CN114896731B - Kinetic parameter identification method of mechanical transmission system and related device - Google Patents
Kinetic parameter identification method of mechanical transmission system and related device Download PDFInfo
- Publication number
- CN114896731B CN114896731B CN202210552661.XA CN202210552661A CN114896731B CN 114896731 B CN114896731 B CN 114896731B CN 202210552661 A CN202210552661 A CN 202210552661A CN 114896731 B CN114896731 B CN 114896731B
- Authority
- CN
- China
- Prior art keywords
- rotating part
- rotation
- identification result
- dynamic model
- mechanical transmission
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000009347 mechanical transmission Effects 0.000 title claims abstract description 85
- 238000000034 method Methods 0.000 title claims abstract description 73
- 230000005484 gravity Effects 0.000 claims abstract description 19
- 230000033001 locomotion Effects 0.000 claims description 84
- 230000001133 acceleration Effects 0.000 claims description 45
- 230000005284 excitation Effects 0.000 claims description 28
- 238000012545 processing Methods 0.000 claims description 26
- 238000001914 filtration Methods 0.000 claims description 15
- 238000012935 Averaging Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 5
- 238000012795 verification Methods 0.000 claims description 5
- 238000003860 storage Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 20
- 238000010586 diagram Methods 0.000 description 6
- 230000000737 periodic effect Effects 0.000 description 5
- 238000005070 sampling Methods 0.000 description 5
- 125000004122 cyclic group Chemical group 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computational Mathematics (AREA)
- Feedback Control In General (AREA)
Abstract
The embodiment of the application relates to the technical field of mechanical transmission systems, and provides a method and a related device for identifying kinetic parameters of a mechanical transmission system. In other words, in the process of establishing the dynamic model, the influence of the inertia quantity, the centrifugal force, the Coriolis force, the gravity and the friction force on the rotating part is comprehensively considered, so that the model is established more comprehensively, and the dynamic parameters in the dynamic model can be accurately identified, so that the aim of improving the torque compensation control precision of the whole mechanical transmission system in the later period is fulfilled.
Description
Technical Field
The embodiment of the application relates to the technical field of mechanical transmission systems, in particular to a method and a related device for identifying dynamic parameters of a mechanical transmission system.
Background
Mechanical transmission systems have the advantages of large load, fast response, high precision, etc., are generally used for replacing human beings to perform repetitive, heavy or dangerous tasks, and are widely applied to various fields of industrial manufacturing.
With the increasing demands on the speed and precision of mechanical transmission systems, the demands on the performance control and precision control of mechanical transmission systems are also increasing. Generally, a dynamic model established based on a mechanical transmission system can realize control of the mechanical transmission system, so that establishment of the dynamic model is the basis for control of the mechanical transmission system, and the more accurate the dynamic parameters in the dynamic model are, the higher the control accuracy of the mechanical transmission system is.
Therefore, how to accurately identify the kinetic parameters in the kinetic model is a technical problem to be solved urgently at present.
Disclosure of Invention
An object of the present invention is to provide a method and a related apparatus for identifying dynamic parameters of a mechanical transmission system, so as to accurately identify dynamic parameters in a dynamic model.
In order to achieve the above purpose, the embodiments of the present application employ the following technical solutions:
in a first aspect, an embodiment of the present application provides a method for identifying a kinetic parameter of a mechanical transmission system, where the method includes:
establishing a dynamic model of each rotating part of the mechanical transmission system; wherein the dynamic model is used for representing the influence of inertia, centrifugal force and Coriolis force, gravity and friction on the rotating part;
aiming at each rotating part, controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track, and acquiring motion data of the rotating part according to a preset time interval in each movement to obtain a plurality of groups of motion data; wherein one acquisition point corresponds to a set of motion data;
processing each group of motion data respectively to remove noise and obtain a plurality of target data; wherein, one acquisition point corresponds to one target data;
and performing parameter identification on the dynamic model of the rotating part according to the target data to obtain an identification result of each dynamic parameter in the dynamic model.
Optionally, the kinetic model is:
wherein τ represents a moment of the rotating portion,represents the inertia of the rotating part and/or the device>Represents the centrifugal force and the Coriolis force of the rotating part, G (q) represents the gravity term compensation of the rotating part, and/or the compensation of the gravity term of the rotating part>Represents the friction force of the rotating part, q represents the rotating angle position of the rotating part, and/or>Represents the angular speed of rotation of the rotating part, and/or the position of the rotating part>Representing a rotational angular acceleration of the rotating part;
the friction in the dynamic model is solved according to the following formula:
wherein,represents the friction of the rotating part and/or the pressure of the rotating part>Representing the motor shaft speed of rotation of said rotating part, i representing the number of terms of a polynomial, p i+1 Representing the coefficients of the terms.
Optionally, the motion data includes an actual rotation angle position and an actual rotation moment of the rotation part;
the step of processing each group of motion data to remove noise and obtain a plurality of target data includes:
averaging the actual rotation angle position and the actual rotation moment in each group of motion data respectively to obtain a plurality of average rotation angle positions and a plurality of average rotation moments, wherein one acquisition point corresponds to one average rotation angle position and one average rotation moment;
filtering the average rotation angle positions and the average rotation moments to remove noise, and obtaining a plurality of rotation angle positions and actual moments, wherein one acquisition point corresponds to one rotation angle position and one actual moment;
solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position by adopting a normal differential difference method;
and obtaining the plurality of target data, wherein the target data comprises actual torque, a rotation angle position, a rotation angular speed and a rotation angular acceleration.
Optionally, the step of solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position by using a ordinary differential difference method includes:
using a second order central difference method, according to the formula
And
solving the rotation angular speed and the rotation angular acceleration corresponding to each rotation angular position;
wherein q represents the rotational angle position,represents the angular speed of rotation, is greater or less>Representing the angular acceleration of rotation, i representing the sequence of data, and t representing the preset time interval during which the angular position of rotation is recorded.
Optionally, one of the target data includes an actual moment, a rotation angle position, a rotation angular velocity, and a rotation angular acceleration corresponding to one of the acquisition points;
the step of performing parameter identification on the dynamic model according to the target data to obtain the identification result of each dynamic parameter in the dynamic model includes:
and respectively substituting the actual moment, the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the dynamic model, and calculating the identification result of each dynamic parameter in the dynamic model.
Optionally, the method further comprises:
verifying the identification result of each kinetic parameter in the kinetic model to determine whether the identification result is the optimal identification result;
if the identification result is the optimal identification result, substituting the optimal identification result into the kinetic model to obtain an ideal kinetic model of the rotating part;
and if the identification result is not the optimal identification result, returning to execute the step of controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track and collecting the motion data of the rotating part at each movement according to a preset time interval to obtain a plurality of groups of motion data aiming at each rotating part until the identification result is the optimal identification result to obtain an ideal dynamic model of the rotating part.
Optionally, one of the target data includes an actual moment, a rotation angle position, a rotation angular velocity, and a rotation angular acceleration corresponding to one of the acquisition points;
the step of verifying the recognition result of each kinetic parameter in the kinetic model to determine whether the recognition result is the best recognition result comprises:
updating the dynamic model to a target dynamic model based on the identification result of each dynamic parameter in the dynamic model;
respectively substituting the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the target dynamic model to obtain a theoretical moment corresponding to each acquisition point;
generating a theoretical moment curve according to the theoretical moment corresponding to each acquisition point, and generating an actual moment curve according to the actual moment corresponding to each acquisition point;
comparing the theoretical moment curve with the actual moment curve to determine whether the identification result is the optimal identification result;
if the contact ratio of the theoretical moment curve and the actual moment curve meets a set condition, determining the identification result as an optimal identification result;
and if the coincidence degree of the theoretical moment curve and the actual moment curve does not meet the set condition, determining that the identification result is not the optimal identification result.
In a second aspect, an embodiment of the present application further provides a device for identifying a dynamic parameter of a mechanical transmission system, where the device includes:
the model establishing module is used for establishing a dynamic model of each rotating part of the mechanical transmission system; wherein the dynamic model is used for representing the influence of inertia, centrifugal force and Coriolis force, gravity and friction on the rotating part;
the control module is used for controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track aiming at each rotating part, and acquiring the motion data of the rotating part according to a preset time interval in each movement to obtain a plurality of groups of motion data; wherein one acquisition point corresponds to a group of motion data;
the processing module is used for respectively processing each group of motion data to remove noise and obtain a plurality of target data; wherein, one acquisition point corresponds to one target data;
and the parameter identification module is used for carrying out parameter identification on the dynamic model of the rotating part according to the plurality of target data to obtain an identification result of each dynamic parameter in the dynamic model.
In a third aspect, an embodiment of the present application further provides an electronic device, including a processor and a memory, where the memory is used to store a program, and the processor is used to implement the method for identifying the dynamic parameter of the mechanical transmission system in the first aspect when executing the program.
In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for identifying a dynamic parameter of a mechanical transmission system in the first aspect.
Compared with the prior art, the method and the related device for identifying the kinetic parameters of the mechanical transmission system provided by the embodiment of the application comprise the steps of firstly, establishing a kinetic model of each rotating part of the mechanical transmission system; then, aiming at each rotating part, controlling a mechanical transmission system to move repeatedly according to a pre-designed excitation track, and acquiring motion data of the rotating part according to a preset time interval in each movement, wherein one acquisition point corresponds to one group of motion data; then, each group of motion data is respectively processed to remove noise, and target data corresponding to each acquisition point is obtained; and finally, performing parameter identification on the dynamic model according to the target data corresponding to each acquisition point to obtain an identification result of each dynamic parameter. In other words, in the process of establishing the dynamic model, the influence of the inertia, the centrifugal force, the coriolis force, the gravity and the friction on the rotating part is comprehensively considered, so that the establishment of the dynamic model is relatively comprehensive, the dynamic parameters in the dynamic model can be accurately identified, and the aim of improving the torque compensation control precision of the whole mechanical transmission system in the later period is fulfilled.
Drawings
Fig. 1 illustrates an application scenario diagram of a method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present application.
Fig. 2 is a first flowchart illustrating a first method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present disclosure.
Fig. 3 shows an example of a rotation portion provided in an embodiment of the present application.
Fig. 4 is a diagram illustrating an example of the rotation portion moving according to the excitation trace provided by the embodiment of the application.
Fig. 5 is a flowchart illustrating a second method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present disclosure.
Fig. 6 shows a third flowchart of a method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present disclosure.
Fig. 7 shows a fourth flowchart of a method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present application.
FIG. 8 is a block diagram illustrating an apparatus for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present disclosure.
Fig. 9 shows a block schematic diagram of an electronic device provided in an embodiment of the present application.
Icon: 100-a dynamic parameter identification device of the mechanical transmission system; 101-a model building module; 102-a control module; 103-a processing module; 104-parameter identification module; 105-a parameter verification module; 10-an electronic device; 11-a processor; 12-a memory; 13-bus.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a schematic view illustrating an application scenario of a method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present disclosure. As shown in fig. 1, the device comprises a mechanical transmission system and an electronic device, wherein the mechanical transmission system and the electronic device are connected through a signal line to realize communication and data transmission between the mechanical transmission system and the electronic device.
The mechanical transmission system comprises a plurality of rotating parts, and the embodiment of the application aims to establish a corresponding dynamic model for each rotating part and accurately identify dynamic parameters in each dynamic model. Meanwhile, each rotating part is provided with a motor, and the motor is used for driving the rotating part to move.
In the present embodiment, the mechanical transmission system may be, but is not limited to, a robot, an automobile, and the like. Correspondingly, the rotating part of the mechanical transmission system can be a joint part of the robot, and can also be wheels of an automobile and the like. The embodiment of the present application does not set any limit to this.
In addition, each rotating part of the mechanical transmission system can be provided with a data acquisition module. Taking a rotating part as an example, in the moving process of the rotating part, the data acquisition module is used for acquiring the rotating angle position and the torque of the rotating part and transmitting the rotating angle position and the torque to the electronic equipment through a signal line.
The electronic equipment is used for receiving the data sent by the data acquisition module and processing the data so as to accurately identify the kinetic parameters in the kinetic model. Meanwhile, the electronic equipment is also used for controlling each rotating part of the mechanical transmission system to move. The electronic device may be, but is not limited to, an upper computer, a personal computer, an industrial personal computer, and the like, and the following embodiments are described by taking the upper computer as an example.
Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a method for identifying a dynamic parameter of a mechanical transmission system according to an embodiment of the present disclosure. The method for identifying the dynamic parameters of the mechanical transmission system is applied to electronic equipment and can comprise the following steps:
s101, establishing a dynamic model of each rotating part of the mechanical transmission system; the dynamic model is used for representing the influence of inertia quantity, centrifugal force, coriolis force, gravity and friction force on a rotating part.
In this embodiment, the mechanical transmission system includes a plurality of rotating portions, and taking a rotating portion as an example, the process of identifying the kinetic parameters in the kinetic model may include: establishing a dynamic model, linearizing the model and acquiring a minimum parameter set, designing and optimizing an excitation track, acquiring and processing data, identifying parameters and verifying the parameters.
In the prior art, the established dynamic model is generally a model containing inertia, centrifugal force, coriolis force and gravity, and can be expressed as:
wherein, tau represents a moment of force,represents an inertia quantity>Representing centrifugal and coriolis forces, G (q) representing gravity term compensation; q denotes the angle of rotation position>Represents the angular speed of rotation, is selected>Indicating the rotational angular acceleration.
From the above equations, the existing dynamic model can represent the basic stress condition of the key part (i.e. the rotation part) of the mechanical transmission system, for example, the basic stress condition of each joint part of the robot.
However, the conventional dynamic model does not consider the influence of the friction force of the rotating part in the mechanical transmission system, but the friction force has a large influence on the moment when the mechanical transmission system operates at a low speed, and if the influence of the friction force is not considered, the control accuracy of the mechanical transmission system is influenced to a certain extent. Therefore, the existing dynamic model cannot accurately control the mechanical transmission system.
In order to solve the technical problem, in the embodiment of the application, when a dynamic model is established, besides the influence of inertia quantity, centrifugal force, coriolis force and gravity on a rotating part, the influence of friction force on the rotating part is also considered.
Namely, when a dynamic model is established, the friction force of a rotating part is introduced, and the finally established dynamic model is as follows:
wherein, tau represents the moment of the rotating part,represents the inertia of the rotating part>Represents the centrifugal force and the Coriolis force of the rotating part, G (q) represents the gravity term compensation of the rotating part, and/or the term compensation of the gravity of the rotating part>Represents the friction force of the rotating part, q represents the rotating angle position of the rotating part, and>indicating the angular speed of rotation of the rotating part>Indicating the angular acceleration of rotation of the rotating part. />
In the present embodiment, the frictional forceCan be varied, e.g., only linear friction, both linear and non-linear friction, etc., are considered, while the friction force->May include coulomb friction, viscous friction, static friction, and the like.
Generally, the frictional force is establishedThe more factors involved in the model, the more accurate the calculation of the friction. The more accurate the calculation result of the friction force is, the more accurate the compensation torque in the control process is, and the higher the control precision is. However, if the complexity of the model is too high, the more computing resources are occupied, the longer the computing time is, a delay phenomenon occurs to a transmission system which needs real-time high-precision control, and control inaccuracy is caused on the contrary, that is, the practicability of the too complex model is not high.
In order to balance the relationship between accuracy and practicality while fully considering the characteristics of the frictional force in the low speed region, in the embodiment of the present application, the frictional force in the dynamic model is designed as follows:
wherein,represents the friction force of the rotating part>Representing the motor shaft speed at the location of rotation, i representing the number of terms of a polynomial, p i+1 Representing the coefficients of the terms.
In this embodiment, after the dynamic model with the friction force model is established for each rotation position, the dynamic model may be linearized, so as to obtain a minimum parameter set of the dynamic model. Alternatively, the number of kinetic parameters of the kinetic model may be reduced using Python language, resulting in a minimum set of parameters.
S102, aiming at each rotating part, controlling a mechanical transmission system to move repeatedly according to a pre-designed excitation track, and acquiring motion data of the rotating part according to a preset time interval in each movement to obtain a plurality of groups of motion data; wherein one acquisition point corresponds to a set of motion data.
In the present embodiment, it is also necessary to design an excitation locus for each rotation portion. For example, referring to fig. 3, excitation tracks are designed for the rotation portion 1 and the rotation portion 2, respectively, and the excitation tracks of the rotation portion 1 and the rotation portion 2 are shown by dotted lines in the figure. And then, controlling the mechanical transmission system to track the designed excitation track, and then acquiring the driving torque of each rotating part of the mechanical transmission system and the position of a driving motor, namely the torque and the rotating angle position of each rotating part.
In order to reduce the influence of the excitation trajectory, the excitation trajectory is designed to be periodic and optimized according to a set optimization principle. Taking a rotating portion as an example, the optimization principle of the excitation trajectory of the rotating portion may include, but is not limited to, a maximum angle that the rotating portion can move, a maximum motor shaft rotation speed of the rotating portion, and the like, and the embodiment of the present application does not limit this.
Meanwhile, in order to make the process of the rotation part moving according to the excitation track smoother, the excitation track is designed to be periodic, and the excitation track is also designed to be in a Fourier series form. That is, the excitation trajectory may be a fourier series trajectory having periodicity.
In this embodiment, after designing a corresponding excitation trajectory for each rotational position, each rotational position of the mechanical transmission system is controlled to perform a periodic motion according to the respective excitation trajectory. For example, taking the rotating portion 2 in fig. 3 as an example, referring to fig. 4, the rotating portion 2 performs a periodic motion according to the corresponding excitation trajectory (i.e., a-B-a-C-a).
And, in each movement, the movement data of the rotating part is collected according to a preset time interval (for example, 2 s) to obtain a plurality of groups of movement data, and one collection point corresponds to one group of movement data. For example, referring to fig. 4, while the rotating portion 2 is moving according to a-B-a-C-a, the movement data of the rotating portion 2 is acquired every 2 seconds, and the movement data of each acquisition point is obtained. Meanwhile, since the rotating portion 2 is periodically moved according to a-B-a-C-a, the motion data of each acquisition point is a group, for example, the motion data of one acquisition point has 100 times of periodic movement.
In the present embodiment, the motion data includes an actual rotational angular position of the rotational section and an actual rotational moment, where the actual rotational angular position is determined with respect to a reference position of the rotational section, for example, where the reference position of the rotational section 2 in fig. 4 is a, the actual rotational angular position of each acquisition point is determined with respect to the reference position a.
S103, processing each group of motion data respectively to remove noise and obtain a plurality of target data; wherein one acquisition point corresponds to one target data.
In this embodiment, taking a rotating portion as an example, after a set of motion data of each sampling point of the rotating portion is obtained, each set of motion data is processed to remove noise, and a target data of each sampling point is obtained.
In order to eliminate the influence of noise in the acquired motion data, taking a group of motion data as an example, it is necessary to average the group of motion data first, and then filter the averaged motion data. Meanwhile, in the filtering process, the improved filtering method is adopted for filtering processing, so that the characteristic of data can be better kept on the premise of removing noise.
Referring to fig. 5, the step S103 may include steps S1031 to S1034, in which each set of motion data is processed to remove noise, respectively, so as to obtain a plurality of target data.
And S1031, averaging the actual rotation angle positions and the actual rotation moments in each group of motion data respectively to obtain a plurality of average rotation angle positions and a plurality of average rotation moments, wherein one acquisition point corresponds to one average rotation angle position and one average rotation moment.
In this embodiment, taking a rotation position as an example, for the actual rotation angle position and the actual rotation moment in each set of motion data, averaging may be performed in a weighted average manner, so as to filter noise, and obtain an average rotation angle position and an average rotation moment of each acquisition point.
S1032, filtering the average rotation angle positions and the average rotation moments respectively to remove noise, and obtaining a plurality of rotation angle positions and actual moments, wherein one acquisition point corresponds to one rotation angle position and one actual moment.
In this embodiment, taking a rotating portion as an example, an average rotation angle position and an average rotation moment of each acquisition point are obtained, and filtering processing may be performed on a plurality of average rotation angle positions and a plurality of average rotation moments respectively to remove noise. In the data filtering process, firstly, a weighting coefficient can be obtained by Butterworth according to a pass band of the mechanical transmission system (namely, a bandwidth of the motor in the mechanical transmission system to work); then, the plurality of average rotational angle positions and the plurality of average rotational moments are subjected to cyclic weighting processing for a plurality of times, respectively. Butterworth can effectively remove noise and maintain an effective signal, so that the noise removal can be performed on data in a lower order, and meanwhile, the fidelity effect of the data is improved through multiple times of cyclic processing.
And S1033, solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position by adopting a normal differential difference method.
In this embodiment, taking a rotating portion as an example, after averaging and filtering a set of motion data of each acquisition point to obtain a rotation angle position and an actual moment corresponding to each acquisition point, a difference method may be used to obtain a speed and an acceleration at each rotation angle position (i.e., each position) of the rotating portion to obtain a rotation angular speed and a rotation angular acceleration corresponding to each rotation angle position.
Optionally, a second-order center difference method may be used to solve the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position, and in the process of solving by using the second-order center difference method, three consecutive data need to be used, and the solving process is as follows:
using a second order central difference method, according to the formula
And
solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position;
wherein q represents a rotation angleThe position of the mobile phone is determined,represents the angular speed of rotation, is selected>Indicating the rotational angular acceleration, i indicating the sequence of data, and t indicating a preset time interval for recording the rotational angular position.
It should be noted that, when the ordinary differential difference method is used to solve the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position, a fourth-order center difference method may be used in addition to the second-order center difference method, and the calculation process is similar to that of the second-order center difference method, and is not described herein again.
S1034, a plurality of target data is obtained, the target data including an actual moment, a rotation angle position, a rotation angular velocity, and a rotation angular acceleration.
In this embodiment, taking a rotation portion as an example, through the processes of S1031 to S1033, target data corresponding to each sampling point of the rotation portion can be obtained, and the target data may include an actual moment, a rotation angle position, a rotation angle velocity, and a rotation angle acceleration.
And S104, performing parameter identification on the dynamic model of the rotating part according to the plurality of target data to obtain an identification result of each dynamic parameter in the dynamic model.
In this embodiment, taking a rotating portion as an example, after obtaining a target data corresponding to each sampling point of the rotating portion, substituting a target data corresponding to each sampling point into the kinetic model of the rotating portion, the identification result of each kinetic parameter in the kinetic model can be calculated.
Optionally, since one target data includes an actual moment, a rotation angle position, a rotation angular velocity, and a rotation angular acceleration corresponding to one acquisition point, referring to fig. 5 again, the process of performing parameter identification on the dynamic model of the rotation portion according to a plurality of target data in step S104 to obtain the identification result of each dynamic parameter in the dynamic model may include S1041.
And S1041, respectively substituting the actual moment, the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the dynamic model, and calculating the identification result of each dynamic parameter in the dynamic model.
That is, the actual moment, the rotation angle position, the rotation angular velocity, and the rotation angular acceleration corresponding to each of the collection points are respectively substituted into the dynamic model established for the joint device in step S101, so as to obtain the identification result of each dynamic parameter in the dynamic model, for example, obtain the dynamic parameter p i+1 The value of (c).
In this embodiment, taking a rotating portion as an example, after obtaining the identification result of each dynamic parameter in the dynamic model of the rotating portion, it is further required to verify the identification result of each dynamic parameter in the dynamic model. Therefore, referring to fig. 6 based on fig. 2, after step S104, the method for identifying a dynamic parameter of a mechanical transmission system according to the embodiment of the present application further includes steps S105 to S106.
S105, verifying the identification result of each kinetic parameter in the kinetic model to determine whether the identification result is the optimal identification result.
In this embodiment, if the recognition result is the best recognition result, step S106 is executed; if the recognition result is not the best recognition result, the step S102 is executed again until the recognition result is the best recognition result. This can be understood as follows: after returning to step S102, the steps S103 to S104 are continued until the recognition result is the best recognition result.
And S106, obtaining an ideal dynamic model of the rotating part.
In this embodiment, taking a rotating portion as an example, an ideal dynamic model of the rotating portion is a model which controls the rotating portion and has high control precision.
Step S105 will be described in detail below.
Referring to fig. 7, the process of verifying the recognition result of each kinetic parameter in the kinetic model in step S105 to determine whether the recognition result is the optimal recognition result may include S1051 to S1056.
S1051, updating the dynamic model to a target dynamic model based on the identification result of each dynamic parameter in the dynamic model.
In this embodiment, taking a rotating part as an example, the identification result (e.g., p) of each dynamic parameter in the dynamic model of the rotating part is obtained according to the processes of steps S101 to S104 i+1 Value of (e), the identification of each kinetic parameter (e.g., p) i+1 Value of) is substituted into the dynamic model of the rotating part again, and the target dynamic model of the rotating part can be obtained.
And S1052, respectively substituting the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the target dynamic model to obtain the theoretical moment corresponding to each acquisition point.
In this embodiment, taking a rotating position as an example, each kinetic parameter in the target kinetic model is known, and therefore, the theoretical moment corresponding to each collecting point can be calculated by respectively substituting the rotating angular position, the rotating angular velocity and the rotating angular acceleration corresponding to each collecting point collected in step S102 into the target kinetic model.
And S1053, generating a theoretical moment curve according to the theoretical moment corresponding to each acquisition point, and generating an actual moment curve according to the actual moment corresponding to each acquisition point.
S1054, comparing the theoretical moment curve with the actual moment curve to determine whether the identification result is the best identification result.
S1055, if the contact ratio of the theoretical moment curve and the actual moment curve meets the set condition, determining the identification result as the optimal identification result.
S1056, if the contact ratio of the theoretical moment curve and the actual moment curve does not meet the set condition, determining that the identification result is not the optimal identification result.
In this embodiment, whether the contact ratio of the theoretical moment curve and the actual moment curve meets the set condition may be determined by calculating the contact ratio of the two curves and determining whether the contact ratio reaches a preset contact ratio threshold (e.g., 90%); or the user can judge according to experience; the embodiment of the present application does not set any limit to this.
Compared with the prior art, the embodiment of the application has the following beneficial effects:
firstly, when a dynamic model of a rotating part is established, a friction force model is added on the basis of a traditional dynamic model, so that the establishment of the dynamic model is relatively comprehensive, and the control precision of a mechanical transmission system is improved.
Secondly, after a group of motion data of each rotating part is obtained, averaging the group of motion data, and then filtering the averaged motion data, so that the influence of noise in the collected motion data can be eliminated; meanwhile, in the filtering process, the improved filtering method is adopted for filtering processing, so that the characteristic of data can be better kept on the premise of removing noise.
Thirdly, in the filtering processing of the data, the weighting coefficient is obtained by Butterworth according to the pass band of the mechanical transmission system, and then the cyclic weighting processing is respectively carried out on the average rotation angle positions and the average rotation moments for a plurality of times, so that the noise of the data can be removed in a lower order, and meanwhile, the fidelity effect of the data is improved through the cyclic processing for a plurality of times.
Referring to fig. 8, fig. 8 is a block diagram illustrating a dynamic parameter identification apparatus 100 of a mechanical transmission system according to an embodiment of the present disclosure. The device 100 for identifying dynamic parameters of a mechanical transmission system is applied to an electronic device, and comprises: a model building module 101, a control module 102, a processing module 103 and a parameter identification module 104.
The model establishing module 101 is used for establishing a dynamic model of each rotating part of the mechanical transmission system; the dynamic model is used for representing the influence of inertia quantity, centrifugal force and Coriolis force, gravity and friction force on a rotating part.
The control module 102 is configured to control the mechanical transmission system to repeatedly move according to a pre-designed excitation track for each rotating part, and acquire motion data of the rotating part at preset time intervals during each movement to obtain multiple sets of motion data; wherein one acquisition point corresponds to a set of motion data.
The processing module 103 is configured to process each group of motion data to remove noise, so as to obtain a plurality of target data; wherein one acquisition point corresponds to one target data.
And the parameter identification module 104 is configured to perform parameter identification on the dynamic model of the rotating portion according to the plurality of target data, so as to obtain an identification result of each dynamic parameter in the dynamic model.
Optionally, the kinetic model is:
wherein, tau represents the moment of the rotating part,represents the inertia of the rotating part and is greater or less than>Represents the centrifugal force and the Coriolis force of the rotating part, G (q) represents the gravity term compensation of the rotating part, and>represents the friction force of the rotating part, q represents the rotating angle position of the rotating part, and>indicating the angular speed of rotation of the rotating part>Indicating the rotation angular acceleration of the rotating part;
the friction in the dynamic model is solved according to the following formula:
wherein,represents the friction force of the rotating part>Representing the motor shaft speed at the location of rotation, i representing the number of terms of a polynomial, p i+1 Representing the coefficients of the terms.
Optionally, the motion data comprises an actual rotational angular position and an actual rotational moment of the rotating part; the processing module 103 is specifically configured to:
respectively averaging the actual rotation angle position and the actual rotation moment in each group of motion data to obtain a plurality of average rotation angle positions and a plurality of average rotation moments, wherein one acquisition point corresponds to one average rotation angle position and one average rotation moment;
respectively filtering the average rotation angle positions and the average rotation moments to remove noise and obtain a plurality of rotation angle positions and actual moments, wherein one acquisition point corresponds to one rotation angle position and one actual moment;
solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position by adopting an ordinary differential difference method;
a plurality of target data is obtained, the target data including an actual moment, a rotational angle position, a rotational angular velocity, and a rotational angular acceleration.
Alternatively, the processing module 103 executes a manner of solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angular position by using a ordinary differential method, which may include:
using a second order central difference method, according to the formula
And
solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position; wherein q represents a rotational angle position,representing angular speed of rotation>Indicating the rotational angular acceleration, i indicating the sequence of data, and t indicating a preset time interval for recording the rotational angular position.
Optionally, one target data includes an actual moment, a rotation angle position, a rotation angular velocity, and a rotation angular acceleration corresponding to one acquisition point; the parameter identification module 104 is specifically configured to:
and respectively substituting the actual moment, the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the dynamic model, and calculating the identification result of each dynamic parameter in the dynamic model.
Optionally, the kinetic parameter identification device 100 of the mechanical transmission system may further include a parameter verification module 105, and the parameter verification module 105 is configured to:
verifying the identification result of each dynamic parameter in the dynamic model to determine whether the identification result is the optimal identification result;
if the identification result is the optimal identification result, substituting the optimal identification result into the kinetic model to obtain an ideal kinetic model of the rotating part;
and if the identification result is not the optimal identification result, returning to execute the step of controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track aiming at each rotating part and acquiring the motion data of the rotating part according to a preset time interval in each movement to obtain a plurality of groups of motion data until the identification result is the optimal identification result to obtain an ideal dynamic model of the rotating part.
Optionally, the verifying the recognition result of each kinetic parameter in the kinetic model by the parameter verification module 105 to determine whether the recognition result is the best recognition result may include:
updating the dynamic model into a target dynamic model based on the identification result of each dynamic parameter in the dynamic model;
respectively substituting the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into a target dynamic model to obtain a theoretical moment corresponding to each acquisition point;
generating a theoretical moment curve according to the theoretical moment corresponding to each acquisition point, and generating an actual moment curve according to the actual moment corresponding to each acquisition point;
comparing the theoretical moment curve with the actual moment curve to determine whether the identification result is the optimal identification result;
if the coincidence degree of the theoretical moment curve and the actual moment curve meets the set condition, determining the identification result as the optimal identification result;
and if the coincidence degree of the theoretical moment curve and the actual moment curve does not meet the set condition, determining that the identification result is not the optimal identification result.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working process of the above-described dynamic parameter identification apparatus 100 for a mechanical transmission system may refer to the corresponding process in the foregoing method embodiment, and will not be described herein again.
Referring to fig. 9, fig. 9 is a block diagram illustrating an electronic device 10 according to an embodiment of the present disclosure. The electronic device 10 may be an upper computer, a personal computer, an industrial personal computer, or the like. The electronic device 10 includes a processor 11, a memory 12, and a bus 13, and the processor 11 is connected to the memory 12 through the bus 13.
The memory 12 is used for storing a program, and the processor 11 executes the program after receiving the execution instruction to implement the method for identifying the dynamic parameter of the mechanical transmission system disclosed in the above embodiment.
The Memory 12 may include a Random Access Memory (RAM) and a non-volatile Memory (NVM).
The processor 11 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by instructions in the form of hardware integrated logic circuits or software in the processor 11. The processor 11 may be a general-purpose processor, and includes a Central Processing Unit (CPU), a Micro Control Unit (MCU), a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA), and an embedded ARM.
The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor 11, the method for identifying the dynamic parameter of the mechanical transmission system disclosed in the foregoing embodiment is implemented.
In summary, the present application provides a method and a related apparatus for identifying dynamic parameters of a mechanical transmission system, first, a dynamic model of each rotating part of the mechanical transmission system is established; then, aiming at each rotating part, controlling a mechanical transmission system to move repeatedly according to a pre-designed excitation track, and acquiring motion data of the rotating part according to a preset time interval in each movement, wherein one acquisition point corresponds to one group of motion data; then, each group of motion data is respectively processed to remove noise, and target data corresponding to each acquisition point is obtained; and finally, performing parameter identification on the dynamic model according to the target data corresponding to each acquisition point to obtain an identification result of each dynamic parameter. In other words, in the process of establishing the dynamic model, the influence of the inertia quantity, the centrifugal force, the Coriolis force, the gravity and the friction force on the rotating part is comprehensively considered, so that the establishment of the dynamic model is relatively comprehensive, the dynamic parameters in the dynamic model can be accurately identified, and the aim of improving the torque compensation control precision of the whole mechanical transmission system in the later period is fulfilled.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (9)
1. A method for identifying kinetic parameters of a mechanical transmission system, the method comprising:
establishing a dynamic model of each rotating part of the mechanical transmission system; wherein the dynamic model is used for representing the influence of inertia, centrifugal force and Coriolis force, gravity and friction on the rotating part;
aiming at each rotating part, controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track, and acquiring motion data of the rotating part according to a preset time interval in each movement to obtain a plurality of groups of motion data; wherein one acquisition point corresponds to a set of motion data;
processing each group of motion data respectively to remove noise to obtain a plurality of target data; wherein, one acquisition point corresponds to one target data;
according to the target data, performing parameter identification on the dynamic model of the rotating part to obtain an identification result of each dynamic parameter in the dynamic model;
verifying the identification result of each kinetic parameter in the kinetic model to determine whether the identification result is the optimal identification result;
if the identification result is the optimal identification result, substituting the optimal identification result into the kinetic model to obtain an ideal kinetic model of the rotating part;
and if the identification result is not the optimal identification result, returning to execute the step of controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track aiming at each rotating part, and acquiring the motion data of the rotating part according to a preset time interval in each movement to obtain multiple groups of motion data until the identification result is the optimal identification result, thereby obtaining an ideal dynamic model of the rotating part.
2. The method of claim 1, wherein the kinetic model is:
wherein τ represents a moment of the rotating portion,represents the inertia of the rotating part and/or the device>Represents the centrifugal force and the Coriolis force of the rotating part, G (q) represents the gravity term compensation of the rotating part, and/or the compensation of the gravity term of the rotating part>Represents the friction force of the rotating part, q represents the rotating angle position of the rotating part, and/or>Represents the angular speed of rotation of the rotating part, and/or the position of the rotating part>Representing a rotational angular acceleration of the rotational position;
the friction in the dynamic model is solved according to the following formula:
3. The method of claim 1, wherein the motion data comprises an actual rotational angular position and an actual rotational torque of the rotational location;
the step of processing each group of the motion data to remove noise and obtain a plurality of target data includes:
respectively averaging the actual rotation angle position and the actual rotation moment in each group of the motion data to obtain a plurality of average rotation angle positions and a plurality of average rotation moments, wherein one acquisition point corresponds to one average rotation angle position and one average rotation moment;
filtering the average rotation angle positions and the average rotation moments to remove noise, and obtaining a plurality of rotation angle positions and actual moments, wherein one acquisition point corresponds to one rotation angle position and one actual moment;
solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position by adopting a normal differential difference method;
and obtaining the plurality of target data, wherein the target data comprises actual torque, a rotation angle position, a rotation angular speed and a rotation angular acceleration.
4. The method of claim 3, wherein said step of solving for rotational angular velocity and rotational angular acceleration for each of said rotational angular positions using ordinary differential differencing comprises:
using a second order central difference method, according to the formula
And
solving the rotation angular velocity and the rotation angular acceleration corresponding to each rotation angle position;
5. The method of claim 1, wherein one of said target data comprises actual torque, angular position of rotation, angular velocity of rotation, and angular acceleration of rotation corresponding to one acquisition point;
the step of performing parameter identification on the dynamic model according to the plurality of target data to obtain the identification result of each dynamic parameter in the dynamic model comprises the following steps:
and respectively substituting the actual moment, the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the dynamic model, and calculating the identification result of each dynamic parameter in the dynamic model.
6. The method of claim 1, wherein one of said target data comprises actual torque, angular position of rotation, angular velocity of rotation, and angular acceleration of rotation corresponding to one acquisition point;
the step of verifying the recognition result of each kinetic parameter in the kinetic model to determine whether the recognition result is the best recognition result comprises:
updating the dynamic model to a target dynamic model based on the identification result of each dynamic parameter in the dynamic model;
respectively substituting the rotation angle position, the rotation angular velocity and the rotation angular acceleration corresponding to each acquisition point into the target dynamic model to obtain a theoretical moment corresponding to each acquisition point;
generating a theoretical moment curve according to the theoretical moment corresponding to each acquisition point, and generating an actual moment curve according to the actual moment corresponding to each acquisition point;
comparing the theoretical moment curve with the actual moment curve to determine whether the identification result is the optimal identification result;
if the coincidence degree of the theoretical moment curve and the actual moment curve meets a set condition, determining the identification result as the optimal identification result;
and if the coincidence degree of the theoretical moment curve and the actual moment curve does not meet the set condition, determining that the identification result is not the optimal identification result.
7. An apparatus for identifying a kinetic parameter of a mechanical transmission system, the apparatus comprising:
the model establishing module is used for establishing a dynamic model of each rotating part of the mechanical transmission system; wherein the dynamic model is used for representing the influence of inertia, centrifugal force and Coriolis force, gravity and friction on the rotating part;
the control module is used for controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track aiming at each rotating part, and acquiring motion data of the rotating part according to a preset time interval in each movement to obtain a plurality of groups of motion data; wherein one acquisition point corresponds to a set of motion data;
the processing module is used for respectively processing each group of motion data to remove noise and obtain a plurality of target data; wherein, one acquisition point corresponds to one target data;
the parameter identification module is used for carrying out parameter identification on the dynamic model of the rotating part according to the target data to obtain an identification result of each dynamic parameter in the dynamic model;
a parameter verification module to:
verifying the identification result of each kinetic parameter in the kinetic model to determine whether the identification result is the optimal identification result;
if the identification result is the optimal identification result, substituting the optimal identification result into the kinetic model to obtain an ideal kinetic model of the rotating part;
and if the identification result is not the optimal identification result, returning to execute the step of controlling the mechanical transmission system to repeatedly move according to a pre-designed excitation track and collecting the motion data of the rotating part at each movement according to a preset time interval to obtain a plurality of groups of motion data aiming at each rotating part until the identification result is the optimal identification result to obtain an ideal dynamic model of the rotating part.
8. An electronic device comprising a processor and a memory, the memory storing a program, the processor when executing the program implementing the method of identifying a kinetic parameter of a mechanical transmission system of any of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of identifying a kinetic parameter of a mechanical transmission system according to any of claims 1 to 6.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210552661.XA CN114896731B (en) | 2022-05-19 | 2022-05-19 | Kinetic parameter identification method of mechanical transmission system and related device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210552661.XA CN114896731B (en) | 2022-05-19 | 2022-05-19 | Kinetic parameter identification method of mechanical transmission system and related device |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114896731A CN114896731A (en) | 2022-08-12 |
CN114896731B true CN114896731B (en) | 2023-04-14 |
Family
ID=82724295
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210552661.XA Active CN114896731B (en) | 2022-05-19 | 2022-05-19 | Kinetic parameter identification method of mechanical transmission system and related device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114896731B (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103034123A (en) * | 2012-12-11 | 2013-04-10 | 中国科学技术大学 | Dynamic model parameter identification based parallel robot control method |
CN107671861A (en) * | 2017-11-13 | 2018-02-09 | 无锡信捷电气股份有限公司 | A kind of improved SCARA Identification of Dynamic Parameters of Amanipulator method |
CN108297093A (en) * | 2017-12-29 | 2018-07-20 | 中国海洋大学 | A kind of step identification method of Manipulator Dynamics parameter |
CN114169230A (en) * | 2021-11-24 | 2022-03-11 | 华南理工大学 | Robot dynamics parameter identification method |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108717492A (en) * | 2018-05-18 | 2018-10-30 | 浙江工业大学 | Manipulator Dynamic discrimination method based on improved artificial bee colony algorithm |
CN108714896B (en) * | 2018-05-28 | 2021-07-16 | 华南理工大学 | Flexible moment feedforward control method of robot based on flexible body dynamic model |
CN111788040B (en) * | 2018-12-28 | 2023-06-06 | 深圳配天智能技术研究院有限公司 | Kinetic parameter identification method of robot, robot and storage device |
CN110531707B (en) * | 2019-09-16 | 2022-03-18 | 无锡信捷电气股份有限公司 | Friction model improvement and dynamic parameter identification method of SCARA robot |
-
2022
- 2022-05-19 CN CN202210552661.XA patent/CN114896731B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103034123A (en) * | 2012-12-11 | 2013-04-10 | 中国科学技术大学 | Dynamic model parameter identification based parallel robot control method |
CN107671861A (en) * | 2017-11-13 | 2018-02-09 | 无锡信捷电气股份有限公司 | A kind of improved SCARA Identification of Dynamic Parameters of Amanipulator method |
CN108297093A (en) * | 2017-12-29 | 2018-07-20 | 中国海洋大学 | A kind of step identification method of Manipulator Dynamics parameter |
CN114169230A (en) * | 2021-11-24 | 2022-03-11 | 华南理工大学 | Robot dynamics parameter identification method |
Also Published As
Publication number | Publication date |
---|---|
CN114896731A (en) | 2022-08-12 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN107813345B (en) | Robot collision detection method and device | |
CN111788040B (en) | Kinetic parameter identification method of robot, robot and storage device | |
KR101724872B1 (en) | Parameter identification for robots with a fast and robust trajectory design approach | |
CN107289951B (en) | Indoor mobile robot positioning method based on inertial navigation | |
CN113119111A (en) | Mechanical arm and track planning method and device thereof | |
CN109586645B (en) | Permanent magnet synchronous motor inertia identification method and equipment | |
CN110941183A (en) | Industrial robot dynamics identification method based on neural network | |
CN112677156B (en) | Robot joint friction force compensation method | |
CN112809667A (en) | Force control method and device of industrial robot and application of force control device | |
CN113051673A (en) | Robot improved Stribeck friction model identification method | |
KR20220109930A (en) | Sensorless Contact Force Estimation Method of Articulated Robot Using Robust External Force Observer | |
CN114896731B (en) | Kinetic parameter identification method of mechanical transmission system and related device | |
CN114800519A (en) | Six-degree-of-freedom industrial robot dynamics parameter identification method considering friction | |
CN111872933A (en) | SCARA robot trajectory tracking control method based on improved quadratic iterative learning control | |
CN110702093A (en) | Particle filter-based positioning method and device, storage medium and robot | |
CN107423515B (en) | Mechanical arm friction identification method, device, equipment and storage medium | |
CN111185908B (en) | Robot control method and device for recognizing friction force, robot and storage medium | |
CN111630772B (en) | Servo system mechanical parameter identification method, servo control system and storage device | |
CN114800536B (en) | Method and device for identifying kinetic parameters of multi-link robot | |
CN109212260B (en) | Motion frequency calculation method and device | |
CN114516050B (en) | Robot external force estimation method and system based on position jacobian condition number optimization | |
CN110110469A (en) | Parallel robot dynamic parameters identification method based on singular value decomposition | |
CN113335294B (en) | Method and device for estimating longitudinal gradient of road surface, electronic device and storage medium | |
CN110567483B (en) | Data processing method of MEMS sensor | |
CN112698345A (en) | Robot simultaneous positioning and mapping optimization method for laser radar |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |