A multi-motor balanced control method and device for automatically and quickly deploying and retracting a tent

Abstract

The present invention discloses a multi-motor balanced control method and device for an automatic and rapid tent deployment. The method comprises: collecting a set of working index information of a motor group for the automatic and rapid tent deployment; obtaining a motor target speed and a total input power value; performing working state evaluation processing on a subset of the working index information of each motor to obtain a corresponding state evaluation value; performing balanced control processing on the motor target speed, the total input power value, the state evaluation values ​​of all motors, and the working index information subset to obtain a balanced input power value for each motor; and inputting the balanced input power value of each motor into the corresponding motor to complete balanced control of the multi-motor for the automatic and rapid tent deployment.

Description

Technical Field

[0001] The present invention relates to the fields of industrial data processing, intelligent control and strategy optimization technology, and in particular to a multi-motor balanced control method and device for automatically and quickly deploying and retracting a tent. Background Art

[0002] In existing automatic rapid tent deployment and folding technologies, the multi-motor drive system is a key component for achieving rapid tent deployment and folding. However, due to the significant differences in the working environment and load of each motor during the tent deployment and folding process, the working conditions between the motors are unbalanced. For example, some motors may experience a drop in speed or even overload due to excessive load, while other motors may waste power due to insufficient load. This imbalance not only affects the efficiency of tent deployment and folding, but may also cause motor damage, reducing the reliability and service life of the system. In addition, most existing control methods use simple power distribution or speed synchronization strategies, which cannot effectively solve the dynamic balance problem between motors and are difficult to meet the high-precision control requirements under complex working conditions. Summary of the Invention

[0003] The present invention mainly solves the problem of multi-motor balanced control of an automatic and rapid tent deployment, and discloses a multi-motor balanced control method and device for an automatic and rapid tent deployment.

[0004] In a first aspect, an embodiment of the present invention discloses a multi-motor balanced control method for automatically and quickly deploying and retracting a tent, comprising:

[0005] S1, collecting a set of working indicator information of a motor group for automatically and quickly deploying and retracting a tent; the working indicator information set includes a subset of working indicator information of each motor; the working indicator information subset includes a data sequence of each type of technical indicator of the motor; the data sequence is a sequence of sampled values ​​of the technical indicators collected at each discrete moment;

[0006] S2, obtain the motor target speed and total input power value;

[0007] S3, performing working status evaluation processing on the working indicator information subset of each motor to obtain a corresponding status evaluation value;

[0008] S4, performing a balancing control process on the motor target speed, the total input power value, the state evaluation values ​​of all motors, and the work index information subset to obtain a balanced input power value for each motor;

[0009] S5, inputting the balanced input power value of each motor to the corresponding motor, thereby completing the balanced control of the multiple motors for automatically and quickly deploying and retracting the tent.

[0010] The working status evaluation process is performed on the working indicator information subset of each motor to obtain a corresponding status evaluation value, including:

[0011] S31, obtaining normal values ​​of each type of technical indicators of the motor;

[0012] S32, subtracting the data sequence of each type of technical indicator in the subset of working indicator information of each motor from the normal value of the corresponding technical indicator to obtain a corresponding difference sequence;

[0013] S33, using all the difference sequences, construct a difference matrix;

[0014] S34, calculating and obtaining the rank value and the first singular value set of the difference matrix; the first singular value set includes all the singular values ​​of the difference matrix;

[0015] S35, performing cross-correlation calculation processing on the difference matrix to obtain a cross-correlation matrix;

[0016] S36, performing eigenvalue calculation processing on the mutual correlation matrix to obtain a first eigenvalue set; the first eigenvalue set includes all eigenvalues ​​of the mutual correlation matrix;

[0017] S37, performing quantitative evaluation calculation on the rank value, the first singular value set, and the first eigenvalue set to obtain corresponding state evaluation values.

[0018] The expression for the quantitative evaluation calculation is:

[0019]

[0020] Among them, P is the rank value, γ max and γ0 represent the maximum and mean values ​​of all elements of the first singular value set, respectively, max and φ0 represent the maximum value and mean value of all elements of the first eigenvalue set respectively, and τ is the state evaluation value.

[0021] The balancing control processing is performed on the motor target speed, the total input power value, the state evaluation values ​​of all motors, and the work index information subset to obtain the balanced input power value of each motor, including:

[0022] S41, performing a difference calculation process on the data sequence of the rotation speed of each motor and the target rotation speed of the motor, to obtain a rotation speed difference value of each motor;

[0023] S42, calculating a speed influence factor for each motor's operating indicator information subset and corresponding speed difference value to obtain a speed influence factor for each motor;

[0024] S43, performing proportional factor calculation processing on the data sequence of the speed influence factor, speed difference value, and speed index of each motor to obtain the proportional factor of each motor;

[0025] S44, performing normalization calculation on the scale factors of all motors to obtain a normalized scale factor of each motor;

[0026] S45 , multiplying the normalized proportional factor of each motor by the total input power value to obtain a balanced input power value of each motor.

[0027] The expression for the difference calculation process is:

[0028]

[0029] in, The i-th element of the data sequence representing the motor speed, represents the target speed of the motor, m represents the length of the data sequence, AQ represents the first difference factor, and XY represents the speed difference value of the motor.

[0030] The speed impact factor calculation is performed on the subset of the working index information of each motor and the corresponding speed difference value to obtain the speed impact factor of each motor, including:

[0031] S421, obtaining normal values ​​of each type of technical indicators of the motor;

[0032] S422, constructing a first data sequence set for each motor using the data sequences of all other technical indicators of the working indicator information subset of each motor excluding the rotational speed;

[0033] S423, using the first data sequence set of each motor, subtracting the normal value of the corresponding technical indicator from each motor to obtain a corresponding first difference sequence;

[0034] S424, constructing a first difference matrix using all first difference sequences;

[0035] S425, calculating the corresponding complex correlation coefficient for each first difference sequence in the first difference matrix;

[0036] S426 , performing fusion calculation processing on the complex correlation coefficients of all first difference sequences of the first difference matrix to obtain a speed influencing factor of the motor.

[0037] The scaling factor calculation process is performed on the data sequence of the speed influence factor, the speed difference value, and the speed index of each motor to obtain the scaling factor of each motor, including:

[0038] Performing a first factor calculation process on the data sequence of the speed influencing factor and the speed index of each motor to obtain a first factor value;

[0039] A proportional calculation is performed on the first factor value and the speed difference value to obtain a proportional factor of the motor.

[0040] According to a second aspect of the present invention, a multi-motor balancing control device for automatically and quickly deploying and retracting a tent is disclosed, the device comprising:

[0041] a memory storing executable program code;

[0042] a processor coupled to the memory;

[0043] The processor calls the executable program code stored in the memory to execute the multi-motor balancing control method for automatically and quickly deploying and retracting a tent.

[0044] According to a third aspect of the present invention, a computer-storable medium is disclosed, wherein the computer-storable medium stores computer instructions. When the computer instructions are called by a computer, the computer instructions are used to execute the multi-motor balancing control method for automatically and quickly deploying and retracting a tent.

[0045] According to a fourth aspect of the present invention, an information data processing terminal is disclosed. The information data processing terminal is used to implement the multi-motor balanced control method for automatically and quickly deploying and retracting a tent.

[0046] The beneficial effects of the present invention are:

[0047] The multi-motor balancing control method for automatically and quickly deploying and retracting a tent of the present invention collects a set of working index information of the motor group and combines the motor target speed and total input power value to accurately evaluate and dynamically balance the working status of each motor.

[0048] The present invention can monitor the operating status of the motor in real time and accurately identify motors with abnormal loads through quantitative evaluation and calculation of a subset of motor working index information, providing a scientific basis for subsequent balancing control. Based on the calculation of the speed difference value and the proportional factor, dynamic adjustment of the input power of each motor is achieved to ensure that the motor can maintain a reasonable load distribution in different working stages. By multiplying the normalized proportional factor and the total input power value, the balanced input power value of each motor is obtained, thereby realizing the coordinated operation of multiple motors and improving the efficiency and stability of the tent unfolding and folding. In addition, the present invention can also effectively extend the service life of the motor, reduce the maintenance cost of the system, and has significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 4 is an implementation flow chart of the method of the present invention. DETAILED DESCRIPTION

[0050] In order to better understand the content of the present invention, an embodiment is given here.

[0051] Figure 1 4 is an implementation flow chart of the method of the present invention.

[0052] In a first aspect, an embodiment of the present invention discloses a multi-motor balanced control method for automatically and quickly deploying and retracting a tent, comprising:

[0053] S1, collecting a set of working indicator information of a motor group for automatically and quickly deploying and retracting a tent; the working indicator information set includes a subset of working indicator information of each motor; the working indicator information subset includes a data sequence of each type of technical indicator of the motor; the data sequence is a sequence of sampled values ​​of the technical indicators collected at each discrete moment;

[0054] S2, obtain the motor target speed and total input power value;

[0055] S3, performing working status evaluation processing on the working indicator information subset of each motor to obtain a corresponding status evaluation value;

[0056] S4, performing a balancing control process on the motor target speed, the total input power value, the state evaluation values ​​of all motors, and the work index information subset to obtain a balanced input power value for each motor;

[0057] S5, inputting the balanced input power value of each motor to the corresponding motor to complete the balanced control of the multiple motors for automatically and quickly deploying and retracting the tent;

[0058] The working status evaluation process is performed on the working indicator information subset of each motor to obtain a corresponding status evaluation value, including:

[0059] S31, obtaining normal values ​​of each type of technical indicators of the motor;

[0060] S32, subtracting the data sequence of each type of technical indicator in the subset of working indicator information of each motor from the normal value of the corresponding technical indicator to obtain a corresponding difference sequence;

[0061] S33, using all the difference sequences, construct a difference matrix;

[0062] S34, calculating and obtaining the rank value and the first singular value set of the difference matrix; the first singular value set includes all the singular values ​​of the difference matrix;

[0063] S35, performing cross-correlation calculation processing on the difference matrix to obtain a cross-correlation matrix;

[0064] S36, performing eigenvalue calculation processing on the mutual correlation matrix to obtain a first eigenvalue set; the first eigenvalue set includes all eigenvalues ​​of the mutual correlation matrix;

[0065] The element in the i-th row and j-th column of the cross-correlation matrix is ​​the cross-correlation calculation result between the i-th row vector and the j-th row vector of the difference matrix. The cross-correlation calculation process is to perform cross-correlation calculation on the row vectors of the difference matrix.

[0066] S37, performing quantitative evaluation calculation on the rank value, the first singular value set, and the first eigenvalue set to obtain a corresponding state evaluation value;

[0067] The expression for the quantitative evaluation calculation is:

[0068]

[0069] Among them, P is the rank value, γ max and γ0 represent the maximum and mean values ​​of all elements of the first singular value set, respectively, max and φ0 represent the maximum value and mean value of all elements of the first eigenvalue set respectively, and τ is the state evaluation value.

[0070] The balancing control processing is performed on the motor target speed, the total input power value, the state evaluation values ​​of all motors, and the work index information subset to obtain the balanced input power value of each motor, including:

[0071] S41, performing a difference calculation process on the data sequence of the rotation speed of each motor and the target rotation speed of the motor, to obtain a rotation speed difference value of each motor;

[0072] S42, calculating a speed influence factor for each motor's operating indicator information subset and corresponding speed difference value to obtain a speed influence factor for each motor;

[0073] S43, performing proportional factor calculation processing on the data sequence of the speed influence factor, speed difference value, and speed index of each motor to obtain the proportional factor of each motor;

[0074] S44, performing normalization calculation on the scale factors of all motors to obtain a normalized scale factor of each motor;

[0075] S45, multiplying the normalized proportional factor of each motor by the total input power value to obtain a balanced input power value of each motor;

[0076] The expression for the difference calculation process is:

[0077]

[0078] in, The i-th element of the data sequence representing the motor speed, represents the target speed of the motor, m represents the length of the data sequence, AQ represents the first difference factor, and XY represents the speed difference value of the motor;

[0079] The speed impact factor calculation is performed on the subset of the working index information of each motor and the corresponding speed difference value to obtain the speed impact factor of each motor, including:

[0080] S421, obtaining normal values ​​of each type of technical indicators of the motor;

[0081] S422, constructing a first data sequence set for each motor using the data sequences of all other technical indicators of the working indicator information subset of each motor excluding the rotational speed;

[0082] S423, using the first data sequence set of each motor, subtracting the normal value of the corresponding technical indicator from each motor to obtain a corresponding first difference sequence;

[0083] S424, constructing a first difference matrix using all first difference sequences;

[0084] S425, calculating the corresponding complex correlation coefficient for each first difference sequence in the first difference matrix;

[0085] S426, performing a fusion calculation process on the complex correlation coefficients of all first difference sequences of the first difference matrix to obtain a speed influencing factor of the motor;

[0086] Subtracting each data sequence of the first data sequence set of each motor from the normal value of the corresponding technical indicator is to subtract each element in the data sequence from the normal value of the corresponding technical indicator to obtain the corresponding first difference sequence;

[0087] The expression of the fusion calculation is:

[0088]

[0089] Where G is the motor speed influencing factor, t0 is the mean of the complex correlation coefficients of all first difference sequences, and N! represents the factorial of N.

[0090] The calculation expression of the complex correlation coefficient is:

[0091]

[0092] Where N is the number of first difference sequences, t irepresents the complex correlation coefficient of the first difference sequence of the i-th order, t1=1, r ij is the mutual correlation coefficient between the i-th first difference sequence and the j-th first difference sequence, r i2,1 is the first-order partial correlation coefficient of the first difference sequence of the i-th order, and so on, r i3,12 is the secondary partial correlation coefficient of the ith first difference sequence, r iN,1234…(N-1) is the N-1 level partial correlation coefficient of the i-th first difference sequence;

[0093] The calculation expression for the partial correlation coefficient at each level is:

[0094]

[0095] The calculation of other partial correlation coefficients is similar.

[0096] The scaling factor calculation process is performed on the data sequence of the speed influence factor, the speed difference value, and the speed index of each motor to obtain the scaling factor of each motor, including:

[0097] Performing a first factor calculation process on the data sequence of the speed influencing factor and the speed index of each motor to obtain a first factor value;

[0098] A proportional calculation is performed on the first factor value and the speed difference value to obtain a proportional factor of the motor.

[0099] The expression for calculating the first factor is:

[0100]

[0101] Among them, hq is the first factor value, q k is the kth element of the data sequence of the speed index, m is the length of the data sequence of the speed index, and G is the speed influencing factor;

[0102] The expression for the ratio calculation is:

[0103]

[0104] Where gv is the scale factor of the motor.

[0105] The technical indicators of the motor, including speed, output power, operating current, operating temperature, and inverter output voltage;

[0106] Each motor of the motor group is used to control the retraction and expansion of each bracket of the automatic rapid tent expansion and contraction;

[0107] The working index information set can be measured by sensors installed on the motor group;

[0108] The motor target speed and total input power value can be obtained by setting;

[0109] According to a second aspect of the present invention, a multi-motor balancing control device for automatically and quickly deploying and retracting a tent is disclosed, the device comprising:

[0110] a memory storing executable program code;

[0111] a processor coupled to the memory;

[0112] The processor calls the executable program code stored in the memory to execute the multi-motor balancing control method for automatically and quickly deploying and retracting a tent.

[0113] According to a third aspect of the present invention, a computer-storable medium is disclosed, wherein the computer-storable medium stores computer instructions. When the computer instructions are called by a computer, the computer instructions are used to execute the multi-motor balancing control method for automatically and quickly deploying and retracting a tent.

[0114] According to a fourth aspect of the present invention, an information data processing terminal is disclosed. The information data processing terminal is used to implement the multi-motor balanced control method for automatically and quickly deploying and retracting a tent.

[0115] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A multi-motor balanced control method for automatically and quickly deploying and retracting a tent, characterized in that: include: S1, collecting a set of working indicator information of a motor group for automatically and quickly deploying and retracting a tent; the working indicator information set includes a subset of working indicator information of each motor; the working indicator information subset includes a data sequence of each type of technical indicator of the motor; the data sequence is a sequence of sampled values ​​of the technical indicators collected at each discrete moment; S2, obtain the motor target speed and total input power value; S3, performing working status evaluation processing on the working indicator information subset of each motor to obtain a corresponding status evaluation value; S4, performing a balancing control process on the motor target speed, the total input power value, and the subset of working index information of all motors to obtain a balanced input power value for each motor; The balancing control processing is performed on the motor target speed, the total input power value, the state evaluation values ​​of all motors, and the work index information subset to obtain the balanced input power value of each motor, including: S41, performing a difference calculation process on the data sequence of the rotation speed of each motor and the target rotation speed of the motor, to obtain a rotation speed difference value of each motor; S42, calculating a speed influence factor for each motor's operating indicator information subset and corresponding speed difference value to obtain a speed influence factor for each motor; S43, performing proportional factor calculation processing on the data sequence of the speed influence factor, speed difference value, and speed index of each motor to obtain the proportional factor of each motor; S44, performing normalization calculation on the scale factors of all motors to obtain a normalized scale factor of each motor; S45, multiplying the normalized proportional factor of each motor by the total input power value to obtain a balanced input power value of each motor; S5, inputting the balanced input power value of each motor to the corresponding motor, thereby completing the balanced control of the multiple motors for automatically and quickly deploying and retracting the tent.

2. The multi-motor balanced control method for automatically and quickly deploying and retracting a tent according to claim 1, characterized in that: The working status evaluation process is performed on the working indicator information subset of each motor to obtain a corresponding status evaluation value, including: S31, obtaining normal values ​​of each type of technical indicators of the motor; S32, subtracting the data sequence of each type of technical indicator in the subset of working indicator information of each motor from the normal value of the corresponding technical indicator to obtain a corresponding difference sequence; S33, using all the difference sequences, construct a difference matrix; S34, calculating and obtaining the rank value and the first singular value set of the difference matrix; the first singular value set includes all the singular values ​​of the difference matrix; S35, performing cross-correlation calculation processing on the difference matrix to obtain a cross-correlation matrix; S36, performing eigenvalue calculation processing on the mutual correlation matrix to obtain a first eigenvalue set; the first eigenvalue set includes all eigenvalues ​​of the mutual correlation matrix; S37, performing quantitative evaluation calculation on the rank value, the first singular value set, and the first eigenvalue set to obtain corresponding state evaluation values.

3. The multi-motor balanced control method for automatically and quickly deploying and retracting a tent according to claim 2, characterized in that: The expression for the quantitative evaluation calculation is: Among them, P is the rank value, γ max and γ0 represent the maximum and mean values ​​of all elements of the first singular value set, respectively, max and φ0 represent the maximum value and mean value of all elements of the first eigenvalue set respectively, and τ is the state evaluation value.

4. The multi-motor balanced control method for automatically and quickly deploying and retracting a tent according to claim 1, characterized in that: The expression for the difference calculation process is: in, The i-th element of the data sequence representing the motor speed, represents the target speed of the motor, m represents the length of the data sequence, AQ represents the first difference factor, and XY represents the speed difference value of the motor.

5. The multi-motor balanced control method for automatically and quickly deploying and retracting a tent according to claim 1, characterized in that: The speed impact factor calculation is performed on the subset of the working index information of each motor and the corresponding speed difference value to obtain the speed impact factor of each motor, including: S421, obtaining normal values ​​of each type of technical indicators of the motor; S422, constructing a first data sequence set for each motor using the data sequences of all other technical indicators of the working indicator information subset of each motor excluding the rotational speed; S423, using the first data sequence set of each motor, subtracting the normal value of the corresponding technical indicator from each motor to obtain a corresponding first difference sequence; S424, constructing a first difference matrix using all first difference sequences; S425, calculating the corresponding complex correlation coefficient for each first difference sequence in the first difference matrix; S426 , performing fusion calculation processing on the complex correlation coefficients of all first difference sequences of the first difference matrix to obtain a speed influencing factor of the motor.

6. The multi-motor balanced control method for automatically and quickly deploying and retracting a tent according to claim 1, characterized in that: The scaling factor calculation process is performed on the data sequence of the speed influence factor, the speed difference value, and the speed index of each motor to obtain the scaling factor of each motor, including: Performing a first factor calculation process on the data sequence of the speed influencing factor and the speed index of each motor to obtain a first factor value; A proportional calculation is performed on the first factor value and the speed difference value to obtain a proportional factor of the motor.

7. A multi-motor balancing control device for automatically and quickly deploying and retracting a tent, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the multi-motor balancing control method for automatically and quickly deploying and retracting a tent according to any one of claims 1 to 6.

8. A computer storable medium, characterized in that The computer storable medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the multi-motor balancing control method for automatically and quickly deploying and retracting a tent according to any one of claims 1 to 6.

9. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the multi-motor balanced control method for automatically and quickly deploying and retracting a tent according to any one of claims 1 to 6.

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