CN116277034A

CN116277034A - Robot control method and device for coping with load change and electronic equipment

Info

Publication number: CN116277034A
Application number: CN202310542253.0A
Authority: CN
Inventors: 王远; 魏晓晨; 李文龙; 李文凯; 张靖
Original assignee: Beijing Yidian Lingdong Technology Co ltd
Current assignee: Beijing Yidian Lingdong Technology Co ltd
Priority date: 2023-05-15
Filing date: 2023-05-15
Publication date: 2023-06-23
Anticipated expiration: 2043-05-15
Also published as: CN116277034B

Abstract

The application discloses a robot control method and device for coping with load change and electronic equipment. Wherein the method comprises the following steps: acquiring torque parameters and position tracking errors of the robot at the current moment; acquiring a sampling period corresponding to the robot, wherein the sampling period represents the interval duration of the torque parameters of the adjacent two acquisition robots; determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, wherein the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used for compensating load change existing when the robot is controlled to move by the first control parameter; and determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter, and controlling the robot to move according to the target torque parameter, wherein the target moment is positioned behind the current moment. The technical problem that control accuracy is poor when controlling a robot in the prior art is solved.

Description

Robot control method and device for coping with load change and electronic equipment

Technical Field

The present invention relates to the field of robot control, and more particularly, to a robot control method, apparatus, and electronic device for coping with load changes.

Background

In the prior art, a PID control method can be adopted to control the robot, however, when the robot is controlled to move by the PID control method, the load change of the robot in practical application cannot be dealt with, so that the control precision of the robot is poor.

However, in the field of robot control, particularly in practical applications of medical mechanical arms, load changes, such as arm strength transmission of an operator and load impact changes of end-effector power, are often involved, and therefore, the medical robot should be designed in consideration of the load changes, that is, it is necessary to design a control method adapted to the load changes.

In view of the above problems, no effective solution has been proposed at present.

Disclosure of Invention

The application provides a robot control method and device for coping with load change and electronic equipment, and aims to at least solve the technical problem that in the prior art, control accuracy is poor when a robot is controlled.

According to an aspect of the present application, there is provided a robot control method for coping with a load change, including: acquiring torque parameters and position tracking errors of the robot at the current moment; acquiring a sampling period corresponding to the robot, wherein the sampling period represents the interval duration of the torque parameters of the adjacent two acquisition robots; determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, wherein the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used for compensating load change existing when the robot is controlled to move by the first control parameter; and determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter, and controlling the robot to move according to the target torque parameter, wherein the target moment is positioned behind the current moment.

Further, the robot control method for coping with load variation further includes: acquiring actual displacement of the robot at the current moment; acquiring expected displacement corresponding to the robot at the current moment, wherein the expected displacement is realized by the expected robot at the current moment; and calculating the difference between the expected displacement and the actual displacement to obtain a position tracking error.

Further, the robot control method for coping with load variation further includes: after a sampling period corresponding to the robot is acquired, differential calculation is carried out on the sampling period to obtain differential time corresponding to the robot; and carrying out integral calculation on the sampling period to obtain the corresponding integral time of the robot.

Further, the robot control method for coping with load variation further includes: before determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, conducting derivative calculation on the position tracking error to obtain the first parameter; and conducting derivative calculation on the first parameter to obtain a second parameter.

Further, the robot control method for coping with load variation further includes: acquiring a minimum value of proportional gain corresponding to the robot; the first control parameter is determined based on a minimum value of the proportional gain, the derivative time, the integral time, the first parameter, the second parameter, the position tracking error, and the sampling period.

Further, the robot control method for coping with load variation further includes: determining a target gain corresponding to the robot based on the minimum value of the proportional gain, wherein the target gain is an adaptive gain for coping with load change; the second control parameter is determined based on the target gain, the derivative time, the integral time, the first parameter, the second parameter, the position tracking error, and the sampling period.

Further, the robot control method for coping with load variation further includes: acquiring the self-adaptive total gain of the robot at the current moment; and calculating the difference between the minimum value of the self-adaptive total gain and the proportional gain to obtain the target gain.

Further, the robot control method for coping with load variation further includes: and summing the first control parameter, the second control parameter and the torque parameter to obtain the target torque parameter.

According to another aspect of the present application, there is also provided a robot control device that handles a load change, including: the acquisition module is used for acquiring torque parameters and position tracking errors of the robot at the current moment; the acquisition module is used for acquiring a sampling period corresponding to the robot, wherein the sampling period represents the interval duration of the torque parameters of the adjacent two acquisition robots; the system comprises a determining module, a sampling module and a control module, wherein the determining module is used for determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used for compensating load change existing when the robot is controlled to move by the first control parameter; and the control module is used for determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter and controlling the robot to move according to the target torque parameter, wherein the target moment is positioned behind the current moment.

According to another aspect of the present application, there is also provided a computer readable storage medium, in which a computer program is stored, wherein the computer readable storage medium is controlled to execute the above robot control method for coping with load change when the computer program is run.

According to another aspect of the present application, there is also provided an electronic device, wherein the electronic device includes one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the above-described robot control method for coping with load changes.

In the method, a mode of determining a target torque parameter of a robot at a target moment according to a first control parameter, a second control parameter and a torque parameter is adopted, firstly, the torque parameter and a position tracking error of the robot at the current moment are acquired, and then a sampling period corresponding to the robot is acquired, wherein the sampling period represents the interval duration of the torque parameters of the adjacent two acquisition robots. And then, determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, wherein the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used for compensating the load change existing when the robot is controlled to move by the first control parameter. And finally, determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter, and controlling the robot to move according to the target torque parameter, wherein the target moment is positioned behind the current moment.

From the above, according to the method and the device, the second control parameter is added to compensate the load change existing when the robot is controlled to move by the first control parameter on the basis of the conventional PID control parameter (namely the first control parameter), so that the purpose of correcting the torque parameter of the robot at the next moment in real time is achieved, and the control precision of the robot in the running process is improved.

Therefore, through the technical scheme of the application, the purpose of real-time coping with the load change of the robot is achieved, the technical effect of real-time correction of the torque parameter of the robot according to the load change of the robot is achieved, and the problem that in the prior art, the control precision is poor when the robot is controlled is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:

FIG. 1 is a flow chart of an alternative robot control method to cope with load variations according to an embodiment of the present application;

FIG. 2 is a control schematic of an alternative robotic arm according to an embodiment of the application;

FIG. 3 is a schematic illustration of an alternative six-axis load cell according to an embodiment of the present application;

fig. 4 is a schematic view of an alternative robot control device that handles load changes according to an embodiment of the present application.

Detailed Description

In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that, related information (including, but not limited to, user equipment information, user personal information, etc.) and data (including, but not limited to, data for presentation, analyzed data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party. For example, an interface is provided between the system and the relevant user or institution, before acquiring the relevant information, the system needs to send an acquisition request to the user or institution through the interface, and acquire the relevant information after receiving the consent information fed back by the user or institution.

The present application is further illustrated below in conjunction with various embodiments.

Example 1

According to the embodiments of the present application, there is provided an embodiment of a control method of a robot, it should be noted that the steps shown in the flowcharts of the drawings may be performed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be performed in an order different from that herein.

Fig. 1 is a flowchart of an alternative robot control method for coping with load changes according to an embodiment of the present application, as shown in fig. 1, the method comprising the steps of:

Step S101, acquiring torque parameters and position tracking errors of the robot at the current moment.

Alternatively, a control system of a robot may be used as an execution subject of the robot control method of the embodiment of the present application, in which the control system of the robot is simply referred to as a control system for convenience of description. Alternatively, the control system may be a software system or an embedded system that is installed in the processor of the robot.

Alternatively, the robot in the present application may be various kinds of robots, for example, a mechanical arm, a gripper, in other words, the robot in the present application may be various kinds of devices classifiable in the field of robots, and the kind of the robot is not particularly limited in the present application. Preferably, in the present application, the robot may be a medical-type mechanical arm applied in the medical field.

Alternatively, the control system in the present application may implement control of the robot according to the control function shown in formula (1).

（1）

Wherein in formula (1), (k-1) characterizes the current moment,

a torque parameter characterizing the robot at the current moment, < >>

Characterizing the position tracking error of the robot at the current moment.

Alternatively, in order to realize control of the robot according to the above formula (1), the following processes of step S102 to step S104 also need to be performed.

Step S102, acquiring a sampling period corresponding to the robot.

In step S102, the sampling period characterizes the interval duration of the torque parameters of the adjacent two acquisition robots.

Optionally, in formula (1), L represents a sampling period corresponding to the robot. For example, if the control system collects the torque parameters of the robot once every 0.001 seconds, l=0.001 seconds.

Step S103, determining a first control parameter and a second control parameter according to the position tracking error and the sampling period.

In step S103, the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used to compensate for load variation occurring when the robot is controlled to move by the first control parameter.

Specifically, in the formula (1),

characterized by a first control parameter, wherein the first control parameter is also referred to as a conventional PID control parameter, ">

Characterized as a second control parameter, wherein the second control parameter is also referred to as an adaptive PID control parameter.

Step S104, determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter, and controlling the robot to move according to the target torque parameter.

In step S104, the target time is located after the current time, for example, when the current time is (k-1), the target time is k.

Specifically, in the formula (1)

And characterizing a target torque parameter of the robot at a target moment.

It should be noted that, taking the robot as an example, when the load variation is not considered, the control method of the robot is complex, and when the load variation is introduced, the inertia matrix and the gravity torque are immediately increased, so that the dynamic behavior of the robot is significantly changed and the control is more complex.

In addition, proportional-integral-derivative (PID) control algorithms are the most common control algorithms in the industry, and have high acceptance in the field of industrial control. The widespread use of PID controllers benefits from their stable performance under a variety of operating conditions, as well as their ease of operation. Engineers can implement PID control in a simple and intuitive manner. Among them, there are three basic elements of PID control: proportional (pro-port), integral (integral), differential (derivative). The optimization results can be obtained by these three different calculation methods. The process of setting P, I, D the optimum gain to obtain the desired feedback from the control system is called tuning. The calculation of the PID optimum requires a lot of experience and knowledge, and most of current regulators are equipped with an automatic fine tuning function that can easily calculate the PID optimum.

While PID control has proven to be adequate for tracking in linear systems, it is not well-behaved in nonlinear systems such as robots. While PID control methods can exhibit good tracking performance in combination with fuzzy logic, optimal control, and neural networks, these methods often require accurate plant models or involve theoretical complexity, which can make PID control difficult to implement in practical systems and result in structural simplicity and model independence.

From the foregoing, it can be seen that for the problem of load variation in a medical robot scene, conventional PID control with constant gain cannot adapt to this requirement, whereas model-based reference adaptive control requires estimating robot dynamics by an adaptive algorithm, thus increasing structural and computational complexity and reducing adaptation speed. Another is a PID control method based on fuzzy control, which requires expert experience to formulate complex fuzzy PID rules, the fuzzy processing will cause the control accuracy of the robot to be reduced and the dynamic quality to be deteriorated, and the design lacks systemicity, and the control target cannot be defined.

In summary, in the case of load variation, the PID control method with constant gain has a problem of large performance limitation, and cannot cope with complex working conditions, but the above-mentioned related complex control method is difficult to implement. Therefore, in order to ensure the tracking performance of the nonlinear robot system under the unknown dynamics condition, the PID control method can be improved by combining the self-adaptive time delay control theory so as to realize more accurate control of the robot, wherein the time delay control is considered to be a more effective control algorithm of the robot system due to the simple structure and good robustness.

In addition, although the adaptive delay control can solve the control problem of the load change, it cannot be directly applied to the PID controller of the existing robot. On the basis, the discrete PID control is equivalent to the discrete form time delay control, so that the relationship between the PID gain and the time delay control parameter can be obtained by using the equivalence, the PID gain can be selected by using a system method, and based on the characteristic, the control function of the robot is designed by combining a group of independent adjustment parameters, so that the control of the robot is realized under the condition of coping with load change. That is, according to the content of the steps S101 to S104, the second control parameter is added on the basis of the PID control parameter (i.e., the first control parameter) to compensate the load change existing when the robot is controlled to move by the first control parameter, so that the purpose of correcting the torque parameter of the robot at the next moment in real time is achieved, and the control precision in the running process of the robot is improved.

In an alternative embodiment, in the process of acquiring the position tracking error of the robot at the current moment, the control system firstly acquires the actual displacement of the robot at the current moment and then acquires the expected displacement corresponding to the robot at the current moment, wherein the expected displacement is the displacement realized by the expected robot at the current moment. And finally, the control system calculates the difference between the expected displacement and the actual displacement to obtain the position tracking error.

Alternatively, in the present application, the actual displacement of the robot at the current time may be denoted by q, and the desired displacement corresponding to the robot at the current time may be used

On this basis, the control system can calculate the position tracking error of the robot at the current moment>

。

In an alternative embodiment, after the sampling period corresponding to the robot is acquired, the control system further performs differential calculation on the sampling period to obtain differential time corresponding to the robot; and carrying out integral calculation on the sampling period to obtain the corresponding integral time of the robot.

Alternatively, the present application is directed to the method of formula (1)

Represents the differential time corresponding to the robot by +.>

Indicating the integration time corresponding to the robot.

In an alternative embodiment, before determining the first control parameter and the second control parameter according to the position tracking error and the sampling period, the control system first performs derivative calculation on the position tracking error to obtain the first parameter, and then performs derivative calculation on the first parameter to obtain the second parameter.

Alternatively, in the present application, in formula (1)

Characterizing the first parameter mentioned above, +.1->

Characterizing the second parameter as described above.

In an alternative embodiment, the control system may further obtain a minimum value of the proportional gain corresponding to the robot, and then determine the first control parameter according to the minimum value of the proportional gain, the differential time, the integration time, the first parameter, the second parameter, the position tracking error, and the sampling period.

Specifically, the minimum value of the proportional gain corresponding to the robot can be calculated by the formula (1)

And (3) representing. Finally, as can be seen from the partial formula of the first control parameter shown in formula (1), the minimum value of the proportional gain corresponding to the robot is obtained +.>

Differential time->

Integration time->

First parameter->

Second parameter->

Position tracking error->

And after the sampling period L, the first control parameter can be obtained by solving.

In an alternative embodiment, the control system may further determine a target gain corresponding to the robot based on a minimum value of the proportional gain, wherein the target gain is an adaptive gain that is responsive to the load change. The control system then determines a second control parameter based on the target gain, the derivative time, the integral time, the first parameter, the second parameter, the position tracking error, and the sampling period.

Specifically, when determining the target gain corresponding to the robot based on the minimum value of the proportional gain, the control system may acquire the adaptive total gain of the robot at the current moment, and then calculate the difference between the adaptive total gain and the minimum value of the proportional gain to obtain the target gain.

Alternatively, as shown in equation (2)

（2）

Wherein, the application represents the self-adaptive total gain of the robot at the current moment by K(s) through

The target gain is represented, wherein the target gain is a value greater than or equal to 0.

Finally, the target gain is obtained

After determining the second control parameter, the differential time, the integration time, the first parameter, the second parameter, the position tracking error, and the sampling period, the second control parameter in equation (1) may be solved. Wherein +_in formula (1)>

I.e. target gain +.>

。

In an alternative embodiment, the control system may sum the first control parameter, the second control parameter, and the torque parameter to obtain the target torque parameter.

Alternatively, the target torque parameter may be obtained by calculating the sum of the first control parameter, the second control parameter, and the torque parameter, as shown in formula (1)

。

In order to better explain the robot control method in the present application, the following deduction demonstration is made on the formula (1) below.

Taking a robot as an n-degree-of-freedom serial mechanical arm as an example, in order to improve the control effect of the mechanical arm and meet the practical application requirement of the medical mechanical arm, a Lyapunov method can be utilized to prove the stability of a related algorithm, wherein n is a positive integer, and the proving process comprises the following steps:

Firstly, establishing mathematical description of a controlled object:

in particular, modeling robot dynamics, the dynamics of an n-degree of freedom (n-DOF) robotic manipulator is shown below:

（3）

wherein the method comprises the steps of

Respectively representing the angular position, angular velocity and angular acceleration of the robot joint, < >>

Input torque for the control of the joint, < >>

For symmetrical positive definite inertia matrix,>

is the brother force and centrifugal force term,

is gravity item->

Is friction force item->

Is a load disturbance term.

To simplify the dynamic model of robot system, a positive-definite diagonal constant matrix is introduced

Then equation (3) can be written as equation (4)

（4）

Wherein, in the formula (4),

is an adaptive control parameter, +.>

Including all nonlinear or uncertainty terms in robot dynamics, such as coriolis force, centrifugal force, gravity, friction and turbulence, equation (5) is available for lumped system dynamics at a certain moment based on equation (3) and equation (4):

（5）

and step two, introducing error estimation into the mathematical model.

Specifically, a delay estimation method is adopted to obtain the formula (4)

Approximation of +.>

Introducing a time delay for controlling the torque input and the acceleration, using +.>

To estimate +. >

Equation (6) can be obtained:

（6）

wherein, the liquid crystal display device comprises a liquid crystal display device,

is->

L is the introduced time delay value. As can be seen from equation (6), L is smaller, +.>

Estimate->

The higher the accuracy of (c). Since the minimum L achievable in practical cases is a sampling period, the time delay value L is typically selected to be one sampling period.

According to formula (6), the structural design of classical time delay control is as follows formula (7):

(7)

for the position tracking error of the robot, +.>

For the desired position trajectory +.>

、/>

A diagonal feedback gain matrix is determined for the positive. From the formula (5) and the formula (6), it is known that +_>

Can be by->

Approximately, therefore, the non-linear term +.therein can be counteracted by substituting equation (7) into the robot dynamics model (4)>

。

And step three, introducing robot dynamics.

Specifically, according to the formulas (4) to (7), the closed loop system error dynamics of the robot when the time delay control is adopted can be obtained as formula (8):

（8）

wherein the stability of the delay control can be determined by the following conditional formula (9):

（9）

in the formula (9), I is an identity matrix.

When the stability condition formula (9) is satisfied, the right side of formula (8)

Namely, the delay estimation error is bounded. Definitions- >

Representing the delay estimation error, equation (10) can be obtained:

（10）

in the classical delay control system (7), since

Is a constant gain matrix and therefore cannot accommodate load variations of the robotic system. In addition, in classical delay control, delay estimation will produce a non-negligible delay estimation error +.>

Although->

However, if the tracking performance is not effectively suppressed, the tracking performance of the robot system is also affected.

And step four, designing a load synovial membrane self-adaption law.

In particular, to accommodate load variations of the robotic system, redesign is required

(understandably redesigned)

Is a load slide film self-adaptive law) so that the control performance of the controller is not significantly deteriorated when the robot is subjected to load variation. The sliding mode controller is used for ensuring control performance under complex disturbance and time delay errors, and the sliding mode surface is designed into a formula (11).

（11）

Wherein s is a sliding variable,

is a positive diagonal matrix, < >>

Is a positive constant.

According to formulas (10) and (11), formula (8) may be changed to formula (12):

（12）

in order to adapt to the condition that the load of the robot exists or the load suddenly changes, the self-adaptive time delay control method can be designed as a formula (13):

（13）

Substituting formula (11) into formula (12) and comparing with formula (8) to obtain the following relationship:

，

。

in equation (12), the error

Can be regarded as a pulsed disturbance input in closed loop dynamics (12); for a given +.>

The size of s in steady state is mainly determined by redesigned +.>

Determine->

Related to the response speed. Thus, redesign->

The larger s is, the smaller s is; however, redesign->

The size of (2) cannot be infinitely increased because it is subject to the stability condition of equation (9).

In addition, due to

Is determined under no-load conditions, thus, < >>

Equivalent to a constant gain, which can lead to two problems. The first problem is that after introducing the payload, the +.>

The increase in s is suddenly significant according to equations (5) and (10) and thus increases s, while the increase in s leads to a larger tracking error of the robot according to equation (12) and equation (11). Furthermore, a new constant is selected +.>

In the case of this, a second problem arises, namely the new constant +.>

Will become larger than before. However, when the payload is removed, the new gain becomes too large, which results in the stability condition of the robotic system not being met, making the robotic system unstable. Thus, both of the above problems need to be solved when delay control needs to be applied to robotic tasks involving considerable payload variations. I.e. when there is a load introduced, if a constant gain is set +. >

Too small to accommodate the robotic system in which the load is present; and if a comparatively large constant gain is set +.>

To accommodate the presence of a load, then in the event of a sudden change in load, due to the newly set constant gain +.>

Too large, the stability condition equation (9) cannot be satisfied, thereby making the robot system unstable.

In order to solve the two problems, the following step five is continued to obtain the adaptive gain.

Specifically, a load adaptive law is designed based on a sliding variable s

As in equation (14):

（14）

wherein:

（15）

alternatively, s is a sliding variable,

is a square function based on tracking error +.>

Is->

Value after one derivation, +.>

、/>

Is the i-th element of vector J, s, < >>

Is a diagonal matrix->

Diagonal elements on row i of (i); />

Is a right angle matrix ++>

Diagonal elements on row i of (i) determine gain +.>

Is used for adjusting the speed of the device; />

Is a very small normal number; />

Is->

And is also its initial value.

When the robotic system introduces a load, equation (5)

Enlarge (I)>

And also increases. From equation (10), the delay error is known>

Further, as can be seen from the formulas (11) and (12), the sliding variable s increases and the tracking error e also increases. These changes result in +.about.in equation (15) >

Increasing, it is thus possible to derive +.>

Is positive, wherein, due to +.>

Very small->

In formula (14), let +.>

Decrease until the minimum value is reached +.>

. When->

Keep at->

In this case, the formula (12) shows +.>

Exponentially decreasing, according to formula (15)>

Will decrease rapidly, thereby making +.>

Abrupt and abruptAnd (3) increasing. From the above analysis, the designed load self-adaptive time delay control can be effectively applied to the situations of existence of the load and abrupt load change of the robot system, but the gain of the time delay control cannot be directly input into the PID controller, and then the equivalent relation of the discrete domain is utilized for conversion.

Step six, converting into PID control.

Specifically, the gain of the adaptive delay control is converted into a gain applicable to the PID control by the equivalence relation between the discrete domain delay control and the PID control. The standard form of PID control, which is relatively common in industry, is mathematically represented as equation (16):

（16）

indicating proportional gain, ++>

And->

Represents the differential time and the integration time, at the same time, +.>

Is defined as +.>

，/>

For the desired joint displacement +.>

Represented as torque error caused by motor dc offset.

Closed loop systems incorporating equations (3) and (16) often exhibit inadequate control performance and instability due to the non-linear and uncertainty terms in equation (3). Thus, although K,

And->

Has a well-defined physical meaning, but these gains are typically set to be constant by heuristics. There is an equivalent relationship between the PID control and the delay control in the discrete domain, and the adaptive PID control is derived from this relationship, and these gains are equivalent according to the structure of the delay control, so that the adaptive PID control can also adapt to load changes.

Combining the contents of the above steps one to six, a PID control function in the discrete domain, equation (17), can be obtained.

（17）

the torque parameter value corresponding to the robot at the kth sampling time is represented, and L represents the sampling period. Considering the causal relationship in the discrete time domain, we can use +.>

Rather than +.>

. Equation (17) is then converted to a PID delta (speed) algorithm such as equation (18):

（18）

in addition, the adaptive delay control can adequately cope with significant load variation changes, and can be expressed in discrete form as formula (19):

（19）

wherein in the formula(19) In the process, the liquid crystal display device comprises a liquid crystal display device,

representing an adaptive symmetric gain matrix +.>

A positive diagonal matrix representing the expected error dynamics. />

Representing an estimate of the change in the payload in the robot dynamics,

indicating the corresponding adaptive gain of the robot, < > >

Indicating the desired placement of the error dynamics parameters.

Alternatively, the equivalence of PID and delay control in the discrete domain is demonstrated below.

Differential backward direction

And->

Substituting into equation (18) and equation (19) yields two control laws as follows:

PID control law:

（20）

time delay control law:

（21）

comparing the formula (20) with the formula (21), wherein the formula (20) and the formula (21) have the same functional structure; matching the parameters in equation (20) with the parameters in equation (21) yields the following PID gain selections, e.g., equation (22):

（22）

with these gains, the adaptive PID control is essentially a delay control in the form of PID control. It should be noted that in the formula (22)

Without loss of generality, it can be interpreted as the original derived medium constant matrix +.>

Is a self-adaptive version of (c).

Finally, an adaptive PID control is established. In particular, in the case where the payload variation is large, the gain

The adaptation of (c) will be performed per sampling time according to equation (14) and equation (15), wherein the load variation is made by +.>

To perform adaptive compensation.

It follows that the PID gain is determined by equation (22), equation (14) and equation (15). Further, introducing payload change changes

，/>

And->

In accordance with equation (15), the gain is then changed to accommodate the load change according to equation (14). The PID gain is continuously updated by equation (22). Further, while K is being updated, once according to +.>

Define the required error dynamics, +.>

And->

Will remain unchanged. However, is->

And->

Leaving unchanged does not mean that the adaptation is limited to the proportional gain K only. According to formula (15), the differential gain is +.>

And integral gain->

Both also become adaptive through K.

Alternatively, one is introduced by equation (14)

Diagonal element->

Equation (18) may be rewritten to yield equation (1):

（1）

in an alternative embodiment, the following provides a structural design when the robot control method in the present application is applied to an actual medical mechanical arm, and specifically relates to a real-time design of overall hardware and a sensor design for load change detection, as shown in fig. 2. The mechanical arm consists of modularized joints (such as modularized joint 1, modularized joint 2, modularized joint 3 and modularized joint n), the control system adopts a distributed control strategy based on a CAN bus, the upper computer adopts a high-performance industrial personal computer, the lower computer adopts a servo motion control system based on a DSP, and information is transmitted between the upper computer and the lower computer through the CAN bus.

As shown in fig. 2, each modular joint control system is composed of a DSP servo motion controller, a CAN bus interface card, a dc brushless motor, a photoelectric encoder, a brake drive, and the like. The industrial personal computer adopts a real-time system, and the torque calculated by the control algorithm is transmitted to the industrial personal computer for torque control. The sampling period L is determined by the ability of the computer to determine the control hardware, the smaller L the better the control performance, e.g., the sampling period L is selected to be l=0.001 s, the control loop operates at 1000 Hz.

In addition, to achieve detection of attachment and detachment of the payload, a six-axis load cell may be provided on the robot arm, as shown in fig. 3, mounted on the robot arm end holder for collecting data. The mechanical arm in fig. 3 further includes at least a joint A1, a joint A2, and a shutdown A3, and the six-axis load cell is a device for ensuring application accuracy of the robot. The sensor is specially designed for a robot joint, is usually arranged on the wrist of a robot arm, and measures three geometric coordinates

And torque or torque around it>

。

According to the derivation process of the following formula, the application provides the self-adaptive PID control method, based on the method, obvious load change can be dealt with, a complex model is not required to be constructed for load change detection, the self-adaptive dynamic gain is realized by introducing a time delay error for controlling torque input and acceleration and based on synovial membrane control, and the accuracy, the robustness and the stability inherited from the time delay control structure characteristic are maintained by the self-adaptive dynamic gain. In addition, through the equivalent relation of the time delay control and the PID control in the discrete domain, the corresponding PID control gain is extracted, and the method can be directly applied to the existing PID controller, and can directly obtain the self-adaptive control method under the condition of not knowing the time delay control.

Example 2

The embodiment of the present application also provides a robot control device for coping with load variation, and it should be noted that the robot control device for coping with load variation of the embodiment of the present application may be used to execute the robot control method for coping with load variation provided in embodiment 1 of the present application. The following describes a robot control device for coping with load variation provided in the embodiment of the present application.

Fig. 4 is a schematic view of an alternative robot control device that handles load changes according to an embodiment of the present application. As shown in fig. 4, the apparatus includes: the acquisition module 401 is used for acquiring torque parameters and position tracking errors of the robot at the current moment; an acquisition module 402, configured to acquire a sampling period corresponding to the robot, where the sampling period represents an interval duration of torque parameters of two adjacent acquisition robots; a determining module 403, configured to determine a first control parameter and a second control parameter according to the position tracking error and the sampling period, where the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used to compensate for a load change existing when the robot is controlled to move by the first control parameter; the control module 404 is configured to determine a target torque parameter of the robot at a target time according to the first control parameter, the second control parameter, and the torque parameter, and control the robot to move according to the target torque parameter, where the target time is located after the current time.

Optionally, the acquisition module includes: the device comprises an acquisition unit, an acquisition unit and a calculation unit. The acquisition unit is used for acquiring the actual displacement of the robot at the current moment; the acquisition unit is used for acquiring expected displacement corresponding to the robot at the current moment, wherein the expected displacement is realized by the expected robot at the current moment; and the calculating unit is used for calculating the difference value between the expected displacement and the actual displacement to obtain the position tracking error.

Optionally, the robot control device that handles load variation includes: a first computing module and a second computing module. The first calculation module is used for carrying out differential calculation on the sampling period to obtain differential time corresponding to the robot; and the second calculation module is used for carrying out integral calculation on the sampling period to obtain the integral time corresponding to the robot.

Optionally, the robot control device that handles load variation includes: a third calculation module and a fourth calculation module. The third calculation module is used for conducting derivative calculation on the position tracking error to obtain a first parameter; and the fourth calculation module is used for conducting derivative calculation on the first parameter to obtain a second parameter.

Optionally, the determining module includes: a first acquisition unit and a first determination unit. The first acquisition unit is used for acquiring the minimum value of the proportional gain corresponding to the robot; the first determining unit is used for determining a first control parameter according to the minimum value of the proportional gain, the differential time, the integral time, the first parameter, the second parameter, the position tracking error and the sampling period.

Optionally, the determining module includes: a second determination unit and a third determination unit. The second determining unit is used for determining a target gain corresponding to the robot based on the minimum value of the proportional gain, wherein the target gain is an adaptive gain for coping with load change; and the third determining unit is used for determining the second control parameter according to the target gain, the differential time, the integration time, the first parameter, the second parameter, the position tracking error and the sampling period.

Optionally, the second determining unit includes: a first acquisition subunit and a first calculation subunit. The first acquisition subunit is used for acquiring the self-adaptive total gain of the robot at the current moment; and the first calculating subunit is used for calculating the difference value between the minimum value of the self-adaptive total gain and the proportional gain to obtain the target gain.

Optionally, the control module includes: and the summing unit is used for summing the first control parameter, the second control parameter and the torque parameter to obtain the target torque parameter.

Example 3

According to another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to execute the robot control method of the above embodiment 1 for coping with load variation at the time of execution.

Example 4

According to another aspect of the embodiments of the present application, there is also provided an electronic device including one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the robot control method of the foregoing embodiment 1 that deals with load changes.

The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of units may be a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution, in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application and are intended to be comprehended within the scope of the present application.

Claims

1. A robot control method for coping with a load change, comprising:

acquiring torque parameters and position tracking errors of the robot at the current moment;

acquiring a sampling period corresponding to the robot, wherein the sampling period represents the interval duration of two adjacent times of acquisition of the torque parameters of the robot;

determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, wherein the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used for compensating load change existing when the robot is controlled to move by the first control parameter;

and determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter, and controlling the robot to move according to the target torque parameter, wherein the target moment is positioned after the current moment.

2. The method for controlling a robot to cope with a load variation according to claim 1, wherein collecting a position tracking error of the robot at a current time includes:

acquiring the actual displacement of the robot at the current moment;

acquiring expected displacement corresponding to the robot at the current moment, wherein the expected displacement is the displacement expected to be realized by the robot at the current moment;

and calculating the difference value between the expected displacement and the actual displacement to obtain the position tracking error.

3. The robot control method for coping with load variation according to claim 1, further comprising, after acquiring the sampling period corresponding to the robot:

performing differential calculation on the sampling period to obtain differential time corresponding to the robot;

and carrying out integral calculation on the sampling period to obtain the integral time corresponding to the robot.

4. The method according to claim 3, characterized in that before determining the first control parameter and the second control parameter from the position tracking error and the sampling period, the method further comprises:

Conducting derivative calculation on the position tracking error to obtain a first parameter;

and conducting derivative calculation on the first parameter to obtain a second parameter.

5. The method of controlling a robot to cope with a load variation according to claim 4, wherein determining a first control parameter from the position tracking error and the sampling period includes:

acquiring a minimum value of the proportional gain corresponding to the robot;

the first control parameter is determined from the minimum value of the proportional gain, the derivative time, the integral time, the first parameter, the second parameter, the position tracking error, and the sampling period.

6. The method of controlling a robot to cope with a load variation according to claim 5, wherein determining a second control parameter based on the position tracking error and the sampling period, comprises:

determining a target gain corresponding to the robot based on the minimum value of the proportional gain, wherein the target gain is an adaptive gain corresponding to the load change;

the second control parameter is determined based on the target gain, the derivative time, the integral time, the first parameter, the second parameter, the position tracking error, and the sampling period.

7. The method of controlling a robot to cope with a load variation according to claim 6, wherein determining a target gain corresponding to the robot based on a minimum value of the proportional gain, comprises:

acquiring the self-adaptive total gain of the robot at the current moment;

and calculating the difference value between the self-adaptive total gain and the minimum value of the proportional gain to obtain the target gain.

8. The method according to claim 1, wherein determining a target torque parameter of the robot at a target time based on the first control parameter, the second control parameter, and the torque parameter, comprises:

and summing the first control parameter, the second control parameter and the torque parameter to obtain the target torque parameter.

9. A robot control device for coping with a load change, comprising:

the acquisition module is used for acquiring torque parameters and position tracking errors of the robot at the current moment;

the acquisition module is used for acquiring a sampling period corresponding to the robot, wherein the sampling period represents the interval duration of two adjacent acquisition of the torque parameters of the robot;

The determining module is used for determining a first control parameter and a second control parameter according to the position tracking error and the sampling period, wherein the first control parameter is a constant PID parameter corresponding to the robot, and the second control parameter is used for compensating load change when the robot is controlled to move by the first control parameter;

and the control module is used for determining a target torque parameter of the robot at a target moment according to the first control parameter, the second control parameter and the torque parameter and controlling the robot to move according to the target torque parameter, wherein the target moment is positioned behind the current moment.

10. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and wherein the computer program, when executed, controls a device in which the computer-readable storage medium is located to execute the robot control method for coping with load change according to any one of claims 1 to 8.

11. An electronic device comprising one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of controlling a robot to cope with load changes of any of claims 1-8.