involved in the embodiment solution of the present application;

[0055] Figure 8 It is a schematic diagram of the structure of the multi-device collaborative control device involved in the embodiment solution of the present application;

[0056] Figure 9 It is a schematic diagram of the structure of the terminal device involved in the embodiment solution of the present application.

[0057] The realization, functional features and advantages of the purpose of the present application will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific embodiments

[0058] The embodiment of the present application provides a multi-device collaborative control method. Refer to Figure 1 as shown. Figure 1 It is a schematic flowchart of the first embodiment of the multi-device collaborative control method of the present application.

[0059] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application.

[0060] In this embodiment, refer to Figure 2 , Figure 2 It is a motor control strategy diagram involved in the embodiment solution of the present application. The multi-device collaborative control method described in the present application is applied to the target following device in the multi-device collaborative control system, and is specifically executed by the controller in the target following device; in addition, the multi-device collaborative control system further includes: a leading device and other following devices, wherein a communication connection is established between the target following device and the leading device, or the target following device establishes a communication connection with the leading device through the other following devices.

[0061] In this embodiment, refer to Figure 2 , the target following device may include: a controller, a force flow conversion module, a plurality of current drivers, an LSRM, a state buffer, and a linear encoder, and their specific connection manners are as Figure 2 shown.

[0062] It should be noted that the leading device and the following devices (i.e., the target following device and other following devices) are motor devices of the same type. For example, LSRM (Linear Switched Reluctance Motor). Herein, the leading device can be understood as a device that leads multiple following devices to perform the same operation together; the number of following devices includes one or more, which can be understood as devices that follow the leading device to perform the same operation. In other words, the status data of the following devices should be consistent with the status data of the leading device, where the status data may include position data and speed data.

[0063] The multi-device collaborative control method of the present application includes:

[0064] Step S10: Obtain the target status data sent by the adjacent device at the target moment based on a preset multi-device collaborative control model, where the adjacent device is the leading device or other following devices;

[0065] In this embodiment, according to the communication connection between the target following device and the adjacent device, the controller obtains the target status data sent by the adjacent device at the target moment through a preset multi-device collaborative control model.

[0066] It should be noted that the adjacent device can be understood as the leading device connected to the target following device, or other following devices connected to the target following device.

[0067] The target status data can be understood as the speed data of the adjacent device at the target moment (i.e., a past time node) and the position data of the adjacent device relative to the mover guide.

[0068] In this embodiment, the target status data sent by the adjacent device at the target moment is obtained through a preset multi-device collaborative control model, thereby dispersing the complex centralized information processing and calculation in the existing centralized control strategy to each device (i.e., the target following device or the leading device) in the multi-device collaborative control, and thus effectively reducing the complexity of the operation of the multi-device collaborative control system.

[0069] Step S20: Determine the current moment when the target status data is received, and read the current status data of the target following device at the current moment;

[0070] In this embodiment, according to the communication connection between the target following device and the adjacent device, when the controller receives the target status data sent by the adjacent device, the controller can further determine the current moment when the target status data is received, and read the current status data of the target following device at the current moment.

[0071] Step S30: Calculate the target following device's control gain relative to the leader device according to a preset consistency control protocol algorithm using the target time, the current time, the target state data, and the current state data.

[0072] In this embodiment, first, the controller obtains the cached state data of the target following device at the target time through the state buffer in the target following device and determines the delay time when the controller receives the cached state data uploaded by the state buffer. Then, at the node of the current time, calculate the current state weighted term of the target following device according to a preset consistency control protocol algorithm using the current state data, the target state data, and the cached state data. Then, obtain the past time node of the target following device according to the first difference between the current time and the target time, and calculate the past state weighted term of the target following device according to a preset consistency control protocol algorithm using the current state data, the target state data, and the cached state data at the past time node. Further, obtain the delay time node of the target following device according to the second difference between the first difference and the delay time, and calculate the delay state weighted term of the target following device according to a preset consistency control protocol algorithm using the current state data, the target state data, and the cached state data at the delay time node. Finally, calculate the control gain of the target following device relative to the leader device according to the current state weighted term, the past state weighted term, and the delay state weighted term.

[0073] In this embodiment, the control gain of the target following device relative to the leader device can be quickly and accurately obtained through the preset consistency control protocol algorithm, thus laying a solid foundation for improving the consistency of multi-device collaborative movement.

[0074] Step S40: Superimpose the control gain on the current state data to perform synchronous collaborative control on the target following device with the leader device.

[0075] In this embodiment, the controller superimposes the control gain on the current state data to perform synchronous collaborative control on the target following device with the leader device, thereby eliminating the state error data between the target following device and the leader device and effectively improving the consistency of multi-device collaborative movement.

[0076] In summary, in the present application, the multi-device collaborative control method is applied to the target following device in the multi-device collaborative control system. The multi-device collaborative control system further includes: a leader device and other following devices. Among them, a communication connection is established between the target following device and the leader device, or the target following device establishes a communication connection with the leader device through other following devices. The target following device first obtains the target state data sent by the adjacent device at the target moment based on the preset multi-device collaborative control model, where the adjacent device is the leader device or other following devices; then determines the current moment when the target state data is received, and reads the current state data of the target following device at the current moment; then calculates the target moment, the current moment, the target state data, and the current state data according to the preset consistency control protocol algorithm to obtain the control gain of the target following device relative to the leader device; finally, superimposes the control gain on the current state data to perform collaborative control on the target following device synchronously with the leader device.

[0077] Different from the traditional multi-device collaborative control method, the present application designs a multi-device collaborative control model. The target following device can obtain the target state data sent by the adjacent device at the target moment based on this multi-device collaborative control model, thereby effectively liberating the multi-device collaborative control system from the need for high-performance centralized computing units. In other words, the complex centralized information processing and calculation in the existing centralized control strategy are distributed to each device (i.e., the target following device or the leader device) in the multi-device collaborative control, thereby effectively reducing the complexity of the operation of the multi-device collaborative control system; then, the target following device calculates the target moment, the current moment, the target state data, and the current state data according to the preset consistency control protocol algorithm to obtain the control gain of the target following device relative to the leader device, and finally superimposes the control gain on the current state data, and then can perform collaborative control on the target following device synchronously with the leader device, thereby effectively avoiding the technical problem of poor stability and reliability in the multi-device collaborative control in the prior art by improving the consistency of the multi-device collaborative movement.

[0078] Further, based on the first embodiment of the multi-device collaborative control of the present application, the second embodiment of the multi-device collaborative control of the present application is proposed.

[0079] Further, in some feasible embodiments, a state buffer is provided inside the target following device. The above step S30: calculating the target moment, the current moment, the target state data, and the current state data according to the preset consistency control protocol algorithm to obtain the control gain of the target following device relative to the leader device may further include the following implementation steps:

[0080] Step S301: Obtain the cached status data of the target following device at the target moment through the status buffer, and determine the delay moment when the cached status data is received;

[0081] In this embodiment, the controller obtains the cached status data of the target following device at the target moment through the status buffer, and determines the delay moment when the cached status data is received.

[0082] It should be noted that the delay moment can be understood as the time for the status buffer to store, read, and transmit the historical status data of the target following device.

[0083] Step S302: Calculate the current state weighted term of the target following device by calculating the current status data, the target status data, and the cached status data according to the consistency control protocol algorithm on the node at the current moment;

[0084] In this embodiment, the controller calculates the current state weighted term of the target following device by calculating the current status data, the target status data, and the cached status data according to the preset consistency control protocol algorithm on the node at the current moment.

[0085] Step S303: Obtain the past time node of the target following device according to the first difference between the current moment and the target moment, and calculate the current status data, the target status data, and the cached status data according to the consistency control protocol algorithm on the past time node to obtain the past state weighted term of the target following device;

[0086] In this embodiment, the controller obtains the past time node of the target following device according to the first difference between the current moment and the target moment, and calculates the current status data, the target status data, and the cached status data according to the consistency control protocol algorithm on the past time node to obtain the past state weighted term of the target following device.

[0087] Step S304: Obtain the delay time node of the target following device according to the second difference between the first difference and the delay moment, and calculate the current status data, the target status data, and the cached status data according to the consistency control protocol algorithm on the delay time node to obtain the delay state weighted term of the target following device;

[0088] In this embodiment, the controller obtains the delay time node of the target following device according to the second difference between the first difference and the delay moment, and calculates the current status data, the target status data, and the cached status data according to the consistency control protocol algorithm on the delay time node to obtain the delay state weighted term of the target following device.

[0089] Step S305: Calculate according to the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain a control gain of the target following device relative to the leader device.

[0090] In this embodiment, the controller calculates according to the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain a control gain of the target following device relative to the leader device.

[0091] Further, in some other feasible embodiments, the above step S305: Calculate according to the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain a control gain of the target following device relative to the leader device may further include the following implementation steps:

[0092] Step S3051: Determine an adjacency matrix coefficient of the multi-device collaborative control system according to a preset topology graph, and obtain an adjacency coefficient between the target following device and the leader device;

[0093] In this embodiment, the controller searches for an adjacency matrix coefficient of the multi-device collaborative control system from the preset topology graph. After finding the adjacency matrix coefficient of the multi-device collaborative control system, the controller will obtain an adjacency coefficient between the target following device and the leader device, where the adjacency coefficient corresponds one-to-one to the adjacency matrix coefficient.

[0094] In a specific embodiment, referring to Figure 3 , Figure 3 is the topology graph involved in the solution of the embodiment of the present application, where Figure 3 The adjacency matrix coefficient (i.e., the Laplacian matrix) corresponding to the upper left connection graph is L(1), Figure 3 The adjacency matrix coefficient corresponding to the lower left connection graph is L(3), Figure 3 The adjacency matrix coefficient corresponding to the upper right connection graph is L(2), Figure 3 The adjacency matrix coefficient corresponding to the lower right connection graph is L(4). The specific expressions of the above L(1), L(2), L(3), and L(4) are as follows:

[0095]

[0096]

[0097] In addition, it should be noted that L(1) corresponds to D(1), L(2) corresponds to D(2), L(3) corresponds to D(3), and L(4) corresponds to D(4). The specific expressions of D(1), D(2), D(3), and D(4) are as follows:

[0098]

[0099]

[0100] Step S3052: In the multi-device collaborative control model, determine the input matrix of the target following device according to the adjacency matrix coefficient and the adjacency coefficient;

[0101] In this embodiment, the controller first performs parameter identification according to the adjacency matrix coefficient and the adjacency coefficient to obtain the multi-device state matrix A and the control matrix B, and then inputs the multi-device state matrix A and the control matrix B into a preset multi-device collaborative control model for calculation, and the input matrix of the target following device can be obtained.

[0102] It should be noted that the preset multi-device collaborative control model can be understood as the state space equation of the LSRM unit in the target following device being:

[0103]

[0104] Among them, Ax() can be understood as the multi-device state matrix A, and Bu() can be understood as the control matrix B, can be understood as the input matrix of the target following device.

[0105] In addition, it should be noted that performing parameter identification according to the adjacency matrix coefficient and the adjacency coefficient to obtain the multi-device state matrix A and the control matrix B can be expressed as follows:

[0106]

[0107] Step S3053: Calculate according to the adjacency matrix coefficient, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leader device.

[0108] In this embodiment, the controller calculates according to the adjacency matrix coefficient, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leader device.

[0109] Furthermore, in some other feasible embodiments, the above Step S3053: Calculate according to the adjacency matrix coefficient, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leader device may further include the following implementation steps:

[0110] Step S30531: Calculate the control gain of the target following device relative to the leader device according to a preset gain calculation formula, where the gain calculation formula is as follows:

[0111]

[0112] where, the u i (t) refers to the input matrix, α, β, χ are preset weighting coefficients, and x i (t) - x j (t) and x i (t) - x0(t) refer to the current state weighting term, x i (t - d) - x j (t - d) and x i (t - d) - x0(t - d) refer to the past state weighting term, x i (t - d - τ) - x j (t - d - τ) and x i (t - d - τ) - x0(t - d - τ) refer to the time-delay state weighting term, a ij (κ(t)) refers to the adjacency matrix coefficient, b i (κ(t)) is the adjacency coefficient, and K(κ(t)) refers to the control gain of the target following device relative to the leader device.

[0113] In a specific embodiment, the controller obtains the state error between the i-th follower (target following device) and the leader, that is, the error vector Δx i (t) = x i (t) - x0(t), and then calculates according to a preset gain calculation formula for to obtain a gain expression as shown in Equation 1:

[0114]

[0115] Then, after determining that the parameters τ > 0, d > 0, υ > 0, where v refers to the speed data of the target following device, other following devices, and the leader device, if there exists a matrix are all positive definite matrices, and when the following matrix inequality is satisfied, the multi-device cooperative control system composed of multiple motors (i.e., LSRM) will achieve mean-square uniform stability.

[0116]

[0117] where, is the gain-related matrix, i.e., the control gain of the target following device relative to the leader device;

[0118]

[0119]

[0120]

[0121] After determining the upper and lower bounds of the transition rate according to the matrix inequality as and performing calculations according to the above gain expression, the control gain of the target following device relative to the leader device can be obtained. Among them, K(1) corresponds to L(1) and D(1) respectively, K(2) corresponds to L(2) and D(2) respectively, K(3) corresponds to L(3) and D(3) respectively, and K(4) corresponds to L(4) and D(4) respectively. The specific values of K(1), K(2), K(3), and K(4) are as follows:

[0122] K(1) = (10.5023 3.2473), K(2) = (8.1221 4.2368),

[0123] K(3) = (6.2837 2.5636), K(4) = (13.7163 5.8622).

[0124] Furthermore, in some feasible embodiments, referring to Figure 4 , Figure 4 is a schematic diagram of the position between the following device and the moving guide rail involved in the embodiment solution of the present application. The multi-device collaborative control system further includes: a moving guide rail, the motor device is connected to the gear part of the moving guide rail, and the multi-device collaborative control method may further include the following implementation steps:

[0125] Step F10: Obtain the position angle of the target following device relative to the moving guide rail and read the phase current input into the target following device;

[0126] In this embodiment, the controller will obtain the position angle of the target following device relative to the moving guide rail and read the phase current input into the target following device.

[0127] It should be noted that the phase current can be understood as calculated according to the current equation of the three-phase windings of the motor. Among them, the current equation of the three-phase windings of the motor can be as shown in Equation 2 below:

[0128]

[0129] where, u n and i nrefers to the voltage and current of the n-th phase winding, R n refers to the resistance of the n-th phase winding, ψ n (s, i n ) represents the magnetic flux. In a linear switched reluctance motor, the value of the magnetic flux is related to the motor position s and the phase current i n .

[0130] In addition, it should be noted that considering the case where the linear switched reluctance motor operates at a relatively low speed, its back electromotive force can be ignored, that is, the following formula 3 can be obtained according to formula 2:

[0131]

[0132] where L n (s, i n ) is the phase inductance, and its value is related to the motor position and the phase current.

[0133] Step F20: Determine the phase inductance of the target following device according to the position angle and the phase current;

[0134] In this embodiment, the controller first obtains the threshold interval to which the position angle belongs, then obtains the relevant inductance calculation function corresponding to the threshold interval to which the position angle belongs, and then calculates the position angle and the phase current according to the relevant inductance calculation function to obtain the phase inductance of the target following device.

[0135] It should be noted that the threshold intervals include a first threshold interval (i.e., 0 < S < 2), a second threshold interval (i.e., 2 ≤ S < 4), and a third threshold interval (i.e., 4 ≤ S < 6). The threshold interval to which the position angle belongs can be determined according to the specific data of the position angle S.

[0136] In addition, it should be noted that the inductance calculation function can be understood as a piecewise function of the phase inductance varying with position at different current magnitudes obtained through finite element analysis considering the phase current. The specific expression is as follows:

[0137]

[0138] where K(i, s) = as 3 + bs 2 + cs + d, and Table 1 gives the values of a, b, c, and d at different current magnitudes. In addition, the variation of the phase inductance with position at different current magnitudes can be referred to Figure 5 , Figure 5 which is the graph of the phase inductance varying with position involved in the solution of the embodiment of the present application.

[0139]

[0140] Table 1 Inductance parameters of K(i, s)

[0141] Step F30: Construct the multi-device collaborative control model according to the phase inductance and the position angle.

[0142] In this embodiment, the controller trains and learns the phase inductance and the position angle to establish a multi-device collaborative control model.

[0143] In a specific embodiment, first, the kinematic equation of the LSRM can be given from the perspective of kinematics, and its expression is as shown in Equation 4 below:

[0144]

[0145] Where M is the mass of the motor, μ represents the friction coefficient, f is the motor load, and F is the traction force required or generated by the motor. Then, according to the kinematic equation of the LSRM, the discrete-time form of the second-order mathematical model of the LSRM can be obtained, as shown in Equation 5 below:

[0146] A(z -1 )s(t) = B(z -1 )F(t), Equation 5

[0147] Where A(z -1 ) = 1 + a1z -1 + a2z -2 , B(z -1 ) = b1z -2 + b0z -1 , and the parameters a1, a2, b1, and b0 of the LSRM can all be obtained through the parameter online identification method. After determining the z-domain transfer function, the controller converts the second-order mathematical model of the LSRM into the state-space equation of the LSRM according to MATLAB to establish a multi-device collaborative control model.

[0148] It should be noted that F, the traction force required or generated by the motor, can be understood as the horizontal traction force generated by three-phase excitation. It can be as shown in Equation 6 below:

[0149]

[0150] Where the direction of the horizontal traction force of the LSRM is independent of the current direction and only related to the positive and negative of the differential of the inductance and the position .

[0151] Furthermore, in some feasible embodiments, the above step F20: Determine the phase inductance of the target following device according to the position angle and the phase current, further includes the following implementation steps:

[0152] Step F201: Determine whether the position angle belongs to a preset first threshold interval;

[0153] In this embodiment, the controller needs to determine whether the position angle belongs to a preset first threshold interval.

[0154] Step F202: When it is determined that the position angle belongs to the first threshold interval, obtain a first inductance calculation function corresponding to the first threshold interval;

[0155] In this embodiment, when it is determined that the position angle belongs to a preset first threshold interval, the controller will obtain a first inductance calculation function corresponding to the first threshold interval.

[0156] Step F203: Calculate the position angle and the phase current according to the first inductance calculation function to obtain the phase inductance of the target following device.

[0157] In this embodiment, the controller calculates the position angle and the phase current according to the first inductance calculation function to obtain the phase inductance of the target following device.

[0158] Further, in some feasible embodiments, after the above step F201: determining whether the position angle belongs to a preset first threshold interval, the multi-device collaborative control method further includes the following implementation steps:

[0159] Step G10: When it is determined that the position angle does not belong to the first threshold interval, detect whether the position angle belongs to a preset second threshold interval, where the first threshold interval is smaller than the second threshold interval;

[0160] In this embodiment, when it is determined that the position angle does not belong to a preset first threshold interval, the controller detects whether the position angle belongs to a preset second threshold interval, where the first threshold interval is smaller than the second threshold interval.

[0161] Step G20: After it is determined that the position angle belongs to the second threshold interval, obtain a second inductance calculation function corresponding to the second threshold interval, and calculate the position angle and the phase current according to the second inductance calculation function to obtain the phase inductance of the target following device;

[0162] In this embodiment, after it is determined that the position angle belongs to the second threshold interval, the controller will obtain a second inductance calculation function corresponding to the second threshold interval, and calculate the position angle and the phase current according to the second inductance calculation function to obtain the phase inductance of the target following device.

[0163] Step Y10: After determining that the position angle does not belong to the second threshold interval, it is determined that the position angle is in a preset third threshold interval, and the position angle and the phase current are calculated according to a third inductance calculation function corresponding to the third threshold interval to obtain the phase inductance of the target following device, where the third threshold interval is greater than the second threshold interval.

[0164] In this embodiment, after determining that the position angle does not belong to the second threshold interval, the controller will determine that the position angle is in a preset third threshold interval, and calculate the position angle and the phase current according to a third inductance calculation function corresponding to the third threshold interval to obtain the phase inductance of the target following device, where the third threshold interval is greater than the second threshold interval.

[0165] Further, in another embodiment, taking a linear switched reluctance motor as an example, according to the above Figure 3 shown topology diagram for experiments, through experimental verification, the tracking effect diagram of the linear switched reluctance motor system is obtained, as Figure 6 shown, Figure 6 is the tracking effect diagram involved in the solution of the embodiment of the present application, where the initial positions of the three tracking motors are respectively set to: -10mm, +20mm, -20mm. The initial speeds of the three tracking motors are all 0mm / s. Figure 6 Shows the trajectory diagrams of the tracking error, speed error, and state error of the three follower motors with respect to the leader within the time range of 0 - 1 second during the collaborative movement of the multi-device collaborative control system. From Figure 6 it can be seen that the error trajectories of the three follower motors with respect to the leader finally tend to (0,0), which means that the error system can finally tend to be stable.

[0166] In addition, referring to Figure 7 shown, Figure 7 is the schematic diagram of the tracking error involved in the solution of the embodiment of the present application, Figure 7 gives the tracking position error diagram of the three follower motors with respect to the leader within the time range of 1 - 20 seconds. As shown in the figure, affected by random topological jumps, the tracking error has some fluctuations. Generally speaking, the position error range fluctuates between +0.1898mm and -0.2065mm. Among them, the position error of follower 1 fluctuates between +0.1898mm and -0.1719mm, the position error of follower 2 fluctuates between +0.1642mm and -0.2065mm, and the position error of follower 3 fluctuates between +0.1840mm and -0.1730mm. The average errors of the three follower motors are 0.0795mm, 0.0949mm, and 0.0797mm respectively.

[0167] In summary, in the present application, by constructing a multi-device collaborative control model, the originally complex centralized information processing and calculation in the multi-device collaborative control system are dispersed to each device, thereby effectively reducing the complexity of the operation of the multi-device collaborative control system. Then, according to the preset consistency control protocol algorithm, the control gain of the target following device is obtained, and the control gain is superimposed on the current state data of the target following device, so as to achieve the purpose of real-time collaborative motion control of the multi-device collaborative control system.

[0168] In addition, the present application also provides a multi-device collaborative control device. Please refer to Figure 8 , Figure 8 which is a schematic structural diagram of the multi-device collaborative control device involved in the embodiment solution of the present application.

[0169] The multi-device collaborative control device of the present application includes:

[0170] An acquisition module H01, configured to acquire target state data sent by an adjacent device at a target moment based on a preset multi-device collaborative control model, where the adjacent device is the leading device or the other following devices;

[0171] A reading module H02, configured to determine the current moment when the target state data is received, and read the current state data of the target following device at the current moment;

[0172] A calculation module H03, configured to calculate the target moment, the current moment, the target state data, and the current state data according to a preset consistency control protocol algorithm to obtain a control gain of the target following device relative to the leading device;

[0173] A superimposing module H04, configured to superimpose the control gain on the second state data to perform synchronous collaborative control on the target following device with the leading device.

[0174] Optionally, the calculation module H03 may further include:

[0175] A receiving unit, configured to obtain cached state data of the target following device at the target moment through the state buffer, and determine a delay moment when the cached state data is received;

[0176] A first calculation unit, configured to calculate the current state data, the target state data, and the cached state data according to the consistency control protocol algorithm on the node at the current moment to obtain a current state weighted term of the target following device;

[0177] A second calculation unit, configured to obtain a past time node of the target following device according to a first difference between the current moment and the target moment, and calculate the current state data, the target state data, and the cached state data at the past time node according to the consistency control protocol algorithm to obtain a past state weighted term of the target following device;

[0178] A third calculation unit, configured to obtain a delay time node of the target following device according to a second difference between the first difference and the delay moment, and calculate the current state data, the target state data, and the cached state data at the delay time node according to the consistency control protocol algorithm to obtain a delay state weighted term of the target following device;

[0179] A fourth calculation unit, configured to calculate according to the current state weighted term, the past state weighted term, and the delay state weighted term to obtain a control gain of the target following device relative to the leader device.

[0180] Optionally, the calculation module H03 may further include:

[0181] An adjacency unit, configured to determine an adjacency matrix coefficient of the multi-device cooperative control system according to a preset topology graph, and obtain an adjacency coefficient between the target following device and the leader device;

[0182] An input unit, configured to determine an input matrix of the target following device according to the adjacency matrix coefficient and the adjacency coefficient in the multi-device cooperative control model;

[0183] A fifth calculation unit, configured to calculate according to the adjacency matrix coefficient, the adjacency coefficient, the input matrix, the current state weighted term, the past state weighted term, and the delay state weighted term to obtain a control gain of the target following device relative to the leader device.

[0184] Optionally, the calculation module H03 may further include:

[0185] A gain calculation unit, configured to calculate the adjacency matrix coefficient, the adjacency coefficient, the input matrix, the current state weighted term, the past state weighted term, and the delay state weighted term according to a preset gain calculation formula to obtain a control gain of the target following device relative to the leader device, where the gain calculation formula is:

[0186]

[0187] Wherein, the u i (t) refers to the input matrix, α, β, χ are preset weighting coefficients, and xi (t) - x j (t) and x i (t) - x0(t) refers to the current state weighting term, x i (t - d) - x j (t - d) and x i (t - d) - x0(t - d) refers to the past state weighting term, x i (t - d - τ) - x j (t - d - τ) and x i (t - d - τ) - x0(t - d - τ) refers to the time - delay state weighting term, a ij (κ(t)) refers to the adjacency matrix coefficient, b i (κ(t)) is the adjacency coefficient, and K(κ(t)) refers to the control gain of the target following device relative to the leader device.

[0188] Optionally, the acquisition module H01 may include:

[0189] A current reading unit for acquiring the position angle of the target following device relative to the mover guide rail and reading the phase current input into the target following device;

[0190] An inductance determination unit for determining the phase inductance of the target following device according to the position angle and the phase current;

[0191] A construction unit for constructing the multi - device collaborative control model according to the phase inductance and the position angle.

[0192] Optionally, the acquisition module H01 may include:

[0193] A judgment unit for judging whether the position angle belongs to a preset first threshold interval;

[0194] A first calculation function acquisition unit for acquiring the first inductance calculation function corresponding to the first threshold interval when it is determined that the position angle belongs to the first threshold interval;

[0195] A sixth calculation unit for calculating the phase inductance of the target following device according to the first inductance calculation function for the position angle and the phase current.

[0196] Optionally, the acquisition module H01 may include:

[0197] A detection unit for detecting whether the position angle belongs to a preset second threshold interval when it is determined that the position angle does not belong to the first threshold interval, where the first threshold interval is less than the second threshold interval;

[0198] A seventh calculation unit, configured to, after determining that the position angle belongs to the second threshold interval, obtain a second inductance calculation function corresponding to the second threshold interval, and calculate the position angle and the phase current according to the second inductance calculation function to obtain the phase inductance of the target following device;

[0199] An eighth calculation unit, configured to, after determining that the position angle does not belong to the second threshold interval, determine that the position angle is in a preset third threshold interval, and calculate the position angle and the phase current according to a third inductance calculation function corresponding to the third threshold interval to obtain the phase inductance of the target following device, where the third threshold interval is greater than the second threshold interval.

[0200] Each functional module of the multi-device collaborative control device of the present application implements the steps of the multi-device collaborative control method of the present application as described above during operation.

[0201] In addition, the present application further provides a terminal device. Please refer to Figure 9 , Figure 9 which is a schematic structural diagram of the terminal device involved in the solution of the embodiment of the present application. The terminal device in the embodiment of the present application may specifically be a device for locally running multi-device collaborative control.

[0202] As Figure 9 shown, the terminal device in the embodiment of the present application may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005, and a sensing unit 1006. Among them, the communication bus 1002 is used to implement connection communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface).

[0203] The memory 1005 is disposed on the main body of the terminal device. A program is stored on the memory 1005, and when the program is executed by the processor 1001, corresponding operations are implemented. The memory 1005 is further used to store parameters for the terminal device to use. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0204] Those skilled in the art can understand, Figure 9The terminal device structure shown does not constitute a limitation on the terminal device, and it may include more or fewer components than shown in the figure, or combine some components, or have a different component arrangement.

[0205] As Figure 9 shown, in the memory 1005 as a storage medium, there may be included an operating system, a network communication module, a user interface module, and a multi-device collaborative control program for the terminal device.

[0206] In Figure 9 the terminal device shown, the processor 1001 may be used to call the multi-device collaborative control program stored in the memory 1005 and execute the steps of the above multi-device collaborative control method.

[0207] It should be noted that in this article, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or system including that element.

[0208] The serial numbers of the above embodiments of the present application are only for description and do not represent the superiority or inferiority of the embodiments.

[0209] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a computer storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to enable a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application.

[0210] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application accordingly. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, is equally included in the patent protection scope of the present application.

Claims

1. A multi-device collaborative control method, characterized in that, The multi-device collaborative control method is applied to a target following device in a multi-device collaborative control system. The multi-device collaborative control system further includes: a leader device and other following devices. Among them, a communication connection is established between the target following device and the leader device, or the target following device establishes a communication connection with the leader device through the other following devices; The multi-device collaborative control method includes: Obtaining target state data sent by an adjacent device at a target moment based on a preset multi-device collaborative control model, where the adjacent device is the leader device or the other following devices; Determining the current moment when the target state data is received, and reading the current state data of the target following device at the current moment; Calculating the target following device's control gain relative to the leader device according to a preset consensus control protocol algorithm for the target moment, the current moment, the target state data, and the current state data; Adding the control gain to the current state data to perform collaborative control on the target following device synchronously with the leader device; A state buffer is provided inside the target following device. The step of calculating the control gain of the target following device relative to the leader device according to a preset consensus control protocol algorithm for the target moment, the current moment, the target state data, and the current state data includes: Obtaining the cached state data of the target following device at the target moment through the state buffer, and determining the delay moment when the cached state data is received; Calculating the current state weighted term of the target following device according to the consensus control protocol algorithm for the current state data, the target state data, and the cached state data at the node of the current moment; Obtaining the past time node of the target following device according to the first difference between the current moment and the target moment, and calculating the past state weighted term of the target following device according to the consensus control protocol algorithm for the current state data, the target state data, and the cached state data at the past time node; Obtaining the delay time node of the target following device according to the second difference between the first difference and the delay moment, and calculating the delay state weighted term of the target following device according to the consensus control protocol algorithm for the current state data, the target state data, and the cached state data at the delay time node; Calculating the control gain of the target following device relative to the leader device according to the current state weighted term, the past state weighted term, and the delay state weighted term; The step of calculating the control gain of the target following device relative to the leader device according to the current state weighted term, the past state weighted term, and the delay state weighted term includes: Determine the adjacency matrix coefficients of the multi-device collaborative control system according to a preset topological graph, and obtain the adjacency coefficient between the target following device and the leading device; In the multi-device collaborative control model, determine the input matrix of the target following device according to the adjacency matrix coefficients and the adjacency coefficient; Perform calculations based on the adjacency matrix coefficients, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leading device.

2. The multi-device collaborative control method according to claim 1, wherein The step of performing calculations based on the adjacency matrix coefficients, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term to obtain the control gain of the target following device relative to the leading device includes: Perform calculations on the adjacency matrix coefficients, the adjacency coefficient, the input matrix, the current state weighting term, the past state weighting term, and the time-delay state weighting term according to a preset gain calculation formula to obtain the control gain of the target following device relative to the leading device, where the gain calculation formula is: Among them, the (t) refers to the input matrix, is a preset weighting coefficient, and refers to the current state weighting term, and refers to the past state weighting term, and refers to the time-delay state weighting term, refers to the adjacency matrix coefficient, is the adjacency coefficient, refers to the control gain of the target following device relative to the leader device.

3. The multi-device collaborative control method according to claim 1, wherein, The multi-device collaborative control system further includes: a mover guide rail, and the target following device is connected to the gear part of the mover guide rail. The method further includes: Obtain the position angle of the target following device relative to the mover guide rail, and read the phase current input into the target following device; Determine the phase inductance of the target following device according to the position angle and the phase current; Construct the multi-device collaborative control model according to the phase inductance and the position angle.

4. The multi-device collaborative control method according to claim 3, wherein The step of determining the phase inductance of the target following device according to the position angle and the phase current includes: Judge whether the position angle belongs to a preset first threshold interval; When it is determined that the position angle belongs to the first threshold interval, obtain the first inductance calculation function corresponding to the first threshold interval; Perform calculations on the position angle and the phase current according to the first inductance calculation function to obtain the phase inductance of the target following device.

5. The multi-device collaborative control method according to claim 4, wherein, After the step of judging whether the position angle belongs to the preset first threshold interval, the method includes: When it is determined that the position angle does not belong to the first threshold interval, detect whether the position angle belongs to a preset second threshold interval, where the first threshold interval is smaller than the second threshold interval; After it is determined that the position angle belongs to the second threshold interval, obtain the second inductance calculation function corresponding to the second threshold interval, and perform calculations on the position angle and the phase current according to the second inductance calculation function to obtain the phase inductance of the target following device; After determining that the position angle does not belong to the second threshold interval, it is determined that the position angle is in a preset third threshold interval, and the phase inductance of the target following device is calculated by calculating the position angle and the phase current according to a third inductance calculation function corresponding to the third threshold interval, where the third threshold interval is greater than the second threshold interval.

6. A multi-device collaborative control device for the multi-device collaborative control method according to claim 1, characterized in that, The multi-device collaborative control device includes: An acquisition module, configured to acquire target state data sent by an adjacent device at a target moment based on a preset multi-device collaborative control model, where the adjacent device is the leading device or the other following devices; A reading module, configured to determine the current moment when the target state data is received, and read the current state data of the target following device at the current moment; A calculation module, configured to calculate a control gain of the target following device relative to the leading device according to a preset consensus control protocol algorithm for the target moment, the current moment, the target state data, and the current state data, where a state buffer is provided inside the target following device; The calculation module is further configured to obtain buffered state data of the target following device at the target moment through the state buffer, and determine a delay moment when the buffered state data is received; calculate a current state weighted term of the target following device according to the consensus control protocol algorithm for the current state data, the target state data, and the buffered state data at the node of the current moment; obtain a past time node of the target following device according to a first difference between the current moment and the target moment, and calculate a past state weighted term of the target following device according to the consensus control protocol algorithm for the current state data, the target state data, and the buffered state data at the past time node; obtain a delay time node of the target following device according to a second difference between the first difference and the delay moment, and calculate a delay state weighted term of the target following device according to the consensus control protocol algorithm for the current state data, the target state data, and the buffered state data at the delay time node; calculate a control gain of the target following device relative to the leading device according to the current state weighted term, the past state weighted term, and the delay state weighted term; The calculation module is further configured to determine an adjacency matrix coefficient of the multi-device collaborative control system according to a preset topology map, and obtain an adjacency coefficient between the target following device and the leading device; determine an input matrix of the target following device according to the adjacency matrix coefficient and the adjacency coefficient in the multi-device collaborative control model; calculate a control gain of the target following device relative to the leading device according to the adjacency matrix coefficient, the adjacency coefficient, the input matrix, the current state weighted term, the past state weighted term, and the delay state weighted term; An overlay module, configured to overlay the control gain on the second state data, and perform cooperative control on the target following device in synchronization with the leader device.

7. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a multi-device cooperative control program stored on the memory and executable on the processor. When the processor executes the multi-device cooperative control program, the steps of the multi-device cooperative control method according to any one of claims 1 to 5 are implemented.

8. A computer storage medium, characterized in that, A multi-device cooperative control program is stored on the computer storage medium. When the multi-device cooperative control program is executed by a processor, the steps of the multi-device cooperative control method according to any one of claims 1 to 5 are implemented.

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