CN111788040B - Kinetic parameter identification method of robot, robot and storage device - Google Patents
Kinetic parameter identification method of robot, robot and storage device Download PDFInfo
- Publication number
- CN111788040B CN111788040B CN201880087307.6A CN201880087307A CN111788040B CN 111788040 B CN111788040 B CN 111788040B CN 201880087307 A CN201880087307 A CN 201880087307A CN 111788040 B CN111788040 B CN 111788040B
- Authority
- CN
- China
- Prior art keywords
- rotating speed
- speed
- friction
- driving motor
- rotating
- 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
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/18—Stabilised platforms, e.g. by gyroscope
-
- 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
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
Abstract
A dynamic parameter identification method of a robot, the robot and a storage device, wherein the method comprises the following steps: under a plurality of different rotating speeds, the driving motor rotates at a constant speed, corresponding armature current at each rotating speed is collected, corresponding friction moment at each rotating speed is calculated according to the corresponding armature current at each rotating speed, a plurality of data pairs of the rotating speed and the friction moment are formed, and a friction polynomial model is established according to the data pairs, wherein the friction polynomial model is used for describing the relation between the rotating speed of the driving motor and the friction moment, can be used as a linear model, has the expression capability of nonlinear characteristics, has better adaptability, and can simplify the identification calculation of the kinetic parameters of the robot.
Description
Technical Field
The present invention relates to the field of automatic control technologies, and in particular, to a method for identifying kinetic parameters of a robot, and a storage device.
Background
The robot dynamics study is the relationship of joint force, moment and joint motion of the robot. Through the dynamic model, the moment provided by the driver of the joint can be calculated according to the moving target position, target speed and the like of the joint, and the robot is controlled according to the result. The ideal dynamics model only considers inertial force, coriolis force (centrifugal force) and gravity, but in practical cases, the friction moment cannot be ignored, otherwise the control and operation effects of the robot are affected. Therefore, it is necessary to first calculate the friction torque using the friction model and remove the effect of the friction torque from the total torque provided by the driver, thereby obtaining the driving torque under the ideal dynamics model that can be used to calculate the inertia parameters.
The inventor of the invention finds that in the process of researching the prior art, in the process of identifying the dynamic parameters of the robot, particularly identifying the parameters of the friction model, the prior art often uses a stribeck model, the stribeck model comprises an index part, the nonlinearity degree is high, and the optimization and solving processes of the friction model and the dynamic model are very complex, so that the calculation capacity of a robot control system is wasted.
Disclosure of Invention
The invention provides a dynamic parameter identification method of a robot, the robot and a storage device, which are used for solving the problem that the dynamic parameter identification process is too complex in the prior art.
In order to solve the technical problems, the invention provides a technical scheme that: a method for identifying kinetic parameters of a robot is provided. The method comprises the following steps: under a plurality of different rotating speeds, enabling the driving motor to rotate at a constant speed, and collecting corresponding armature currents under each rotating speed; calculating corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque; and establishing the friction polynomial model according to the data pair, wherein the friction polynomial model is used for describing the relation between the rotating speed and the friction torque of the driving motor.
In order to solve the technical problems, the invention provides another technical scheme as follows: there is provided a robot comprising a controller and a drive motor coupled to each other, wherein the controller is executable program instructions and performs the following method: under a plurality of different rotating speeds, enabling the driving motor to rotate at a constant speed, and collecting corresponding armature currents under each rotating speed; calculating corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque; and establishing the friction polynomial model according to the data pair, wherein the friction polynomial model is used for describing the relation between the rotating speed and the friction torque of the driving motor.
In order to solve the technical problems, the invention provides another technical scheme as follows: there is provided a storage device storing program instructions that can be loaded and execute the dynamic parameter identification method of the robot.
The beneficial effects of the invention are as follows: by acquiring a plurality of data pairs of rotating speed and friction torque, a polynomial friction model can be established according to the data pairs. The polynomial friction model can be used as a linear model, has the expression capability of nonlinear characteristics, and has better adaptability. Therefore, the invention can simplify the calculation in the identification process of the robot dynamic parameters and save the calculation capacity of the system.
Drawings
Fig. 1 is a flow chart of an embodiment of a dynamic parameter identification method of a robot according to the present invention.
Fig. 2 is a flow chart of another embodiment of the method for identifying kinetic parameters of a robot according to the present invention.
Fig. 3 is a flowchart of a dynamic parameter identification method of a robot according to another embodiment of the invention.
Fig. 4 is a flowchart of an inertial parameter identification method of a robot according to an embodiment of the invention.
Fig. 5 is a schematic structural view of an embodiment of the robot of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating an embodiment of a dynamic parameter identification method of a robot according to the present invention. The method comprises the following steps.
S101: and under a plurality of different rotating speeds, enabling a driving motor of the robot to rotate at a constant speed, and collecting corresponding armature currents under each rotating speed.
The robot may have a plurality of joints, and each joint may be provided with one or more driving motors to drive the joints to move, thereby achieving movement of the robot. In this application, for clarity of explanation, a driving motor is exemplified. The driving motor of the robot may be a direct current motor or an alternating current motor, which is not limited herein. In step S101, the driving motor is made to move at a constant speed at different rotational speeds, for example, the driving motor may be made to move at a constant speed for a period of time at a lower rotational speed first, then the rotational speed is gradually increased, the constant speed movement for a period of time is maintained at each rotational speed, and the corresponding armature current at each rotational speed is acquired. In order to reduce errors, multiple groups of armature current data can be collected at each rotating speed, and then the corresponding armature current at the rotating speed is obtained by averaging, or when the armature current changes periodically, the direct current component and the alternating current component of each group of armature current data can be extracted and respectively averaged.
Alternatively, the drive motor may be rotated at a constant speed at an initial test speed (e.g., 1 °/s) and the armature current corresponding to the initial test speed is collected. Then, the rotational speed is increased by a variable step (or, if the initial rotational speed is selected to be a higher rotational speed, the rotational speed is gradually reduced according to the variable step in the subsequent test) each time, so as to obtain the subsequent test rotational speed. And enabling the driving motor to rotate at a constant speed under the subsequent test rotating speed, and collecting armature current corresponding to the subsequent test rotating speed until the target rotating speed is reached. The initial rotation speed and the target rotation speed may each be specified empirically by an operator, and for example, the initial rotation speed and the target rotation speed may be set to a minimum rotation speed and a maximum rotation speed that can be achieved by the drive motor, respectively. In some embodiments, the higher the rotational speed, the larger the value of the variable step, i.e. the denser the rotational speed in the low speed section, during the change of the rotational speed, so that the result may better describe the non-linear characteristics of the friction torque in the low speed section. For example, the step size may be set to 1 °/s in the low speed section, i.e., the rotational speed is changed by 1 °/s each time, and the step size may be set to 2 °/s or 3 °/s in the high speed section, or the like. It will be appreciated that in other embodiments the step size of the speed change may be a fixed value.
S102: and calculating corresponding friction moment at each rotating speed according to the corresponding armature current at each rotating speed so as to form a plurality of data pairs of the rotating speed and the friction moment.
On the basis of obtaining the corresponding armature current at each rotating speed, the corresponding friction moment at each rotating speed can be calculated by combining the current-torque model of the joint driving motor. Specifically, since the driving motor moves at a uniform speed at each rotation speed, the acceleration is zero, and no inertia force exists, the direct current component in the torque output by the driving motor can be considered to be used for overcoming the friction torque. Therefore, the direct current component of the armature current at each rotating speed is extracted, and the corresponding moment for overcoming the friction moment, namely the magnitude of the friction moment, can be calculated according to the relation between the output torque of the driving motor and the armature current. Thus, in step S102, a plurality of data pairs of rotational speed and friction torque are obtained.
S103: from these pairs of data, a friction polynomial model is created which describes the relationship between the rotational speed of the drive motor and the friction torque.
In general, to simplify the model complexity, it is considered that the torque generated by friction is only related to the driving motor (joint) rotation speed. In step S103, the polynomial model is used to fit the data obtained in step S102, thereby obtaining each parameter in the polynomial model. The obtained friction polynomial model can be used for describing the relation between the rotating speed of the driving motor and the friction moment, namely, the magnitude of the friction moment applied to the joint during operation can be known by giving any rotating speed of the driving motor.
Alternatively, the polynomial model may be a 1-element K-th order polynomial for characterizing the relationship of rotational speed to friction torque, where K is a positive integer greater than or equal to 2, for example, k=3 or k=4.
Alternatively, since the friction polynomial can be regarded as a linear model, curve fitting can be performed using a least squares method, and the fitting method is simple and quick. It will be appreciated that other parameter optimization and fitting methods may be used to fit the friction polynomials.
By acquiring a plurality of data pairs of the rotating speed and the friction torque, a friction polynomial model can be established according to the data pairs. The friction polynomial model can be used as a linear model, has the expression capability of nonlinear characteristics, and has better adaptability. Therefore, the invention can simplify the calculation in the identification process of the robot dynamic parameters and save the calculation capacity of the system.
Referring to fig. 2, fig. 2 is a flowchart illustrating a dynamic parameter identification method of a robot according to another embodiment of the invention. As shown in fig. 2, the method includes the following steps.
S201: and under a plurality of different rotating speeds, the driving motor rotates at a constant speed, and corresponding armature currents at all the rotating speeds are collected.
S202: and calculating corresponding friction moment at each rotating speed according to the corresponding armature current at each rotating speed so as to form a plurality of data pairs of the rotating speed and the friction moment.
Steps S201 and S202 are similar to steps S101 and S102 described above, and are not repeated here.
S203: and finding out the minimum friction moment and the corresponding reference rotation speed according to the corresponding friction moment at each rotation speed.
If m sets of data pairs of rotational speed and friction torque are acquired, these data pairs are traversed first to find the minimum friction torque and the reference rotational speed corresponding to the minimum friction torque, for example, the minimum friction torque may be denoted as torborder and the corresponding reference rotational speed may be denoted as V border.
S204: and judging whether rotating speeds greater than or less than the reference rotating speed exist in the data pair at the same time.
According to the friction theory, two surfaces in contact with each other in a system in a lubrication state can undergo four friction stages from rest to sliding, namely a static friction stage, a boundary lubrication stage, a partial lubrication stage and a full lubrication stage. Due to the different friction phases, the friction torque tends to decrease and then increase gradually as the rotational speed increases gradually from zero. Therefore, in theory, there is a minimum friction torque at the interface of the descending and ascending sections. In practical situations, under the influence of factors such as the selected test rotating speed, system precision, lubrication condition and the like, the situation that the minimum friction moment is the minimum rotating speed among all data pairs obtained by testing is likely to occur. In both cases, the friction torque needs to be modeled in a different manner, so in step S204 it is determined whether there is a rotational speed in the data pair that is both greater and less than the reference rotational speed, and if so, steps S205 and S206 are performed, otherwise step S207 is performed.
S205: and taking a rotating speed range smaller than the reference rotating speed as a low-speed section, and fitting the data pair of the friction torque in the low-speed section to obtain a low-speed friction model.
S206: and taking a rotating speed range which is larger than the reference rotating speed as a high-speed section, and fitting the data pair of the friction torque in the high-speed section to obtain a high-speed friction model.
In steps S205 and S206, the rotation speed-friction torque data pair obtained by the test is divided into a high-speed section and a low-speed section by using the reference rotation speed v_border as a boundary, and the data pairs in the high-speed section and the low-speed section are fitted by using polynomial models, so as to obtain a friction model of the low-speed section and a friction model of the high-speed section respectively, and a curve of the friction model of the low-speed section and a curve of the friction model of the high-speed section are intersected at a point (v_border, tor_border), so that a continuous friction torque characteristic curve in the complete rotation speed range of the driving motor is obtained. It can be appreciated that the low-speed segment and the high-speed segment can both be fitted with data using a polynomial model of degree K, where the K values can be selected based on empirical values, and the K values of the low-speed segment and the high-speed segment can be the same or different.
In this way, the friction model of the low-speed section and the friction model of the high-speed section are obtained respectively, so that the stribeck phenomenon of the low-speed section can be better described, and the polynomial friction model of the high-speed section can also better characterize the linear characteristic and the nonlinear characteristic of the friction moment of the high-speed section compared with the traditional stribeck friction model.
S207: fitting the data pairs of all the rotating speeds and the friction moments to obtain a friction polynomial model.
If the data pairs do not have rotational speeds greater than and less than the reference rotational speed, typically the reference rotational speed v_border is the lowest rotational speed, in which case a single K-degree polynomial model may be used to fit the data pairs to obtain a friction polynomial model of the joint. It will be appreciated that this case can also be considered a special case of a piecewise polynomial function.
Referring to fig. 3, fig. 3 is a flowchart illustrating a dynamic parameter identification method of a robot according to another embodiment of the invention. As shown in fig. 3, the method includes the following steps.
S301: the drive motor is set to a position mode or a speed mode at a plurality of different rotational speeds.
The servo system is usually provided with a position loop, a speed loop and a current loop control mode, and a driving motor of the robot also belongs to the servo system. Since it is desired that the driving motor moves at a uniform speed during the test, the control may be performed using a position loop or a speed loop, i.e., the driving motor is set to a position mode or a speed mode in step S301.
S302: the driving motor is enabled to move from the first position to the second position at a constant speed, and the driving motor returns to the first position at a constant speed from the second position, and armature current of the driving motor is collected during the constant speed.
At each rotating speed, the driving motor moves from the first position to the second position at a constant speed, and returns to the first position at a constant speed from the second position, so that the armature current of the driving motor rotating forwards and the armature current of the driving motor rotating reversely at each rotating speed can be obtained.
S303: and calculating corresponding friction moment at each rotating speed according to the corresponding armature current at each rotating speed so as to form a plurality of data pairs of the rotating speed and the friction moment.
According to the armature current of the forward rotation of the driving motor at each rotation speed, the rotation speed-friction torque data pair of the forward rotation of the driving motor can be obtained, and the armature current of the reverse rotation of the driving motor at each rotation speed can be used for obtaining the rotation speed-friction torque data pair of the reverse rotation of the driving motor.
S304: and establishing a forward rotation friction model of the driving motor by using a data pair of the rotating speed and the friction torque in the process that the driving motor moves from the first position to the second position at a uniform speed.
S305: and establishing a reverse friction model of the driving motor by using a data pair of the rotating speed and the friction torque in the process that the driving motor returns to the first position from the second position at a constant speed.
In step S304 and step S305, the forward rotation friction model and the reverse rotation friction model of the drive motor can be established by fitting using the pairs of rotational speed-friction torque data obtained in the previous step under the forward rotation and the reverse rotation of the drive motor, respectively, and using the polynomial models, respectively.
According to the forward rotation friction model of the driving motor, the friction moment during forward rotation of the driving motor can be accurately calculated by the rotating speed of the driving motor. According to the reverse friction model of the driving motor, the friction moment when the driving motor reverses can be accurately calculated by the rotating speed of the driving motor. In actual cases, there may be some difference in friction characteristics at the time of forward rotation and reverse rotation of the drive motor, and the friction characteristics of the drive motor can be described more accurately by respectively establishing a forward rotation friction model and a reverse rotation friction model.
It should be appreciated that the solution in the embodiment of fig. 3 may be used in combination with the solutions of fig. 1 and/or 2. For example, the method using the piecewise polynomial model described in the embodiment of fig. 2 may be used in both the construction of the forward friction model and the reverse friction model of the drive motor.
In addition to the friction model, the kinetic parameters of the robot include inertial parameters of the robot, such as mass, centroid and moment of inertia of the axes. Therefore, after the friction polynomial model of the robot is obtained according to any of the above embodiments, the present invention further provides a method of inertial parameter identification of the robot,
the form of the kinetic model of the robot considering friction factors can be expressed as:
where τ is a vector of n 1 (n is the number of robot joints), i (i=1, 2, …, n) thThe physical meaning of the components is the driving moment required by the ith joint of the robot,
is an inertia moment vector, wherein H (q) is a mass matrix,/and>
for acceleration of each axis->
Is the Ke's/centrifugal moment vector, G (q) is the heavy moment vector,/is the centrifugal moment vector>
Is a friction torque vector. Inertial parameters of the robot such as mass, centroid and moment of inertia are included in H (q) and +.>
And G (q). Transforming the formula (1) to obtain a deformed dynamic model:
wherein the method comprises the steps of
Called regression matrix, is independent of inertial parameters, and p is a column vector formed by arranging the inertial parameters. Under this expression, τ and p exhibit a linear relationship, and are therefore referred to as the linear version of the kinetic model.
To identify inertial parameters, a method as shown in fig. 4 may be performed, which includes the following steps.
S401: and selecting an excitation track identified by the inertia parameters, enabling the driving motor to run according to the excitation track, and collecting the feedback position, the feedback speed and the feedback current of the driving motor.
From the above analysis, it can be known that there is a certain relation between the inertial parameters of the robot (or the robot joint) and the driving moment, position, speed, acceleration, friction moment of the robot, and on the basis of the known friction model, we can calculate the above parameters according to the feedback position, feedback speed and feedback current of the driving motor (equivalent to the joint). If a plurality of groups of relations can be obtained, the inertia parameters of the robot can be calculated by fitting the dynamics curve of the robot.
Excitation trajectory refers to the path that we desire the drive motor to move, i.e. at what speed the drive motor moves to where. In an ideal situation, if no systematic error exists, the driving motor is only required to move at different speeds, accelerations and positions of a plurality of groups (the specific number is related to the number of inertial parameters), and corresponding feedback signals are collected, so that the dynamics curve of the robot can be fitted. However, in practical situations, the path of the motion of the driving motor cannot be arbitrarily selected due to interference of system noise and measurement errors, otherwise, calculation errors are too large, and the result is inaccurate or calculation cannot be converged. Therefore, in step S401, an excitation track identified by the inertial parameter is first selected, so that the driving motor moves according to the excitation track, and the feedback position, the feedback speed and the feedback current of the driving motor are collected. The excitation track can be selected empirically or calculated by an optimization algorithm.
Optionally, the initial value of the excitation track parameter may be selected at will, or the initial value may be selected according to an empirical value, and then the parameter of the excitation track is optimized by using an optimization algorithm such as a genetic algorithm, so as to minimize the deviation of the fitting calculation under the condition of considering the system error and the measurement error. For a specific method, reference may be made to the description in the related art.
S402: and calculating corresponding friction torque according to the feedback speed and a friction polynomial model of the driving motor, and calculating output torque according to the feedback current, thereby obtaining the driving torque under an ideal dynamics model.
The collected feedback speed is substituted into a friction polynomial model, so that the corresponding friction moment can be calculated, and the output torque of the driving motor can be calculated according to the feedback current. By subtracting the output torque from the friction torque, the driving torque under the ideal dynamic model (i.e., the dynamic model after ignoring the friction torque or removing the influence of the friction torque) can be obtained. In this way, the driving moment at each point on the excitation path can be obtained.
S403: and fitting inertial parameters of the robot according to the driving moment, the feedback position and the feedback speed.
Observing a kinetic model in a linear form
It can be seen that the parameters related to the inertial parameters include, in addition to the driving torque, a position vector, a velocity vector, and an acceleration vector, where the position vector and the velocity vector of each point on the excitation path are the feedback position and the feedback velocity acquired, and the acceleration vector may be obtained by performing a numerical difference on the feedback velocity. Therefore, the inertial parameters of the robot can be fitted by combining a linear dynamic inverse solution model. The fitting process can adopt optimization algorithms such as least square method, and the like, and the method is not limited.
By implementing the method, on the basis of acquiring the friction polynomial model of the robot, each inertial parameter of the robot can be further acquired, so that all required kinetic parameters of the robot are obtained. Calculation and control can be performed through the acquired dynamic parameters in the control process of the robot.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a robot 500 according to an embodiment of the invention. The robot 500 includes a communication bus 501, a controller 502, a memory 403, and a drive motor 504. The controller 502 and the memory 503 are coupled by a communication bus 501.
The memory 503 stores program data, and the program data may be loaded by the controller 502 and executed by the dynamic parameter identification method of the robot according to any of the above embodiments. It will be appreciated that in other embodiments, the memory 503 may be provided in the same physical device by a different controller 502, and that the method of any of the above embodiments may be performed by combining the robot 500 with a network.
The robot 500 may be a type of robot such as an industrial robot or a home robot, for example, an articulated arm or an anthropomorphic robot, etc. Those skilled in the art will appreciate that the solution provided by the present invention can be used with robots that involve only articulation.
The functions described in the above embodiments may be stored in a device having a storage function if implemented in software and sold or used as a separate product, i.e., the present invention also provides a storage device in which a program is stored. Program data in a storage device including, but not limited to, a usb disk, an optical disk, a server, a hard disk, or the like can be executed to implement the dynamic parameter identification method of the robot in the above embodiment.
The foregoing description is only of embodiments of the present invention, and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes using the descriptions and the drawings of the present invention or directly or indirectly applied to other related technical fields are included in the scope of the present invention.
Claims (14)
1. A method for identifying kinetic parameters of a robot, comprising:
under a plurality of different rotating speeds, enabling a driving motor of the robot to rotate at a constant speed, and collecting corresponding armature currents under each rotating speed;
calculating corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque; and
establishing a friction polynomial model according to the data pair, wherein the friction polynomial model is used for describing the relation between the rotating speed and the friction torque of the driving motor;
the step of enabling the driving motor to rotate at a constant speed under a plurality of different rotating speeds and collecting corresponding armature currents under each rotating speed comprises the following steps:
setting the driving motor to be in a position mode or a speed mode under a plurality of different rotating speeds, enabling the driving motor to move from a first position to a second position at a constant speed, and returning the driving motor from the second position to the first position at a constant speed, and collecting armature current of the driving motor during the period;
the step of calculating the corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque comprises the following steps:
extracting the direct current component of the armature current at each rotating speed, and calculating corresponding friction torque at each rotating speed according to the relation between the output torque of the driving motor and the armature current;
the step of establishing the friction polynomial model according to the data pair comprises the following steps:
establishing a forward rotation friction model of the driving motor by using the data pair of the rotating speed and the friction torque in the process that the driving motor moves from a first position to a second position at a uniform speed; and
establishing a reverse friction model of the driving motor by using the data pair of the rotating speed and the friction torque in the process that the driving motor returns to the first position from the second position at a constant speed;
the step of establishing the friction polynomial model from the pair of data further comprises:
according to the corresponding friction moment at each rotating speed, finding out the minimum friction moment and the corresponding reference rotating speed;
when the data pair simultaneously has the rotating speed which is larger than and smaller than the reference rotating speed, the rotating speed range which is smaller than the reference rotating speed is used as a low-speed section, the data pair of the rotating speed and the friction torque in the low-speed section is fitted to obtain a low-speed friction model, the rotating speed range which is larger than the reference rotating speed is used as a high-speed section, and the data pair of the rotating speed and the friction torque in the high-speed section is fitted to obtain a high-speed friction model.
2. The method of claim 1, wherein the step of modeling the friction polynomial based on the pair of data further comprises:
and when the data pairs do not have the rotating speeds which are larger than and smaller than the reference rotating speed, fitting the data pairs of all the rotating speeds and the friction torque to obtain the friction polynomial model.
3. The method of claim 1, wherein the step of rotating the drive motor at a constant speed at a plurality of different rotational speeds and collecting corresponding armature currents at each rotational speed comprises:
enabling the driving motor to rotate at a constant speed under an initial test rotating speed, and collecting armature current corresponding to the initial test rotating speed;
the method comprises the steps of increasing or decreasing the rotating speed by a variable step length each time to obtain a subsequent test rotating speed, enabling the driving motor to rotate at a constant speed under the subsequent test rotating speed, and collecting armature current corresponding to the subsequent test rotating speed until reaching a target rotating speed;
wherein the higher the rotational speed, the larger the value of the variable step.
4. The method of claim 1, wherein the friction polynomial model is a 1-element K-th order polynomial used to characterize the relationship of rotational speed to friction torque, where K is a positive integer greater than or equal to 2.
5. The method of claim 1, wherein the friction polynomial model is curve fitted using a least squares method.
6. The method as recited in claim 1, further comprising:
selecting an excitation track identified by inertia parameters, enabling the driving motor to run according to the excitation track, and collecting feedback position, feedback speed and feedback current of the driving motor;
calculating corresponding friction torque according to the feedback speed and the friction polynomial model of the driving motor, and calculating output torque according to the feedback current, so as to obtain driving torque under an ideal dynamics model;
and fitting inertial parameters of the robot according to the driving moment, the feedback position and the feedback speed.
7. The method of claim 6, wherein the step of selecting an excitation trajectory for inertial parameter identification comprises:
selecting an initial value of an excitation track parameter; and
and optimizing the excitation track parameters by adopting a genetic algorithm.
8. A robot comprising a controller and a drive motor coupled to each other, wherein the controller is operable to execute program instructions and perform the method of:
under a plurality of different rotating speeds, enabling a driving motor of the robot to rotate at a constant speed, and collecting corresponding armature currents under each rotating speed;
calculating corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque; and
establishing a friction polynomial model according to the data pair, wherein the friction polynomial model is used for describing the relation between the rotating speed and the friction torque of the driving motor;
the step of enabling the driving motor to rotate at a constant speed under a plurality of different rotating speeds and collecting corresponding armature currents under each rotating speed comprises the following steps:
setting the driving motor to be in a position mode or a speed mode under a plurality of different rotating speeds, enabling the driving motor to move from a first position to a second position at a constant speed, and returning the driving motor from the second position to the first position at a constant speed, and collecting armature current of the driving motor during the period;
the step of calculating the corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque comprises the following steps:
extracting the direct current component of the armature current at each rotating speed, and calculating corresponding friction torque at each rotating speed according to the relation between the output torque of the driving motor and the armature current;
the step of establishing the friction polynomial model according to the data pair comprises the following steps:
establishing a forward rotation friction model of the driving motor by using the data pair of the rotating speed and the friction torque in the process that the driving motor moves from a first position to a second position at a uniform speed; and
establishing a reverse friction model of the driving motor by using the data pair of the rotating speed and the friction torque in the process that the driving motor returns to the first position from the second position at a constant speed;
the step of establishing the friction polynomial model from the pair of data further comprises:
according to the corresponding friction moment at each rotating speed, finding out the minimum friction moment and the corresponding reference rotating speed;
when the data pair simultaneously has the rotating speed which is larger than and smaller than the reference rotating speed, the rotating speed range which is smaller than the reference rotating speed is used as a low-speed section, the data pair of the rotating speed and the friction torque in the low-speed section is fitted to obtain a low-speed friction model, the rotating speed range which is larger than the reference rotating speed is used as a high-speed section, and the data pair of the rotating speed and the friction torque in the high-speed section is fitted to obtain a high-speed friction model.
9. The robot of claim 8, wherein said step of modeling said friction polynomial based on said pair of data further comprises:
and when the data pairs only have rotating speeds larger than the reference rotating speed, fitting the data pairs of all the rotating speeds and the friction torque to obtain the friction polynomial model.
10. The robot of claim 8, wherein the method further comprises:
selecting an excitation track identified by inertia parameters, enabling the driving motor to run according to the excitation track, and collecting feedback position, feedback speed and feedback current of the driving motor;
calculating corresponding friction torque according to the feedback speed and the friction polynomial model of the driving motor, and calculating output torque according to the feedback current, so as to obtain driving torque under an ideal dynamics model;
and fitting inertial parameters of the robot according to the driving moment, the feedback position and the feedback speed.
11. The robot of claim 10, wherein the step of selecting an excitation trajectory for inertial parameter identification comprises:
selecting an initial value of an excitation track parameter; and
and optimizing the excitation track parameters by adopting a genetic algorithm.
12. The robot of claim 8, wherein the step of rotating the drive motor at a constant speed at a plurality of different rotational speeds and collecting corresponding armature currents at each rotational speed comprises:
enabling the driving motor to rotate at a constant speed under an initial test rotating speed, and collecting armature current corresponding to the initial test rotating speed;
the method comprises the steps of increasing or decreasing the rotating speed by a variable step length each time to obtain a subsequent test rotating speed, enabling the driving motor to rotate at a constant speed under the subsequent test rotating speed, and collecting armature current corresponding to the subsequent test rotating speed until reaching a target rotating speed;
wherein the higher the rotational speed, the larger the value of the variable step.
13. The robot of claim 8, wherein:
the friction polynomial model is a 1-element K-th order polynomial used for representing the relation between the rotating speed and the friction torque, wherein K is a positive integer greater than or equal to 2; and
the friction polynomial model is curve fitted using a least squares method.
14. A device having a storage function, wherein program instructions are stored, the program instructions being loadable and operative to perform a method of identifying a kinetic parameter of a robot, the method comprising:
under a plurality of different rotating speeds, enabling the driving motor to rotate at a constant speed, and collecting corresponding armature currents under each rotating speed;
calculating corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque; and
establishing a friction polynomial model according to the data pair, wherein the friction polynomial model is used for describing the relation between the rotating speed and the friction torque of the driving motor;
the step of enabling the driving motor to rotate at a constant speed under a plurality of different rotating speeds and collecting corresponding armature currents under each rotating speed comprises the following steps:
setting the driving motor to be in a position mode or a speed mode under a plurality of different rotating speeds, enabling the driving motor to move from a first position to a second position at a constant speed, and returning the driving motor from the second position to the first position at a constant speed, and collecting armature current of the driving motor during the period;
the step of calculating the corresponding friction torque at each rotating speed according to the corresponding armature current at each rotating speed to form a plurality of data pairs of the rotating speed and the friction torque comprises the following steps:
extracting the direct current component of the armature current at each rotating speed, and calculating corresponding friction torque at each rotating speed according to the relation between the output torque of the driving motor and the armature current;
the step of establishing the friction polynomial model according to the data pair comprises the following steps:
establishing a forward rotation friction model of the driving motor by using the data pair of the rotating speed and the friction torque in the process that the driving motor moves from a first position to a second position at a uniform speed; and
establishing a reverse friction model of the driving motor by using the data pair of the rotating speed and the friction torque in the process that the driving motor returns to the first position from the second position at a constant speed;
the step of establishing the friction polynomial model from the pair of data further comprises:
according to the corresponding friction moment at each rotating speed, finding out the minimum friction moment and the corresponding reference rotating speed;
when the data pair simultaneously has the rotating speed which is larger than and smaller than the reference rotating speed, the rotating speed range which is smaller than the reference rotating speed is used as a low-speed section, the data pair of the rotating speed and the friction torque in the low-speed section is fitted to obtain a low-speed friction model, the rotating speed range which is larger than the reference rotating speed is used as a high-speed section, and the data pair of the rotating speed and the friction torque in the high-speed section is fitted to obtain a high-speed friction model.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/125045 WO2020133270A1 (en) | 2018-12-28 | 2018-12-28 | Dynamic parameter identification method for robot, robot and storage device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111788040A CN111788040A (en) | 2020-10-16 |
| CN111788040B true CN111788040B (en) | 2023-06-06 |
Family
ID=71126773
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201880087307.6A Active CN111788040B (en) | 2018-12-28 | 2018-12-28 | Kinetic parameter identification method of robot, robot and storage device |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN111788040B (en) |
| WO (1) | WO2020133270A1 (en) |
Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114425770A (en) * | 2020-10-29 | 2022-05-03 | 北京配天技术有限公司 | Industrial robot teaching control method, electronic equipment and storage medium |
| CN112507480A (en) * | 2020-11-25 | 2021-03-16 | 浙江同善人工智能技术有限公司 | Inertial parameter identification method |
| CN112528434B (en) * | 2020-12-04 | 2023-01-06 | 上海新时达机器人有限公司 | Information identification method and device, electronic equipment and storage medium |
| CN113051673B (en) * | 2020-12-14 | 2023-09-26 | 华南理工大学 | Improved Stribeck friction model identification method for robot |
| CN114636571A (en) * | 2020-12-16 | 2022-06-17 | 北京配天技术有限公司 | White box testing method and device, electronic equipment and storage medium |
| CN112677156B (en) * | 2020-12-30 | 2022-10-18 | 法奥(淄博)智能装备有限公司 | Robot joint friction force compensation method |
| CN113189865B (en) * | 2021-01-27 | 2024-03-26 | 上海际知医疗科技有限公司 | Rehabilitation robot control system based on dynamic parameter identification |
| CN112947069B (en) * | 2021-01-28 | 2022-10-28 | 内蒙古大学 | Control method for moving two-wheeled robot |
| CN113001588A (en) * | 2021-03-08 | 2021-06-22 | 陕西知感通和物联科技有限公司 | Method for identifying kinetic parameters of foot type robot |
| CN114896731B (en) * | 2022-05-19 | 2023-04-14 | 法奥意威(苏州)机器人系统有限公司 | Kinetic parameter identification method of mechanical transmission system and related device |
| CN114888803B (en) * | 2022-05-19 | 2024-01-30 | 山东新一代信息产业技术研究院有限公司 | Mechanical arm dynamic parameter identification method based on iterative optimization |
| CN114800519B (en) * | 2022-05-20 | 2023-09-26 | 天津大学 | Six-degree-of-freedom industrial robot dynamic parameter identification method considering friction |
| CN115674190B (en) * | 2022-09-30 | 2024-05-07 | 深圳市越疆科技股份有限公司 | Cooperative mechanical arm and motion control method, collision detection method and control system thereof |
| CN116175567B (en) * | 2023-02-14 | 2023-11-24 | 合肥合滨智能机器人有限公司 | Identification method for mechanical arm joint friction model parameters and kinetic parameters |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101850549A (en) * | 2010-04-30 | 2010-10-06 | 苏州博实机器人技术有限公司 | Special joint feature detection and parameter regulation device for robot |
| CN103344243A (en) * | 2013-07-02 | 2013-10-09 | 北京航空航天大学 | Friction parameter identification method for aerial remote-sensing inertial stabilization platform |
| CN103926875A (en) * | 2014-04-18 | 2014-07-16 | 东南大学 | Method for friction compensation of ball screw feeding system |
| CN104638999A (en) * | 2014-08-27 | 2015-05-20 | 北京理工大学 | Segment neural network friction model based dual-motor servo system control method |
| CN106695458A (en) * | 2017-02-22 | 2017-05-24 | 华中科技大学 | Friction force modeling method for numerical control machine tool feeding system |
| CN107263467A (en) * | 2017-05-11 | 2017-10-20 | 广州视源电子科技股份有限公司 | The method and apparatus and robot of control machine people cradle head motion |
| CN108582078A (en) * | 2018-05-15 | 2018-09-28 | 清华大学深圳研究生院 | A kind of mechanical arm zero-force control method towards direct teaching |
| CN108890650A (en) * | 2018-08-30 | 2018-11-27 | 无锡信捷电气股份有限公司 | PTP acceleration optimization method and device based on dynamic parameters identification |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3302166B2 (en) * | 1994-03-30 | 2002-07-15 | 株式会社東芝 | Rotary equipment test equipment |
| CN106256084B (en) * | 2014-04-22 | 2019-03-01 | 三菱电机株式会社 | Control device of electric motor |
| CN104678763B (en) * | 2015-01-21 | 2017-02-22 | 浙江工业大学 | Friction compensation and dynamic surface control method based on least squares support vector machine for electromechanical servo system |
| CN105404157A (en) * | 2016-01-06 | 2016-03-16 | 北京理工大学 | Specified performance parameter estimation-based self-adaptive control method |
| CN106998161B (en) * | 2017-03-31 | 2019-05-21 | 苏州伟创电气设备技术有限公司 | A kind of method for identification of rotational inertia and device of servo-system |
| 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 |
-
2018
- 2018-12-28 CN CN201880087307.6A patent/CN111788040B/en active Active
- 2018-12-28 WO PCT/CN2018/125045 patent/WO2020133270A1/en active Application Filing
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101850549A (en) * | 2010-04-30 | 2010-10-06 | 苏州博实机器人技术有限公司 | Special joint feature detection and parameter regulation device for robot |
| CN103344243A (en) * | 2013-07-02 | 2013-10-09 | 北京航空航天大学 | Friction parameter identification method for aerial remote-sensing inertial stabilization platform |
| CN103926875A (en) * | 2014-04-18 | 2014-07-16 | 东南大学 | Method for friction compensation of ball screw feeding system |
| CN104638999A (en) * | 2014-08-27 | 2015-05-20 | 北京理工大学 | Segment neural network friction model based dual-motor servo system control method |
| CN106695458A (en) * | 2017-02-22 | 2017-05-24 | 华中科技大学 | Friction force modeling method for numerical control machine tool feeding system |
| CN107263467A (en) * | 2017-05-11 | 2017-10-20 | 广州视源电子科技股份有限公司 | The method and apparatus and robot of control machine people cradle head motion |
| CN108582078A (en) * | 2018-05-15 | 2018-09-28 | 清华大学深圳研究生院 | A kind of mechanical arm zero-force control method towards direct teaching |
| CN108890650A (en) * | 2018-08-30 | 2018-11-27 | 无锡信捷电气股份有限公司 | PTP acceleration optimization method and device based on dynamic parameters identification |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111788040A (en) | 2020-10-16 |
| WO2020133270A1 (en) | 2020-07-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111788040B (en) | Kinetic parameter identification method of robot, robot and storage device | |
| CN108058188B (en) | Control method of robot health monitoring and fault diagnosis system | |
| JP5996127B2 (en) | Friction identification method and friction identification apparatus | |
| US10126202B2 (en) | Method for automatically estimating inertia, coulomb friction, and viscous friction in a mechanical system | |
| JP5198514B2 (en) | Robot controller | |
| CN102006011B (en) | Controller of electric motor having function of estimating inertia and friction simultaneously | |
| JP5591400B2 (en) | Drive machine load characteristic estimation device | |
| CN108803324A (en) | Multi-joint industrial machinery arm contragradience finite time sliding-mode control | |
| WO2014021433A1 (en) | Robotic apparatus and control method therefor | |
| CN104638999B (en) | Dual-servo-motor system control method based on segmentation neutral net friction model | |
| CN106020124A (en) | Apparatus for controlling servo motor and method for detecting collision | |
| CN111965976B (en) | Robot joint sliding mode control method and system based on neural network observer | |
| WO2017172367A1 (en) | Automatic determination of maximum acceleration for motion profiles | |
| CN113325805A (en) | Active disturbance rejection controller and design method thereof | |
| CN112528434B (en) | Information identification method and device, electronic equipment and storage medium | |
| CN113128018A (en) | Friction force calculation method and device, robot and readable storage medium | |
| CN104965413B (en) | The friciton compensation self-adaptation control method of controlledization flat pad | |
| CN112677156A (en) | Robot joint friction force compensation method | |
| CN110569767B (en) | Motion parameter identification method, system, equipment and computer readable storage medium | |
| CN114859708A (en) | Tracking control method for single-connecting-rod flexible mechanical arm | |
| CN110842911A (en) | Flexible mechanical arm combined modeling and sliding mode control method considering joint motor characteristics | |
| CN108227493B (en) | Robot trajectory tracking method | |
| CN114179089A (en) | Robust region tracking control method for mechanical arm | |
| JP2014117787A (en) | Controller | |
| CN114800519B (en) | Six-degree-of-freedom industrial robot dynamic parameter identification method considering friction |
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 |