Stability control method and system for multi-joint mechanical arm of sand blasting robot

Abstract

The invention belongs to the technical field of industrial robot mechanical arm control, and provides a stability control method and system for a multi-joint mechanical arm of a sand blasting robot, and the method comprises the steps: obtaining a dynamic model of the multi-joint mechanical arm of the sand blasting robot; adopting a time-varying convergence function of a stable preset finite time control strategy to perform state transformation on the obtained dynamic model to obtain a virtual control signal and an actual control input signal of the dynamic model; and the stability of the dynamic model is analyzed based on the obtained virtual control signal and the actual control input signal, a stable point of the dynamic model is determined, the actual torque of the mechanical arm is controlled to be kept continuous on the two sides of the determined stable point correspondingly, and stability control over the multi-joint mechanical arm of the sand blasting robot is completed according to the actual torque of the mechanical arm.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial robot manipulator arm control, and in particular relates to a stability control method and system for a multi-joint manipulator arm of a sandblasting robot. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] With the rapid development of robotics, multi-joint sandblasting robot arms are widely used in industrial production, precision manufacturing, and medical fields. However, the effects of gun recoil, external disturbances, and unknown parameters can cause traditional preset-time control methods to cause the controller to lose control after the preset time. This is especially true when the sandblasting robot arm joints require high precision control and are subject to strong external disturbances. Problems such as poor stability, slow response, and severe jitter often occur, leading to poor control results. Existing control methods, including proportional-integral-differential control, fuzzy control, and model-based control, often fail to maintain good robustness and stability in the face of external disturbances in complex environments. In particular, when using stable control strategies, jitter is prone to occur, affecting the accuracy of the sandblasting robot arm and the overall performance of the system. Summary of the Invention

[0004] To solve the above problems, the present invention proposes a stability control method and system for a multi-joint robotic arm of a sandblasting robot, which suppresses the influence of gun recoil, external disturbances and unknown parameters within a preset time, and maintains stability during the disturbance and stabilization process, thereby solving the problem of the original preset time control method in the prior art that the control signal is reset to zero after the preset time point and cannot handle the influence of external disturbances, system unknowns and gun recoil, thereby causing system crash and the problem of possible jitter during external disturbances and control stabilization, affecting the accuracy of the robotic arm and the overall performance of the system; and improving the stability and reliability of the preset finite time dual-mode control end of the multi-joint robotic arm of the sandblasting robot.

[0005] According to some embodiments, a first solution of the present invention provides a stability control method for a multi-joint manipulator arm of a sandblasting robot, which adopts the following technical solution: A stability control method for a multi-joint mechanical arm of a sandblasting robot, comprising: Obtain the dynamic model of the multi-joint manipulator of the sandblasting robot; The obtained dynamic model is transformed into a state by using a time-varying convergence function of a stable preset finite-time control strategy to obtain a virtual control signal and an actual control input signal of the dynamic model; The stability of the dynamic model is analyzed based on the obtained virtual control signal and the actual control input signal, and the stable point of the dynamic model is determined. The actual torque of the robotic arm is controlled to maintain continuity on both sides of the determined stable point. The stability control of the multi-joint robotic arm of the sandblasting robot is completed according to the actual torque of the robotic arm.

[0006] As a further technical limitation, the dynamic model of the multi-joint manipulator of the sandblasting robot is constructed as follows: ;in, is the vector of the link joint angle, is the joint angle The inertia matrix, is the Coriolis force and centrifugal force matrix, is the friction force vector, is the gravity vector, is the control input, is an external disturbance, is the joint rotation acceleration, is the joint rotation speed.

[0007] As a further technical limitation, the time-varying convergence function used is for ;in, is the actual convergence time of the robotic arm system, For preset time, is the running time of the robotic arm system; the state of the obtained dynamic model is transformed by combining the time-varying convergence function, and the state of the multi-joint robotic arm of the sandblasting robot is converted into an error variable through time-varying transformation to obtain the virtual control signal of the dynamic model and the actual control input signal .

[0008] As a further technical limitation, in the process of analyzing the stability of the dynamic model, the convergence of the dynamic model is analyzed by using the Lyapunov equation, and the stable point is determined by combining it with Young's inequality. The control signal is switched at the determined stable point to complete the stable control of the robotic arm.

[0009] As a further technical limitation, before reaching the stable point, by analyzing the convergence of each state of the dynamic model, all states of the dynamic model tend to zero when reaching the stable point.

[0010] As a further technical limitation, when a stable point is reached, the control torque of the dynamic model is maintained, and the actual control input signal is kept smooth at the stable point for a preset time.

[0011] According to some embodiments, a second solution of the present invention provides a stability control system for a multi-joint manipulator arm of a sandblasting robot, which adopts the following technical solution: A stability control system for a multi-joint mechanical arm of a sandblasting robot, comprising: an acquisition module configured to acquire a dynamic model of a multi-joint manipulator arm of a sandblasting robot; a transformation module configured to perform a state transformation on the acquired dynamic model using a time-varying convergence function of a stable preset finite-time control strategy to obtain a virtual control signal and an actual control input signal of the dynamic model; The control module is configured to analyze the stability of the dynamic model based on the obtained virtual control signal and the actual control input signal, determine the stability point of the dynamic model, control the actual torque of the robotic arm on both sides of the determined stability point to maintain continuity, and complete the stability control of the multi-joint robotic arm of the sandblasting robot according to the actual torque of the robotic arm.

[0012] According to some embodiments, a third solution of the present invention provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps of the stability control method for a multi-joint mechanical arm of a sandblasting robot as described in the first embodiment of the present invention.

[0013] According to some embodiments, a fourth solution of the present invention provides an electronic device, which adopts the following technical solution: An electronic device comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps of the stability control method of the multi-joint mechanical arm of a sandblasting robot as described in the first embodiment of the present invention are implemented.

[0014] According to some embodiments, a fifth solution of the present invention provides a computer program product, which adopts the following technical solution: A computer program product includes software code, wherein the program in the software code executes the steps of the stability control method of the multi-joint mechanical arm of a sandblasting robot as described in the first embodiment of the present invention.

[0015] Compared with the prior art, the present invention has the following beneficial effects: In order to address the problems in the prior art where the original preset time control method sets the control signal to zero after the preset time point and is unable to handle the influence of external disturbances, system unknowns and spray gun recoil, thus causing system crashes and possible jitters during external disturbances and control stabilization, affecting the accuracy of the robotic arm and the overall performance of the system; the present invention suppresses the influence of spray gun recoil, external disturbances and unknown parameters within the preset time, maintains stability during the disturbance and stabilization process, and improves the stability and reliability of the preset finite time dual-mode control terminal of the multi-joint robotic arm of the sandblasting robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings constituting a part of the specification of this embodiment are used to provide a further understanding of this embodiment. The schematic embodiments and descriptions of this embodiment are used to explain this embodiment and do not constitute an improper limitation on this embodiment.

[0017] Figure 1 This is a flow chart of a stability control method for a multi-joint mechanical arm of a sandblasting robot in Embodiment 1 of the present invention; Figure 2 Schematic diagram of the steps of the stability control method of the multi-joint mechanical arm of the sandblasting robot in the first embodiment of the present invention; Figure 3 : This is a comparison diagram of the response process of the joint angle position of the sandblasting robot manipulator arm in the first embodiment of the present invention under stable preset finite time, proportional-integral-differential, and finite time control respectively; wherein, Figure 3 (a) is the joint angle Response process comparison chart, Figure 3 (b) is the joint angle Response process comparison chart; Figure 4 1 is a comparison diagram of the response process of the joint angular velocity of the sandblasting robot manipulator arm in the first embodiment of the present invention under the stable preset finite time, proportional-integral-differential, and finite time control respectively; wherein, Figure 4 (a) is the joint angular velocity Response process comparison chart, Figure 4 (b) is the joint angular velocity Response process comparison chart; Figure 5 : This is a comparison diagram of the response process of the input torque of the sandblasting robot arm joint in the first embodiment of the present invention under stable preset finite time, proportional-integral-differential, and finite time control respectively; wherein, Figure 5 (a) is the input torque Response process comparison chart, Figure 5 (b) is the input torque Response process comparison chart; Figure 6 This is a comparison diagram of the convergence process of the joint angle position of the sandblasting robot manipulator arm in the first embodiment of the present invention under the stable preset finite time and the latest preset finite time control; wherein, Figure 6 (a) is the joint angle Response process comparison chart, Figure 6 (b) is the joint angle Response process comparison chart; Figure 7This is a comparison diagram of the convergence process of the angular velocity of the sandblasting robot arm joint in the first embodiment of the present invention under the stable preset finite time and the latest preset finite time control; wherein, Figure 7 (a) is the joint angular velocity Response process comparison chart, Figure 7 (b) is the joint angular velocity Response process comparison chart; Figure 8 : This is a comparison diagram of the response process of the input torque of the sandblasting robot arm joint in the first embodiment of the present invention under the stable preset finite time and the latest preset finite time control; wherein, Figure 8 (a) is the input torque Response process comparison chart, Figure 8 (b) is the input torque Response process comparison chart; Figure 9 This is a structural block diagram of a stability control system of a multi-joint mechanical arm of a sandblasting robot in Example 2 of the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0019] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0020] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0021] In the present invention, terms such as "upper", "lower", "left", "right", "front", "back", "vertical", "horizontal", "side", "bottom", etc. indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. They are relational words determined only for the convenience of describing the structural relationships of the various parts or elements of the present invention, and do not specifically refer to any part or element in the present invention, and should not be understood as limiting the present invention.

[0022] In the present invention, terms such as "fixed connection," "connected," and "connection" should be interpreted broadly to mean a fixed connection, an integral connection, or a detachable connection; a direct connection or an indirect connection through an intermediary. Relevant researchers or technicians in this field may determine the specific meanings of these terms in the present invention based on specific circumstances, and they should not be construed as limitations of the present invention.

[0023] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0024] Example 1 Embodiment 1 of the present invention introduces a stability control method for a multi-joint mechanical arm of a sandblasting robot.

[0025] like Figure 1 and Figure 2 A stability control method for a multi-joint manipulator arm of a sandblasting robot is shown, comprising: Obtain the dynamic model of the multi-joint manipulator of the sandblasting robot; The obtained dynamic model is transformed into a state by using a time-varying convergence function of a stable preset finite-time control strategy to obtain a virtual control signal and an actual control input signal of the dynamic model; The stability of the dynamic model is analyzed based on the obtained virtual control signal and the actual control input signal, and the stable point of the dynamic model is determined. The actual torque of the robotic arm is controlled to maintain continuity on both sides of the determined stable point. The stability control of the multi-joint robotic arm of the sandblasting robot is completed according to the actual torque of the robotic arm.

[0026] As one or more implementation methods, a dynamic model of the multi-joint manipulator of the sandblasting robot is established, namely ; in, is the vector of the link joint angle, is the joint angle The inertia matrix, is the Coriolis force and centrifugal force matrix, is the friction force vector, is the gravity vector, is the control input, is an external disturbance, is the joint rotation acceleration, Joint rotation speed.

[0027] Through state changes 、 and control inputs , the dynamic model can be transformed into a strict feedback form, namely: ; in, , , , is the system output.

[0028] The stable pre-set finite time time-varying convergence function is defined as: ; in, is a constant, For the preset time, meet .make , and when hour, ,at the same time ( is a positive constant); when hour, .

[0029] As one or more implementations, the sandblasting robot arm state is converted into an error variable through a time-varying transformation: (1) In Time: Error variable and Defined as: ; ; in, , , .

[0030] The error variable is specifically , , Represents the virtual control input for subsequent design, where , .

[0031] Design virtual control signals and actual control inputs; that is, virtual control signals for ; Actual control input for ;in, , , , is a positive definite diagonal matrix, is the identity matrix.

[0032] As one or more implementation methods, this embodiment analyzes the convergence of the system through the Lyapunov function, which is: ; ; The derivative of is derived as: ; Using Young's inequality, we can get: .

[0033] Substituting into the above formula we can get: .

[0034] because , and , we can get ,and ; .

[0035] Since the virtual control signal yes and The function of The derivative of can be expressed as: ; Similarly, The derivative of can be expressed as: ; according to , and , we can get ,and ; Substitute into We can get: .

[0036] Then the actual controller Substitution ,have to: .

[0037] (2) In Time: Error variable and Defined as: ; ; in, , .

[0038] This embodiment proves through stability analysis that the chattering problem of the traditional switching controller does not occur at the control signal switching point.

[0039] At the preset time After that, the controller converts to , ;in, , is a positive definite diagonal matrix, ensuring that the system state is The global asymptotic stability is achieved.

[0040] The same logic applies : .

[0041] In summary, its derivative finally satisfies: ; ; in, , .

[0042] As one or more implementation methods, a stable preset finite-time control strategy based on the Lyapunov function is used to perform stability analysis on the virtual control input and the time-varying convergence function, specifically: (1) In Analyze the system state convergence, all states are within the preset time Time approaches zero.

[0043] From the above formula we can get: ; And by as well as , it can be inferred that , and then get .

[0044] The finite time time-varying convergence function is preset by the stable form We can get: , so it is inferred that , .

[0045] By the formula We can get: ; It can be inferred that: ; ; The formula Rewrite as ;in, , , , ; ; ; ; .

[0046] It can be inferred that: ; ; Will Substitution We can get: ; This means .and .

[0047] (2) In When the stability of the system is analyzed, at the stable point At this point, the control torque remains continuous and the controller is smooth at the stable preset time.

[0048] The formula Bring in We can get: ; Therefore, it can be deduced that: ; Points can be earned: .

[0049] Therefore, for , Established and , ; ;and . So we finally get: .

[0050] The stable preset time controller is smooth at the stable point. Ability to achieve expected results within the preset time and In addition, at the stable point At this point, the control torque remains continuous and the stability analysis is completed.

[0051] As one or more implementations, the controller parameters are designed to meet specific conditions; wherein, , , , is a positive definite diagonal matrix, and , , by adjusting The convergence speed can be optimized.

[0052] The stability control method in this embodiment is applicable to complex systems that require continuous control input, such as multi-joint manipulators of sandblasting robots, quadrotors and satellites. The preset finite-time control algorithm proposed has a controllable convergence time by human input, accurately converges at the input time, and is not affected by the initial state of the manipulator and the control parameters. This helps to make the operation time of the sandblasting robot controllable, highly portable, and unaffected by external working conditions. After the preset time, it can also suppress the influence of external disturbances, gun recoil and system unknowns. Through time scaling and stabilization mechanisms, the unity of preset time convergence and infinite time stability is achieved, breaking through the limitation that traditional finite-time controllers are only applicable to finite intervals.

[0053] In order to verify the effectiveness of the stability control method of the multi-joint manipulator arm of the sandblasting robot introduced in this embodiment, two sets of comparative experiments are conducted to conduct scientific demonstration.

[0054] (1) Experiment 1: The proposed stable preset finite time control method was compared with the proportional-integral-differential control method and the finite time control method to verify that its convergence time is controllable and is not affected by the initial state and control parameters, and the control effect of convergence is smooth and stable.

[0055] Set the initial joint angle positions to , the proposed stable preset finite time control parameters are set to , , , ,in , , , , preset convergence time .

[0056] like Figure 3 Angular position of the sandblasting robot arm shown and The convergence process under different control methods, by analyzing the experimental results of each control method, we can clearly see the differences in their convergence speed, accuracy and stability. When using the stable preset finite time controller, the angular position of the sandblasting robot arm and Converges to the desired value within a preset finite time. Specifically, the angular position is Converge to the expected value , showing the advantages of the stable preset finite time method in controlling the convergence time. In contrast, the convergence time of the proportional-integral-derivative controller is longer, which is and ,Although the proportional-integral-derivative control parameters have been optimized, its convergence speed is still insufficient.

[0057] In addition, in the case of large initial position errors, the proportional-integral-differential controller often overshoots, resulting in unstable oscillations during the adjustment of the sandblasting robot arm links, which seriously affects the stability and accuracy of the system. and It can also converge within a certain time, but its convergence time is and , significantly longer than the stable preset finite time method, and during this process, the system's response speed and accuracy are inferior to those of the stable preset finite time controller. This comparison shows that although the finite time control method has strong finite time control capabilities, its performance in practical applications is still limited by the choice of model and parameters. More significantly, the stable preset finite time method can ensure that the angular position of the sandblasting robot arm accurately converges to the desired state within the preset time under different initial states, control parameters, and preset times. This feature makes the stable preset finite time control method more flexible and stable in practical applications, without being restricted by initial states or control parameters, which is something that proportional-integral-differential control methods and finite time control methods cannot achieve. Whether changing the initial posture value or adjusting the control parameters and preset time, the stable preset finite time method consistently maintains its excellent control performance, thus achieving efficient control under variable working conditions.

[0058] like Figure 4 The angular velocity of the sandblasting robot arm joints shown and The response process under different control methods; by comparing the experimental results of the stable preset finite time, proportional-integral-differential and finite time controllers, we can clearly observe the performance differences of each control strategy on the joint angular velocity. Under the stable preset finite time control, the joint angular velocity and It converges quickly to steady state within the preset time and has the fastest convergence speed among the three control methods.

[0059] The angular velocity of the sandblasting robot arm is The steady state has been reached at this moment, which shows that the stable preset finite time controller can effectively reduce the fluctuation of joint angular velocity while ensuring convergence. In addition, the maximum angular velocity under the stable preset finite time control is and They are , , which is significantly smaller than the maximum angular velocity under proportional-integral-derivative control and , and the maximum angular velocity under finite-time control and . Experimental results show that the stable preset finite time control method is not only superior to other controllers in terms of convergence speed, but also has the smallest angular velocity fluctuation during the adjustment of the joint angular velocity. This feature helps to ensure that the sandblasting robot arm can maintain a smoother dynamic response during precise positioning and movement, avoiding strong vibration and instability caused by rapid changes in angular velocity. Compared with the proportional-integral-differential control method and the finite time method, the stable preset finite time control method can effectively reduce the mechanical vibration caused by excessive or rapidly changing angular velocity, thereby improving the control accuracy and the overall stability of the system, and ensuring the efficient and smooth operation of the sandblasting robot arm in complex tasks. This makes the stable preset finite time method have important application value in applications requiring high precision and low vibration.

[0060] like Figure 5 The input torque and response comparison under different control methods are shown. Under the proportional-integral-derivative controller, the input torque and The boundary is and , which is significantly larger than the bounds of the input torque observed under finite-time control and stable preset finite-time control. Under finite-time control, the input torque and The maximum value of the boundary is and , and under the stable preset finite time control, the input torque and The boundary is and , both of which are significantly lower than the torque value under proportional-integral-derivative control.

[0061] Results demonstrate that the proposed stable preset finite-time control method not only effectively controls the motion of the sandblasting robot's manipulator arm but also significantly reduces the input torque requirement. Lower input torque not only reduces the burden on the sandblasting robot's manipulator arm's drive motor, thereby reducing energy consumption, but also helps extend the lifespan of various components in the control system. Compared to the proportional-integral-differential control method, the stable preset finite-time control method can reduce overdrive while ensuring precise control, thereby improving overall energy efficiency and system stability. Furthermore, the low input torque of the stable preset finite-time control method helps mitigate the risk of controller failure caused by long-term high-load operation and extend the controller's service life.

[0062] (2) Experiment 2: A comparative analysis was conducted on the proposed stable preset finite time control method and the latest preset finite time control method, aiming to verify the smooth stability characteristics of the stable preset finite time control method at the preset time T, as well as the robustness of the control algorithm after T. The experimental results are as follows Figures 5 to 7 As shown, the disturbance is introduced between the 4th and 5th seconds after the preset time T.

[0063] like Figure 6 and Figure 7 The figure shows the convergence trends of the joint angles and angular velocities of the sandblasting robot arm under stable preset finite-time control and the latest preset finite-time control. Under both control methods, the joint angles and angular velocities of the sandblasting robot arm tend toward the desired values ​​and remain stable within the preset time. However, it is worth noting that although the stable preset finite-time control method can successfully overcome the disturbance and stabilize the joint angles and angular velocities back to the desired values ​​within 9 seconds after the disturbance is introduced, the latest preset finite-time control method fails to recover to the desired state after the disturbance occurs, showing poor system robustness. This phenomenon shows that the stable preset finite-time control method exhibits stronger recovery capabilities under disturbances than the latest preset finite-time control method.

[0064] like Figure 8 As shown in the figure, after the disturbance is introduced, the input torque of the latest preset finite-time controller remains unchanged after the preset time T. This fixed input torque cannot effectively cope with external disturbances, causing the sandblasting robot arm to lose control and fail to recover to the desired state. In contrast, under the stable preset finite-time control, the input torque is promptly adjusted to the external disturbance between seconds 4 and 9, successfully ensuring system stability. This demonstrates that the stable preset finite-time controller not only has strong disturbance resistance but also can flexibly adjust the control input according to actual conditions, effectively adjusting the joint angle and velocity to the desired values. Furthermore, the experimental results show that the control torque of the stable preset finite-time controller changes smoothly at the stable point, avoiding the chattering phenomenon commonly seen in stable controllers. Chattering often leads to a sharp decline in system performance and may even cause equipment damage. The smooth and stable characteristics of the stable preset finite-time control method significantly improve the stability and reliability of the system.

[0065] In order to address the problem that the original preset time control method in the prior art sets the control signal to zero after the preset time point and is unable to handle the influence of external disturbances, system unknowns and spray gun recoil, thereby causing system crashes and possible vibrations during external disturbances and control stabilization, affecting the accuracy of the robotic arm and the overall performance of the system; this embodiment suppresses the influence of spray gun recoil, external disturbances and unknown parameters within the preset time, maintains stability during the disturbance and stabilization process, and improves the stability and reliability of the preset finite time dual-mode control terminal of the multi-joint robotic arm of the sandblasting robot.

[0066] Example 2 The second embodiment of the present invention introduces a stability control system for a multi-joint mechanical arm of a sandblasting robot.

[0067] like Figure 9 The stability control system of a multi-joint manipulator arm of a sandblasting robot shown includes: an acquisition module configured to acquire a dynamic model of a multi-joint manipulator arm of a sandblasting robot; a transformation module configured to perform a state transformation on the acquired dynamic model using a time-varying convergence function of a stable preset finite-time control strategy to obtain a virtual control signal and an actual control input signal of the dynamic model; The control module is configured to analyze the stability of the dynamic model based on the obtained virtual control signal and the actual control input signal, determine the stability point of the dynamic model, control the actual torque of the robotic arm on both sides of the determined stability point to maintain continuity, and complete the stability control of the multi-joint robotic arm of the sandblasting robot according to the actual torque of the robotic arm.

[0068] The detailed steps are the same as those of the stability control method of the multi-joint mechanical arm of the sandblasting robot provided in Example 1, and will not be repeated here.

[0069] Example 3 A third embodiment of the present invention provides a computer-readable storage medium.

[0070] A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps of the stability control method for a multi-joint mechanical arm of a sandblasting robot as described in the first embodiment of the present invention.

[0071] The detailed steps are the same as those of the stability control method of the multi-joint mechanical arm of the sandblasting robot provided in Example 1, and will not be repeated here.

[0072] Example 4 A fourth embodiment of the present invention provides an electronic device.

[0073] An electronic device comprises a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, the steps of the stability control method of the multi-joint mechanical arm of a sandblasting robot as described in the first embodiment of the present invention are implemented.

[0074] The detailed steps are the same as those of the stability control method of the multi-joint mechanical arm of the sandblasting robot provided in Example 1, and will not be repeated here.

[0075] Example 5 A fifth embodiment of the present invention provides a computer program product.

[0076] A computer program product includes software code, wherein the program in the software code executes the steps of the stability control method of the multi-joint mechanical arm of a sandblasting robot as described in the first embodiment of the present invention.

[0077] The detailed steps are the same as those of the stability control method of the multi-joint mechanical arm of the sandblasting robot provided in Example 1, and will not be repeated here.

[0078] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk drives, CD-ROMs, optical storage devices, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention may be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0079] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0082] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0083] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

[0084] The above description is merely a preferred embodiment of this embodiment and is not intended to limit this embodiment. Those skilled in the art will readily appreciate that this embodiment may be modified and varied in various ways. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this embodiment shall be within the scope of protection of this embodiment.

Claims

1. A stability control method for a multi-joint manipulator arm of a sandblasting robot, characterized in that: include: Obtain the dynamic model of the multi-joint manipulator of the sandblasting robot; The obtained dynamic model is transformed into a state by using a time-varying convergence function of a stable preset finite-time control strategy to obtain a virtual control signal and an actual control input signal of the dynamic model; The stability of the dynamic model is analyzed based on the obtained virtual control signal and the actual control input signal, and the stable point of the dynamic model is determined. The actual torque of the robotic arm is controlled to maintain continuity on both sides of the determined stable point. The stability control of the multi-joint robotic arm of the sandblasting robot is completed according to the actual torque of the robotic arm.

2. A method for controlling the stability of a multi-joint manipulator arm of a sandblasting robot as claimed in claim 1, characterized in that: The dynamic model of the multi-joint manipulator of the sandblasting robot is: ;in, is the vector of the link joint angle, is the joint angle The inertia matrix, is the Coriolis force and centrifugal force matrix, is the friction force vector, is the gravity vector, is the control input, is an external disturbance, is the joint rotation acceleration, is the joint rotation speed.

3. A method for controlling the stability of a multi-joint manipulator arm of a sandblasting robot as claimed in claim 1, characterized in that: The time-varying convergence function used for ;in, is the actual convergence time of the robotic arm system, For preset time, is the running time of the robotic arm system; the state of the obtained dynamic model is transformed by combining the time-varying convergence function, and the state of the multi-joint robotic arm of the sandblasting robot is converted into an error variable through time-varying transformation to obtain the virtual control signal of the dynamic model and the actual control input signal .

4. A method for controlling the stability of a multi-joint manipulator arm of a sandblasting robot as claimed in claim 1, characterized in that: In the process of analyzing the stability of the dynamic model, the convergence of the dynamic model is analyzed by Lyapunov equation, and the stable point is determined by combining Young's inequality. The control signal is switched at the determined stable point to complete the stable control of the robotic arm.

5. A method for controlling the stability of a multi-joint manipulator arm of a sandblasting robot as claimed in claim 1, characterized in that: Before reaching the stable point, by analyzing the convergence of each state of the dynamic model, it is found that all states of the dynamic model tend to zero when reaching the stable point.

6. A method for controlling the stability of a multi-joint manipulator arm of a sandblasting robot as claimed in claim 1, characterized in that: When the stable point is reached, the control torque of the dynamic model is maintained, and the actual control input signal is kept smooth at the stable point for a preset time.

7. A stability control system for a multi-joint manipulator arm of a sandblasting robot, characterized in that: include: an acquisition module configured to acquire a dynamic model of a multi-joint manipulator arm of a sandblasting robot; a transformation module configured to perform a state transformation on the acquired dynamic model using a time-varying convergence function of a stable preset finite-time control strategy to obtain a virtual control signal and an actual control input signal of the dynamic model; The control module is configured to analyze the stability of the dynamic model based on the obtained virtual control signal and the actual control input signal, determine the stability point of the dynamic model, control the actual torque of the robotic arm on both sides of the determined stability point to maintain continuity, and complete the stability control of the multi-joint robotic arm of the sandblasting robot according to the actual torque of the robotic arm.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the stability control method of the multi-joint mechanical arm of a sandblasting robot according to any one of claims 1 to 6 are implemented.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of the stability control method of the multi-joint mechanical arm of a sandblasting robot are implemented as described in any one of claims 1 to 6.

10. A computer program product comprising software code, characterized in that The program in the software code executes the steps of the stability control method of the multi-joint manipulator arm of a sandblasting robot according to any one of claims 1 to 6.

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