Robot follow-up control method, device, control terminal and storage medium

Abstract

The present invention relates to the field of robot control, and discloses a robot follow-up control method, device, control terminal and storage medium, the method comprising: establishing a tracking error model for the tracking error of the robot, and determining the control coefficient of the tracking error model according to a preset tracking error control range; the tracking error is the error between the target position and the actual position of the robot; determining the motor output control equation of the robot according to the tracking error model; obtaining the tracking error of the robot at the current moment and the motor output at the previous moment, determining the motor output at the current moment according to the motor output control equation, and controlling the robot according to the motor output. When there is a disturbance when the robot moves, the motor output of the robot at the current moment can be determined according to the set model, so that the tracking error is limited to a preset range.

Description

Technical Field

[0001] The present invention relates to the field of robot control, and in particular to a robot follow-up control method, device, control terminal and storage medium. Background Art

[0002] During the use of the robot, there are often certain errors between the arrival plane position and posture values ​​given to the robot and the arrival plane position and posture values ​​fed back by the robot.

[0003] In the traditional calculation process, a method similar to the switching function is often used to approximate and adjust the error. However, in the process of mode switching, the error will produce mode jitter, for example, there will be a difference between the ideal value and the actual value. The reasons for such a difference include parameter perturbation, external interference and various unmodeled dynamic characteristics. This makes the robot's tracking error converge slowly and difficult to control. Even if it converges, it converges in a large range, so that the system still has a large tremor, which reduces the robot's tracking robustness. Summary of the invention

[0004] In a first aspect, the present application provides a robot follow-up control method, comprising:

[0005] Establishing a tracking error model for the tracking error of the robot, and determining a control coefficient of the tracking error model according to a preset tracking error control range; the tracking error is the error between the target posture and the actual posture of the robot;

[0006] Determining a motor output control equation of the robot according to the tracking error model;

[0007] The tracking error of the robot at the current moment and the motor output at the previous moment are obtained, the motor output at the current moment is determined according to the motor output control equation, and the robot is controlled according to the motor output at the current moment.

[0008] Furthermore, the control coefficients include convergence coefficient, tremor coefficient and interference error;

[0009] The convergence coefficient is used to reflect the convergence speed of the tracking error, the chatter coefficient is used to reflect the boundary value of the tracking error, and the interference error is used to reflect the interference error of the entire robot system.

[0010] Furthermore, determining the control coefficient of the tracking error model according to a preset tracking error control range includes:

[0011] According to a preset tracking error control range, the first boundary, the second boundary and the third boundary of the tracking error are determined, and the relationship between the first boundary, the second boundary and the third boundary and the control coefficient is determined to determine each of the control coefficients.

[0012] Furthermore, the expression of the tracking error model is as follows:

[0013]

[0014] In the formula, e k+1 represents the tracking error at the next moment, e k represents the tracking error at the current moment, k as a subscript represents the current moment, k+1 represents the next moment, ρ is the convergence coefficient, ε is the tremor coefficient, d k+1 is the interference error at the next moment, is the compensation coefficient for the interference error at the next moment, sgn(e k ) means e k The positive and negative cases, when e k When sgn(e k ) is 1, when e k When sgn(e k ) is -1.

[0015] Furthermore, the relationship between the first boundary and the control coefficient is:

[0016]

[0017] In the formula, Δ MDR is the first boundary, used to reflect the convergence process of the tracking error in the monotonic interval, ρ is the convergence coefficient, ε is the chatter coefficient, where d u d l are the interference error d at the current moment respectively k The upper and lower bounds of

[0018] The relationship between the second boundary and the control coefficient is:

[0019]

[0020] In the formula, Δ AAL is the second boundary; used to reflect the oscillation convergence process of the tracking error;

[0021] The relationship between the third boundary and the control coefficient is:

[0022]

[0023] In the formula, Δ SSE is the third boundary, which is used to measure the final convergence interval of the tracking error.

[0024] Furthermore, the calculation expression of the interference error is:

[0025] d k =w k -w k-1 ;

[0026] Where W k is the interference amount at the current moment, W k-1 is the interference amount at the next moment, d k is the interference error at the current moment.

[0027] Furthermore, the calculation expression of the motor output control equation is as follows:

[0028]

[0029] In the formula, u k Indicates the motor output at the current moment, u k-1 Indicates the motor output at the last moment, e k represents the tracking error at the current moment, k as a subscript represents the current moment, k-1 is the previous moment, k-2 is the previous moment of k-1, ρ is the convergence coefficient, ε is the tremor coefficient, sgn(e k ) means e k The positive and negative cases, when e k When sgn(e k ) is 1, when e k When sgn(e k ) is -1, b1, b2, a1 and a2 represent the system parameters of the robot system respectively, y represents the actual position of the robot, r represents the target position of the robot, d k+1 is the interference error at the next moment, is the compensation coefficient for the interference error at the next moment.

[0030] In a second aspect, the present application further provides a robot follow-up control device, comprising:

[0031] A coefficient calculation module, used to establish a tracking error model for the tracking error of the robot, and determine the control coefficient of the tracking error model according to a preset tracking error control range; the tracking error is the error between the target position and the actual position of the robot;

[0032] A motor output module, used to determine the motor output control equation of the robot according to the tracking error model;

[0033] The control module is used to obtain the tracking error of the robot at the current moment and the motor output at the previous moment, determine the motor output at the current moment according to the motor output control equation, and control the robot according to the motor output at the current moment.

[0034] In a third aspect, the present application further provides a control terminal, comprising a processor and a memory, wherein the memory stores a computer program, and when the computer program runs on the processor, the robot follow-up control method is executed.

[0035] In a fourth aspect, the present application also provides a readable storage medium storing a computer program, which executes the robot follow-up control method when running on a processor.

[0036] The present invention discloses a robot follow-up control method, device, control terminal and storage medium, the method comprising: establishing a tracking error model for the tracking error of the robot, determining the control coefficient of the tracking error model according to a preset tracking error control range; the tracking error is the error between the target position and the actual position of the robot; determining the motor output control equation of the robot according to the tracking error model; obtaining the tracking error of the robot at the current moment and the motor output at the previous moment, determining the motor output at the current moment according to the motor output control equation, and controlling the robot according to the motor output. In the case of disturbance, the output of the current motor of the robot can be determined according to the set model, so that the tracking error is limited within the preset range, which can effectively ensure the stability of the robot during movement, eliminate the interference of the error, and realize the rapid correction of the tracking error. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope of protection of the present invention. In each of the drawings, similar components are numbered similarly.

[0038] Figure 1 A schematic diagram of a robot follow-up control method according to an embodiment of the present application is shown;

[0039] Figure 2 A simulation schematic diagram of a robot follow-up control method according to an embodiment of the present application is shown;

[0040] Figure 3 A schematic diagram of an interface of a robot follow-up control device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0042] The components of the embodiments of the present invention generally described and shown in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0043] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present invention, are intended only to indicate specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items or adding the possibility of one or more features, numbers, steps, operations, elements, components or combinations of the foregoing items.

[0044] Furthermore, the terms “first”, “second”, “third”, etc. are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0045] Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meanings as those generally understood by those skilled in the art to which the various embodiments of the present invention belong. The terms (such as those defined in generally used dictionaries) will be interpreted as having the same meanings as the contextual meanings in the relevant technical field and will not be interpreted as having idealized meanings or overly formal meanings unless clearly defined in the various embodiments of the present invention.

[0046] The technical solution of the present application is applied to the tracking control process of the robot, and a tracking error model is used to control the robot's motor output to ensure that the tracking error caused by the robot's motor output controlling the robot's movement is within a preset range, thereby ensuring the robot's stability.

[0047] Next, the technical solution of the present application is described with specific embodiments.

[0048] Example 1

[0049] like Figure 1 As shown, this application includes the following steps:

[0050] Step S100: establishing a tracking error model for the tracking error of the robot, and determining a control coefficient of the tracking error model according to a preset tracking error control range.

[0051] When the robot moves, the target position is set, and the planning algorithm determines the path and posture of the robot to reach the target position, and then drives the motor to move along the planned path. It can be seen that the output of the motor is the key to realizing the above planning. By outputting the appropriate output force, the robot moves along the planned path. In actual movement, due to external or internal interference, as well as system errors and other reasons, the motor outputs according to the calculated output force. After executing the planned movement, the actual position reached by the robot and the posture when it reaches the actual position are different from the planned position and posture, that is, the difference between the target posture and the actual posture, forming a tracking error.

[0052] For example, in an actual robot system, let r k is the target pose, y k is the actual pose, then the tracking error can be defined as e k =r k -y k .

[0053] The subscript k refers to the moment. In this embodiment, k is the current moment. The moment is determined by the sampling time of the robot. The shorter the sampling time, the shorter the time interval between moments. Otherwise, the longer it is. Therefore, it can be understood that the tracking of the robot motion in this embodiment is a discrete motion system. Considering the influence of external interference on the robot motion state described by single input and single output, it can be expressed as:

[0054] A(q -1 )y k =B(q -1 ) k +w k .

[0055] u k is the theoretical output of the robot motor at the current moment, y k is the position coordinate of the robot at the current moment, w k is the interference, A(q -1 ) and B(q -1 ) is the delay operator q -1 Polynomial of:

[0056] A(q -1 )=1+a1q -1 +...+a n q -n

[0057] B(q -1)=b1q -1 +...+b m q -m ,b≠0

[0058] Where a1,...,a n ,b1,...,b m is the robot system parameter, and 1≤m≤n.

[0059] The present invention aims to obtain the appropriate motor output u k , so that the above tracking error e k It can be stabilized in a convergence range as much as possible. To this end, a tracking error model can be established for the tracking error to limit the tracking error. In other words, the tracking error needs to be controlled within a reasonable control range to ensure the stability of the robot's motion. The control range includes the convergence range of the tracking error and the convergence method of the tracking error.

[0060] The tracking error model of the present application is used to control the convergence of the tracking error so that the tracking error can converge quickly and stably within an ideal range in the robot system. It can be understood that, combined with the above discrete time system expression and the robot dynamics equation, the tracking error of the robot at the next moment is related to the tracking error at the current moment, the interference in the robot system and other elements. Therefore, the tracking error model expression of the present application is as follows:

[0061]

[0062] In the formula, e k represents the tracking error at the current moment, k as a subscript represents the current moment, k+1 represents the next moment, ρ is the convergence coefficient, ε is the tremor coefficient, d k+1 is the interference error, is the compensation coefficient for interference error, sgn(e k ) means e k The positive and negative cases, when e k When sgn(e k ) is 1, when e k When sgn(e k ) is -1.

[0063] Among them, the sat function used in the formula is used to achieve different adjustments according to the errors in different situations. For example, the actual posture is left, right or up compared to the target posture. In terms of distance, the deviation value may be the same, but different directions have different deviations. In addition, according to the definition of the sat function, the tracking error can converge quickly, and the deviations in different situations can also fluctuate as smoothly as possible within the convergence range. The fluctuation of the tracking error is reduced, which can enhance the stability of the robot during movement.

[0064] The d in the formula is the interference error, which is the difference between the interference of the system at the current moment and the interference of the system at the previous moment. Its calculation expression is:

[0065] d k =w k -w k-1

[0066] Where W is the interference in the robot system, which can be various unmodeled dynamic characteristics such as parameter perturbation, gravity, friction, internal damping of the system, etc. In actual working scenarios, these interferences will not exist or take effect in real time, but often affect the movement of the robot in some form in some cases. In this embodiment, an interference model is established for these interferences to calculate the interference amount, so the interference amount is a known quantity. k is the interference error at the current moment, that is, the difference between the interference amount at the current moment and the interference amount at the previous moment. * As a compensation coefficient, it is used to balance the influence of the interference error on the above tracking model. In the tracking error model of this embodiment, the interference error is bounded, that is, the interference error converges within a range, then there is a compensation coefficient

[0067] Among them, d u d l are the interference errors d k The upper and lower bounds, that is, the maximum and minimum values ​​of the interference error, can be calculated based on the interference model and are certain values. It can be understood that if the upper and lower bounds are opposite numbers to each other, the compensation coefficient is 0.

[0068] This application does not discuss how to model the interference model. For example, the interference model expression can be:

[0069] w k =0.12*|mod(k,40)-20|+0.18*|mod(k+4,40)-20|.

[0070] The interference error d can be calculated based on this model k The expression of , thus obtaining the upper bound d u and the lower bound dl , and then get the corresponding compensation coefficient The above interference model is established after multiple data collections based on the robot's motion environment. It can be considered that the interference model is related to the robot itself and the robot's working environment. Therefore, as long as the interference model is obtained, the corresponding interference error and compensation coefficient can be obtained.

[0071] It can be understood that the interference error d is a simulation and feedback of the interference quantity. k+1 The interference error of the robot system at the next moment is used to adapt the tracking error scenario at the next moment as much as possible, thereby estimating and pre-controlling the tracking error.

[0072] For example, if the current moment is the first moment, then e1=r1-y1 exists, where r1 and y1 can be determined by reading the motor data and obtaining the robot position, and the tracking error at the current moment can be determined. The compensation coefficient is a fixed value, and the interference error d2 at the second moment can be calculated by the interference model of the interference quantity, so the tracking error e2 at the next moment can be planned by combining the measurement value of the tracking error obtained at the first moment with the above tracking error model.

[0073] Among them, the convergence coefficient is used to control the convergence speed of the tracking error, the chatter coefficient is used to control the chatter of the tracking error within the convergence range, and the interference error represents the external or internal interference of the entire robot system, so that the tracking error model can take into account the tracking error caused by the interference signal.

[0074] The above-mentioned settings of convergence coefficient and tremor coefficient are used to reflect the convergence properties of tracking parameters. In order to better describe and limit the convergence process of tracking parameters, the convergence of tracking parameters can be reflected in three elements: convergence interval, monotonic convergence of tracking error outside the convergence interval, and oscillatory convergence within the convergence interval. Therefore, the convergence effect of the tracking convergence model can be limited according to the three boundaries related to these three elements.

[0075] where the first boundary Δ is defined MDR It is used to reflect the convergence process of the tracking error in the monotonic interval, that is, when the tracking error is outside the convergence interval and converges to the convergence interval, the speed of this interval is similar to the derivative.

[0076] The formula for the first boundary is described as:

[0077] It is understandable that when the tracking error is greater than the convergence interval, it needs to be monotonically decreasing, and when the tracking error is less than the convergence interval, it needs to be monotonically increasing, and it is best not to over-correct, which can be understood as the rate of change of the tracking error within the monotonic interval. The rate of change must ensure that the tracking error quickly enters the convergence interval, but ensure that it does not converge too quickly, so as to cross the 0 point, so that the correction amplitude is too large.

[0078] Second boundary Δ AAL It is used to reflect the oscillation convergence process of the tracking error, that is, the state when the tracking error oscillates and converges within the convergence interval.

[0079] The formula for the second boundary is described as.

[0080]

[0081] The second boundary represents the rate of change of the tracking error in the oscillation interval, reflecting the speed of the oscillation of the tracking error in the convergence interval, the amplitude of each oscillation, and the stability of the tracking error, that is, the slope of the tracking error in the convergence interval.

[0082] The third boundary Δ SSE Used to measure the final convergence interval of the tracking error.

[0083] The formula for the third boundary is described as:

[0084] Wherein, K* is a positive integer.

[0085] For example, if the third boundary is 4, it means that the tracking error will converge to the interval [-4,4].

[0086] In this embodiment, by determining the relationship between the above three boundaries and each parameter, the value of each parameter can be determined. The specific relationship between the three boundaries and each parameter can be obtained by combining the formula description of each boundary and the derivation of the tracking error model expression. The specific relationship formulas are as follows:

[0087] definition Indicates the average distance of the interference error from the zero point.

[0088] Through the formula description of the first boundary and the above tracking error model, we can know that:

[0089] Knowable

[0090] When e k >0, make 0 < e k+1 <e k .

[0091] Needs to be satisfied

[0092] From the above formula, we can get:

[0093] e k >ε+Δ,ε>Δ,ρ=0

[0094]

[0095] Similarly, k When <0, there is

[0096] Then rearranging the above formula we can get is a decreasing function with respect to ε; is an increasing function about ε. After rearrangement, the relationship between the first boundary and the control coefficient is:

[0097]

[0098] For the second boundary, the convergence interval of the tracking error is generally near the zero point. When it is greater than 0, it should be reduced, and when it is less than 0, it should be increased. Therefore, when e k >0, by We can get:

[0099] e k+1 ≤(1-ρ)e k -ε+Δ

[0100] e k+1 ≥(1-ρ)e k -ε-Δ

[0101] To make |e k |Satisfies monotonically decreasing, that is, -e k <e k+1 <e k

[0102] (1-ρ)e k -ε+Δ<e k

[0103] -e k <(1-ρ)e k -ε-Δ

[0104] Rearranging the above formula yields:

[0105] e k >ε+Δ,ε>Δ,ρ=0

[0106]

[0107] When e k <0 exists:

[0108] e k <-ε-Δ,ε>Δ,ρ=0

[0109]

[0110] After arranging the above formula, we can know that is a decreasing function with respect to ε; is an increasing function about ε. k >0 and e k When <0, the relationship between the second boundary and the control coefficient is:

[0111]

[0112] The third boundary is the limit of the convergence range of the tracking error. Considering the disturbance, the third boundary can be defined as the following two cases for discussion:

[0113] C1:

[0114] C2:

[0115] Where 0<α≤1.

[0116] When C1 occurs:

[0117] When 0<e k ≤Δ SSE When exists:

[0118] -Δ SSE ≤(1-ρ)e k -ε-Δ

[0119] (1-ρ)e k +Δ≤Δ SSE .

[0120] because is a decreasing function of ε, Δ+ε is an increasing function of ε, and there exists Therefore, the relationship between the third boundary and the control coefficient in the case of c1 is:

[0121]

[0122]

[0123]

[0124] When C2

[0125] αΔ SSE ≤e k+1 ≤Δ SSE

[0126] αΔ SSE≤(1-ρ)e k -ε-Δ

[0127] (1-ρ)e k -ε+Δ≤Δ SSE

[0128] After finishing, we can get:

[0129] -ε-Δ>0,ρ=0

[0130]

[0131]

[0132] When -Δ SSE ≤e k+1 ≤-αΔ SSE hour

[0133] -Δ SSE ≤(1-ρ)e k -ε-Δ

[0134] (1-ρ)e k -ε+Δ≤-αΔ SSE

[0135] After finishing, we can get:

[0136]

[0137]

[0138]

[0139] It can be seen from the above formula that the interval given by the third boundary is a maximum boundary. For example, when the third boundary is 4, the convergence interval is [-4,4], while the actual tracking error may converge in the interval [-2,4]. That is, the third boundary is used to impose a maximum limit on the tracking error.

[0140] By setting the above three boundaries, a relationship between the three boundaries and the control coefficients, the coefficient values ​​of each control coefficient can be obtained by the simultaneous relationship.

[0141] The first boundary, the second boundary and the third boundary are set according to the robot's own working environment, robot structural parameters, system parameters, control mode, control accuracy and other aspects. Taking the third boundary as an example, by setting an ideal third boundary, the above control coefficient is limited. At that time, there must be errors for the robot movement. Therefore, even if the third boundary is set to 0, it is impossible to truly converge the tracking error to 0. In addition, for the first boundary and the second boundary, the rate of change of the control tracking error in the monotonic interval and the convergence interval, it can be understood that the faster it converges to the convergence interval, the better, but the faster the change speed, there is also the possibility of over-correction, so it also needs to be set according to the actual situation.

[0142] Step S200, determining the motor output control equation of the robot according to the tracking error model.

[0143] It can be understood that when the robot moves, the motor output at the current moment controls the actual position of the robot at the next moment, thereby generating a tracking error at the next moment. Therefore, it can be considered that the motor output at the current moment affects the tracking error at the next moment. Therefore, it is only necessary to calculate the motor output at the current moment to control the tracking error.

[0144] For example, the robot system in step S100 is expressed as follows when in motion:

[0145] A(q -1 )y k =B(q -1 ) k +w k .

[0146] Combining this expression with the above tracking error model:

[0147]

[0148] We can find out about u k The motor output control equation is as follows:

[0149]

[0150] Wherein, b1, b2, a1 and a2 represent the system parameters in the above robot system. The system parameters are parameters set according to the robot system itself, which are determined by the structure of the robot and other factors, and are not discussed in this application. After solving the above motor output control equation, the motor output at the current moment can be obtained according to the above expression.

[0151] Step S300, obtaining the tracking error of the robot at the current moment and the motor output at the previous moment, determining the motor output at the current moment according to the motor output control equation, and controlling the robot according to the motor output at the current moment.

[0152] The above-mentioned system parameters are set according to the robot system itself and are known values. The above-mentioned robot position coordinates, motor output and tracking error at time k and before are all known values ​​and can be obtained by real-time sampling of the motion state of the robot motor. The above-mentioned various control coefficients can be calculated or established in the manner in step S100. Therefore, each time the tracking error at the current moment is read, the motor output can be controlled according to the convergence condition of the tracking error model. The theoretical output value of the motor at the current moment is determined by the size and direction of the current tracking error, so that the output of the motor at the next moment can make the tracking error converge to the convergence interval, or maintain it in the convergence interval.

[0153] like Figure 2 As shown in the figure, it is a simulation diagram of tracking error. In this figure, the first boundary is set to 0.8571, the second boundary is set to 0.3529, and the third boundary is set to 0.6. Then the corresponding control coefficients can be obtained as ρ=0.3 and ε=0.45 respectively. Because the disturbance is taken into account, a disturbance signal model R needs to be customized:

[0154] R=Cw k =C*0.12*|mod(k,40)-20|+0.18*|mod(k+4,40)-20|

[0155] C is an adjustable parameter of the disturbance, which is used to adjust the disturbance signal in the simulation, and mod is the modulus operator.

[0156] Figure 2 Each hollow circle in the figure is sampled according to the sampling interval, and the tracking error coordinate point is calculated. It can be seen that the variation between the sampling point outside the convergence interval and the nearest point is much larger than the variation between the two adjacent coordinate points within the convergence interval, which corresponds to the values ​​of the first and second boundaries mentioned above, and its convergence interval [-0.6, 0.6] is also located in the third boundary.

[0157] exist Figure 2 In the proposed method, the tracking error converges quickly outside the convergence interval, which realizes the rapid correction of the tracking error. In the convergence interval, the convergence speed is low, and the oscillation convergence mode is stable, which ensures the stability of the robot during movement.

[0158] This embodiment establishes a tracking error model to perform convergence limit on the tracking error, so that the tracking error can be limited according to the actual situation and the working requirements of the robot, thereby obtaining the motor output at the current moment, and achieving more precise control of the motor output, so that the tracking error caused by the robot in actual movement converges to an acceptable range, and can also control the convergence speed of the error and the convergence form in the convergence interval, thereby ensuring the steady state of the robot during movement as much as possible, and ensuring the stability of the robot's work.

[0159] like Figure 3 As shown, a robot follow-up control device comprises:

[0160] The coefficient calculation module 10 is used to establish a tracking error model for the tracking error of the robot, and determine the control coefficient of the tracking error model according to a preset tracking error control range; the tracking error is the error between the target position and the actual position of the robot;

[0161] A motor output module 20, used to determine the motor output control equation of the robot according to the tracking error model;

[0162] The control module 30 is used to obtain the tracking error of the robot at the current moment and the motor output at the previous moment, determine the motor output at the current moment according to the motor output control equation, and control the robot according to the motor output.

[0163] The present application also provides a control terminal, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is run on the processor, the robot follow-up control method is executed. The control terminal can be a host computer for controlling the movement of the robot, such as a computer, or a control device placed inside the robot, such as a built-in computer.

[0164] The present application also provides a readable storage medium storing a computer program, wherein the computer program executes the robot follow-up control method when running on a processor. The storage device may be a device that can store data, such as a hard disk, a memory, or a cache.

[0165] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or the flow chart, and the combination of boxes in the structure diagram and / or the flow chart, can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0166] In addition, the functional modules or units in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0167] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0168] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A robot follow-up control method, characterized in that: include: Establishing a tracking error model for the tracking error of the robot, and determining a control coefficient of the tracking error model according to a preset tracking error control range; The tracking error is the error between the target position and the actual position of the robot; Determining a motor output control equation of the robot according to the tracking error model; Obtaining the tracking error of the robot at the current moment and the motor output at the previous moment, determining the motor output at the current moment according to the motor output control equation, and controlling the robot according to the motor output at the current moment; The control coefficients include convergence coefficient, tremor coefficient and interference error; The convergence coefficient is used to reflect the convergence speed of the tracking error, the chatter coefficient is used to reflect the boundary value of the tracking error, and the interference error is used to reflect the interference error of the entire robot system; The expression of the tracking error model is as follows: Where ek+1 represents the tracking error at the next moment, ek represents the tracking error at the current moment, k as a subscript represents the current moment, k+1 represents the next moment, ρ is the convergence coefficient, ε is the tremor coefficient, and d k+1 is the interference error at the next moment, is the compensation coefficient for the interference error at the next moment, sgn(e k ) indicates the positive or negative condition of ek. When ek is greater than or equal to 0, sgn(e k ) is 1, when ek is less than 0, then sgn(e k ) is -1; Determining the control coefficient of the tracking error model according to a preset tracking error control range includes: According to a preset tracking error control range, determining a first boundary, a second boundary and a third boundary of the tracking error, and determining the relationship between the first boundary, the second boundary and the third boundary and the control coefficient respectively, so as to determine each of the control coefficients; The first boundary is used to reflect the convergence process of the tracking error in the monotonic interval; The second boundary is used to reflect the oscillation convergence process of the tracking error; The third boundary is used to measure the final convergence interval of the tracking error; The calculation expression of the motor output control equation is as follows: In the formula, u k Indicates the motor output at the current moment, u k-1 Indicates the motor output at the last moment, e k represents the tracking error at the current moment, k as a subscript represents the current moment, k-1 is the previous moment, k-2 is the previous moment of k-1, ρ is the convergence coefficient, ε is the tremor coefficient, sgn(e k ) indicates the positive or negative condition of ek. When ek is greater than or equal to 0, sgn(e k ) is 1, when ek is less than 0, then sgn(e k ) is -1, b1, b2, a1 and a2 represent the system parameters of the robot system respectively, y represents the actual position of the robot, r represents the target position of the robot, d k+1 is the interference error at the next moment, is the compensation coefficient for the interference error at the next moment.

2. The robot follow-up control method according to claim 1, characterized in that: The relationship between the first boundary and the control coefficient is: In the formula, Δ MDR is the first boundary, used to reflect the convergence process of the tracking error in the monotonic interval, ρ is the convergence coefficient, ε is the chatter coefficient, where d u ,d l are the interference error d at the current moment respectively k The upper and lower bounds of The relationship between the second boundary and the control coefficient is: In the formula, Δ AAL is the second boundary; used to reflect the oscillation convergence process of the tracking error; The relationship between the third boundary and the control coefficient is: In the formula, Δ SSE is the third boundary, which is used to measure the final convergence interval of the tracking error.

3. The robot follow-up control method according to claim 1, characterized in that: The calculation expression of the interference error is: d k =w k -w k-1 ; Where W k is the interference amount at the current moment, W k-1 is the interference amount at the next moment, d k is the interference error at the current moment.

4. A robot follow-up control device, characterized in that: The device is used to execute the robot follow-up control method according to any one of claims 1 to 3, comprising: A coefficient calculation module, used to establish a tracking error model for the tracking error of the robot, and determine the control coefficient of the tracking error model according to a preset tracking error control range; the tracking error is the error between the target position and the actual position of the robot; A motor output module, used to determine the motor output control equation of the robot according to the tracking error model; The control module is used to obtain the tracking error of the robot at the current moment and the motor output at the previous moment, determine the motor output at the current moment according to the motor output control equation, and control the robot according to the motor output at the current moment.

5. A control terminal, characterized in that: The invention comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is run on the processor, the robot follow-up control method according to any one of claims 1 to 3 is executed.

6. A readable storage medium, characterized in that: The device stores a computer program, which executes the robot follow-up control method according to any one of claims 1 to 3 when running on a processor.

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