A control method, device and control system for a robotic arm

Abstract

The present invention provides a control method for a robotic arm. The control method for the robotic arm includes: obtaining the initial position and the target position of the robotic arm, and inputting the initial position and the target position into a model predictive controller; outputting the state parameters at the current moment in the model predictive controller according to the initial position and the target position, and respectively inputting the state parameters at the current moment into a robotic arm controller and a prediction model; outputting the target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and outputting the prediction parameters at the next moment in the prediction model according to the state parameters at the current moment; adding the target parameters and the prediction parameters to obtain combined parameters, and controlling the robotic arm to move to the target position with the combined parameters.

Description

Technical Field

[0001] The present invention mainly relates to the field of mechanical control, and in particular, to a control method, device, and control system for a robotic arm. Background Art

[0002] Proportional Integral Derivative (PID) control is widely used in the control of robotic arms due to its advantages of simplicity and ease of calculation. However, it is difficult to achieve the combination of speed and stability only relying on PID control, and PID control also has certain limitations in dealing with constraint conditions. To solve the limitations of PID control, some more advanced and intelligent control algorithms have been proposed in the industry, such as impedance control, torque control, and adaptive control. However, these algorithms require providing an accurate mathematical model of the controlled object, that is, an accurate mathematical model based on physical and chemical principles. In addition, due to the strong correlation, non-linearity, and multi-input multi-output characteristics of the robotic arm model, it has become increasingly difficult to use these control algorithms to predict, optimize, control, and evaluate in industrial production processes. Summary of the Invention

[0003] To solve the above technical problems, the present invention provides a control method, device, and control system for a robotic arm, which can stably and quickly control the robotic arm.

[0004] To achieve the above object, the present invention proposes a control method for a robotic arm. The control method for the robotic arm includes: obtaining an initial position and a target position of the robotic arm, and inputting the initial position and the target position into a model predictive controller; outputting state parameters at the current moment in the model predictive controller according to the initial position and the target position, and inputting the state parameters at the current moment into a robotic arm controller and a prediction model respectively; outputting target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and outputting prediction parameters at the next moment in the prediction model according to the state parameters at the current moment; adding the target parameters and the prediction parameters to obtain a combined parameter, and controlling the robotic arm to move to the target position with the combined parameter. Therefore, by outputting target parameters at the current moment through the robotic arm, outputting prediction parameters at the next moment through the prediction model, adding the target parameters and the prediction parameters to obtain a combined parameter, and controlling the robotic arm to move to the target position with the combined parameter, the movement of the robotic arm is corrected by generating prediction parameters through the prediction model, and the stability of the movement of the robotic arm is improved.

[0005] In an embodiment of the present invention, the method further includes: calculating the current position of the robotic arm corresponding to the merging parameter, comparing the current position with a threshold, and when the current position is greater than the threshold, adding the current position and the target position, and inputting the sum value of the current position and the target position into the model predictive controller. For this purpose, a feedback loop is formed, further improving the stability and accuracy of the robotic arm movement.

[0006] In an embodiment of the present invention, the state parameters include the angle and angular velocity of the robotic arm. For this purpose, stable control of the angle and angular velocity is achieved.

[0007] In an embodiment of the present invention, the following formula is used to output the predicted parameters at the next moment in the prediction model according to the state parameters at the current moment: x(k + 1) = Ax(k) + Bu(k) y(k) = Cx(k) where A, B, and C are constants, x(k + 1) represents the angle vector of each joint in the robotic arm input at the (k + 1)-th moment, x(k) represents the angle vector of each joint in the robotic arm input at the k-th moment, u(k) represents the angular velocity vector of each joint in the robotic arm input at the k-th moment, and y(k) represents the angle vector of each joint in the robotic arm output at the k-th moment. For this purpose, the prediction model is enabled to predict the parameters at the next moment.

[0008] In an embodiment of the present invention, outputting the state parameters at the current moment in the model predictive controller according to the initial position and the target position includes: using a minimized cost function to output the state parameters at the current moment in the model predictive controller according to the initial position and the target position. For this purpose, the control of the model predictive controller is achieved.

[0009] The present invention also provides a control device for a robotic arm. The control device for the robotic arm includes: an acquisition module, which acquires the initial position and the target position of the robotic arm and inputs the initial position and the target position into the model predictive controller; a first processing module, which outputs the state parameters at the current moment in the model predictive controller according to the initial position and the target position, and inputs the state parameters at the current moment into the robotic arm controller and the prediction model respectively; a second processing module, which outputs the target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and outputs the predicted parameters at the next moment in the prediction model according to the state parameters at the current moment; a calculation and control module, which adds the target parameters and the predicted parameters to obtain a merging parameter, and controls the robotic arm to move to the target position with the merging parameter.

[0010] In an embodiment of the present invention, the device further includes: calculating a current position of the robotic arm corresponding to the combined parameter, comparing the current position with a threshold, and when the current position is greater than the threshold, adding the current position and the target position, and inputting the sum value of the current position and the target position into the model predictive controller.

[0011] In an embodiment of the present invention, the state parameters include the angle and angular velocity of the robotic arm.

[0012] In an embodiment of the present invention, the following formula is used to output the predicted parameters at the next moment according to the state parameters at the current moment in the prediction model: x(k + 1) = Ax(k) + Bu(k) y(k) = Cx(k) where A, B, and C are constants, x(k + 1) represents the angle vector of each joint in the robotic arm input at the (k + 1)-th moment, x(k) represents the angle vector of each joint in the robotic arm input at the k-th moment, u(k) represents the angular velocity vector of each joint in the robotic arm input at the k-th moment, and y(k) represents the angle vector of each joint in the robotic arm output at the k-th moment.

[0013] In an embodiment of the present invention, outputting the state parameters at the current moment according to the initial position and the target position in the model predictive controller includes: using a minimized cost function to output the state parameters at the current moment according to the initial position and the target position in the model predictive controller.

[0014] The present invention also provides a control system for a robotic arm, the control system for the robotic arm includes: a model predictive controller that outputs state parameters at the current moment according to the received initial position and target position; a robotic arm controller that receives the state parameters at the current moment and outputs target parameters at the current moment according to the state parameters at the current moment; a prediction model that receives the state parameters at the current moment and outputs predicted parameters at the next moment according to the state parameters at the current moment; an adder that adds the target parameters and the predicted parameters to obtain a combined parameter, and the combined parameter is used to control the robotic arm to move to the target position with the combined parameter.

[0015] The present invention also provides a mechanical system, the mechanical system includes a robotic arm and the control system according to claim 11, and the control system is used to control the robotic arm.

[0016] The present invention also provides an electronic device, including a processor, a memory, and instructions stored in the memory, where when the instructions are executed by the processor, the methods described above are implemented.

[0017] The present invention also provides a computer-readable storage medium, on which computer instructions are stored, and when the computer instructions are executed, the method described above is performed. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The following drawings are only intended to illustrate and explain the present invention, and do not limit the scope of the present invention. Among them,

[0019] Figure 1 is a flowchart of a method for controlling a robotic arm according to an embodiment of the present invention;

[0020] Figure 2 is a control logic diagram of a robotic arm according to an embodiment of the present invention;

[0021] Figure 3 is a schematic diagram of a control device of a robotic arm according to an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of a control system of a robotic arm according to an embodiment of the present invention;

[0023] Figure 5 is a schematic diagram of a mechanical system according to an embodiment of the present invention;

[0024] Figure 6 is a schematic diagram of an electronic device according to an embodiment of the present invention;

[0025] Figures 7A-7G is a schematic diagram of a simulation result of a 7-degree-of-freedom robotic arm of a control method according to an embodiment of the present invention.

[0026] DESCRIPTION OF THE REFERENCE NUMERALS

[0027] 100 Control method of the robotic arm

[0028] 110 - 140 Steps

[0029] 210 Input

[0030] 220 Model predictive controller

[0031] 230 Robotic arm controller

[0032] 240 Prediction model

[0033] 250 Judgment unit

[0034] 260 Output

[0035] 270 First adder

[0036] 280 Second adder

[0037] Control device for a 300 robotic arm

[0038] 310 Acquisition module

[0039] 320 First processing module

[0040] 330 Second processing module

[0041] 340 Calculation and control module

[0042] 400 Control system for a robotic arm

[0043] 410 Model predictive controller

[0044] 420 Robotic arm controller

[0045] 430 Prediction model

[0046] 440 Adder

[0047] 500 Mechanical system

[0048] 510 Control system for a robotic arm

[0049] 520 Robotic arm

[0050] 600 Electronic device

[0051] 610 Processor

[0052] 620 Memory Detailed implementation manners

[0053] For a clearer understanding of the technical features, objectives, and effects of the present invention, the specific implementation manners of the present invention will now be described with reference to the accompanying drawings.

[0054] Many specific details are set forth in the following description in order to provide a thorough understanding of the present invention. However, the present invention may be implemented in other ways different from those described herein, and thus the present invention is not limited by the specific embodiments disclosed below.

[0055] As shown in this application and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. A method or device may also include other steps or elements.

[0056] The present invention proposes a control method for a robotic arm, Figure 1 which is a flowchart of a control method 100 for a robotic arm according to an embodiment of the present invention. Figure 2It is a control logic diagram of a robotic arm according to an embodiment of the present invention. The control method of the robotic arm in the embodiments of the present invention will be described below in conjunction with Figure 1 and Figure 2 As shown in Figure 1 , the control method of the robotic arm includes:

[0057] Step 110, obtain the initial position and the target position of the robotic arm, and input the initial position and the target position into the model predictive controller.

[0058] The initial position of the robotic arm can be obtained by a position sensor installed on the robotic arm, and the target position of the robotic arm can be obtained from the user through a human-machine interface. The initial position and the target position of the robotic arm can be coordinates in the robotic arm coordinate system or coordinates in the world coordinate system. Figure 2 In , the input 210 includes the initial position and the target position of the robotic arm. The initial position and the target position are input into the model predictive controller 220 as positive feedback through the first adder 270.

[0059] Step 120, output the state parameters at the current moment in the model predictive controller according to the initial position and the target position, and input the state parameters at the current moment into the robotic arm controller and the prediction model respectively.

[0060] After the initial position and the target position are input into the model predictive controller 220, the model predictive controller 220 uses a mathematical model to output a state parameter at the current moment according to the initial position and the target position. In some embodiments, the state parameters include the angle and angular velocity of the robotic arm. Taking a six-joint robot as an example, the output of the model predictive controller 220 can be a 12*1 matrix, where the first 6 rows are the angles of the 6 joints at the current moment, and the last 6 rows are the angular velocities of the 6 joints at the current moment. In some embodiments, outputting the state parameters at the current moment in the model predictive controller according to the initial position and the target position includes: outputting the state parameters at the current moment in the model predictive controller using a minimized cost function according to the initial position and the target position.

[0061] Step 130, output the target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and output the prediction parameters at the next moment in the prediction model according to the state parameters at the current moment.

[0062] After the state parameters at the current moment are input into the robotic arm controller 230, the robotic arm controller 230 uses a control algorithm to output the target parameters at the current moment according to the state parameters at the current moment. Taking a six-joint robot as an example, the output of the robotic arm controller 230 can be a 6*1 matrix, and each row represents the target angle of the 6 joints.

[0063] After the state parameters at the current moment are input into the prediction model 240, the prediction model 240 outputs the prediction parameters at the next moment according to the state parameters at the current moment. Taking a six-axis robot as an example, the output of the prediction model 240 can be a 6*1 matrix, and each row represents the predicted angles of 6 joints.

[0064] In some embodiments, the following formula can be used to output the prediction parameters at the next moment according to the state parameters at the current moment in the prediction model:

[0065] x(k + 1) = Ax(k) + Bu(k)

[0066] y(k) = Cx(k)

[0067] Among them, A, B, and C are constants. x(k + 1) represents the angle vector of each joint in the robotic arm input at the (k + 1)-th moment, x(k) represents the angle vector of each joint in the robotic arm input at the k-th moment, u(k) represents the angular velocity vector of each joint in the robotic arm input at the k-th moment, and y(k) represents the angle vector of each joint in the robotic arm output at the k-th moment.

[0068] Step 140: Add the target parameters and the prediction parameters to obtain the combined parameters, and control the robotic arm to move to the target position with the combined parameters.

[0069] The output target parameters of the robotic arm controller 230 are used as positive feedback through the second adder 280 to the output 260, and the output prediction parameters of the prediction model 240 are used as negative feedback through the second adder 280 to the output 260. That is, the target parameters and the prediction parameters are added to obtain the combined parameters. In the combined parameters, the target parameters are positive values and the prediction parameters are negative values, thereby realizing the correction of the movement of the robotic arm through the prediction model and improving the stability of the robotic arm movement. The combined parameters are then sent to a robotic arm driver (not shown in the figure), and the robotic arm driver controls the robotic arm to move to the target position according to the combined parameters.

[0070] In some embodiments, method 100 further includes: calculating the current position of the robotic arm corresponding to the combined parameters, comparing the current position with a threshold, and when the current position is greater than the threshold, adding the current position and the target position, and inputting the sum value of the current position and the target position into the model predictive controller. Figure 2 In this case, the combined parameters output by the second adder 280 are also input to the judgment unit 250. The judgment unit 250 calculates the current position of the robotic arm corresponding to the combined parameters, compares the current position with a threshold. If the current position is greater than the threshold, the current position is input as negative feedback into the first adder 270, and the target position is the positive input of the first adder 270. Otherwise, it goes to the output 260. Thus, a feedback loop is formed, further improving the stability and accuracy of the robotic arm movement.

[0071] Figures 7A-7G It is a schematic diagram of the simulation result of a 7-joint robotic arm of a control method according to an embodiment of the present invention. Figures 7A-7G They respectively correspond to each joint. The abscissa is time, with the unit of second (s), and the ordinate is the joint angle, with the unit of degree (°). The solid line is the angle simulation curve using the control method of the embodiment of the present invention, and the dashed line is the angle simulation curve using the PID control method. From Figures 7A-7G it can be seen that whether using the control method in the embodiment of the present invention or the PID control method, the steady state can be reached within 0.5 seconds. However, the fluctuation using the control method in the embodiment of the present invention is smaller, that is, the stability is higher.

[0072] An embodiment of the present invention provides a robotic arm control method. By outputting the target parameters at the current moment by the robotic arm, outputting the predicted parameters at the next moment by the prediction model, adding the target parameters and the predicted parameters to obtain the combined parameters, and controlling the robotic arm to move to the target position with the combined parameters, it realizes the correction of the movement of the robotic arm by generating predicted parameters through the prediction model, and improves the stability of the movement of the robotic arm.

[0073] The present invention also proposes a control device 300 for a robotic arm. Figure 3 It is a schematic diagram of a control device 300 for a robotic arm according to an embodiment of the present invention. As Figure 3 shown, the control device 300 for a robotic arm includes:

[0074] An acquisition module 310, which acquires the initial position and the target position of the robotic arm and inputs the initial position and the target position into the model predictive controller.

[0075] A first processing module 320, which outputs the state parameters at the current moment in the model predictive controller according to the initial position and the target position, and inputs the state parameters at the current moment into the robotic arm controller and the prediction model respectively.

[0076] A second processing module 330, which outputs the target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and outputs the predicted parameters at the next moment in the prediction model according to the state parameters at the current moment.

[0077] A calculation and control module 340, which adds the target parameters and the predicted parameters to obtain the combined parameters, and controls the robotic arm to move to the target position with the combined parameters.

[0078] In some embodiments, the device 300 further includes: calculating the current position of the robotic arm corresponding to the combined parameters, comparing the current position with a threshold, and when the current position is greater than the threshold, adding the current position and the target position, and inputting the sum value of the current position and the target position into the model predictive controller.

[0079] In some embodiments, the state parameters include the angles and angular velocities of the robotic arm.

[0080] In some embodiments, the following formula is used to output the predicted parameters at the next moment in the prediction model according to the state parameters at the current moment:

[0081] x(k + 1) = Ax(k) + Bu(k)

[0082] y(k) = Cx(k)

[0083] where A, B, and C are constants, x(k + 1) represents the angle vector of each joint in the robotic arm input at the (k + 1)-th moment, x(k) represents the angle vector of each joint in the robotic arm input at the k-th moment, u(k) represents the angular velocity vector of each joint in the robotic arm input at the k-th moment, and y(k) represents the angle vector of each joint in the robotic arm output at the k-th moment.

[0084] In some embodiments, the state parameters at the current moment output by the model predictive controller according to the initial position and the target position include: using the minimized cost function to output the state parameters at the current moment by the model predictive controller according to the initial position and the target position.

[0085] The present invention also provides a control system 400 for a robotic arm, Figure 4 which is a schematic diagram of a control system for a robotic arm according to an embodiment of the present invention. As Figure 4 shown, the control system 400 for the robotic arm includes:

[0086] A model predictive controller 410 that outputs the state parameters at the current moment according to the received initial position and target position.

[0087] A robotic arm controller 420 that receives the state parameters at the current moment and outputs the target parameters at the current moment according to the state parameters at the current moment.

[0088] A prediction model 430 that receives the state parameters at the current moment and outputs the predicted parameters at the next moment according to the state parameters at the current moment.

[0089] An adder 440 that adds the target parameters and the predicted parameters to obtain a combined parameter, and the combined parameter is used to control the robotic arm to move to the target position with the combined parameter.

[0090] The present invention also provides a mechanical system 500, Figure 5 which is a schematic diagram of a mechanical system 500 according to an embodiment of the present invention. As Figure 5As shown, the mechanical system 500 includes a robotic arm 520 and a control system 510 for controlling the robotic arm 520, and the control system 510 of the robotic arm can be the control system 400 of the robotic arm described above.

[0091] The present invention also provides an electronic device 600. Figure 6 is a schematic diagram of an electronic device 600 according to an embodiment of the present invention. As Figure 6 shown, the electronic device 600 includes a processor 610 and a memory 620. Instructions are stored in the memory 620, and when the instructions are executed by the processor 610, the method 100 described above is implemented.

[0092] The present invention also provides a computer-readable storage medium, on which computer instructions are stored, and when the computer instructions are run, the method 100 described above is executed.

[0093] Some aspects of the methods and apparatuses of the present invention can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software can be referred to as "blocks", "modules", "engines", "units", "components" or "systems". The processor can be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, aspects of the present invention may be embodied as a computer product located on one or more computer-readable media, the product including computer-readable program code. For example, the computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes...), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs)...), smart cards, and flash memory devices (e.g., cards, sticks, key drives...).

[0094] Flowcharts are used herein to illustrate the operations performed by the methods according to the embodiments of the present application. It should be understood that the previous operations are not necessarily executed precisely in order. Instead, various steps can be processed in reverse order or simultaneously. Also, or other operations can be added to these processes, or one or several operations can be removed from these processes.

[0095] It should be understood that although this specification is described according to various embodiments, not every embodiment only contains an independent technical solution. This narrative manner of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

[0096] The above are only illustrative specific embodiments of the present invention and are not intended to limit the scope of the present invention. Any equivalent changes, modifications and combinations made by those skilled in the art without departing from the concept and principles of the present invention shall fall within the scope of protection of the present invention.

Claims

1. A control method for a robotic arm (100), characterized in that, The control method (100) of the robotic arm includes: Obtain the initial position and the target position of the robotic arm, and input the initial position and the target position into a model predictive controller (110); Output the state parameters at the current moment in the model predictive controller according to the initial position and the target position, and input the state parameters at the current moment into a robotic arm controller and a prediction model respectively (120); Output the target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and output the prediction parameters at the next moment in the prediction model according to the state parameters at the current moment (130); Sum the target parameters and the prediction parameters to obtain combined parameters, and control the robotic arm to move to the target position with the combined parameters (140); Wherein, the state parameters include the angle and angular velocity of the robotic arm; The following formula is used to output the prediction parameters at the next moment in the prediction model according to the state parameters at the current moment: x(k + 1) = Ax(k) + Bu(k) y(k) = Cx(k) Wherein, A, B, and C are constants, x(k + 1) represents the angle vector of each joint in the robotic arm input at the (k + 1)-th moment, x(k) represents the angle vector of each joint in the robotic arm input at the k-th moment, u(k) represents the angular velocity vector of each joint in the robotic arm input at the k-th moment, and y(k) represents the angle vector of each joint in the robotic arm output at the k-th moment; Outputting the state parameters at the current moment in the model predictive controller according to the initial position and the target position includes: using a minimized cost function to output the state parameters at the current moment in the model predictive controller according to the initial position and the target position.

2. The control method (100) according to claim 1, wherein, The method (100) further includes: calculating the current position of the robotic arm corresponding to the combined parameters, comparing the current position with a threshold, and when the current position is greater than the threshold, summing the current position and the target position, and inputting the sum value of the current position and the target position into the model predictive controller.

3. A control device (300) for a robotic arm, characterized in that, The control device (300) of the robotic arm includes: An acquisition module (310) that acquires the initial position and the target position of the robotic arm, and inputs the initial position and the target position into a model predictive controller; A first processing module (320) that outputs the state parameters at the current moment in the model predictive controller according to the initial position and the target position, and inputs the state parameters at the current moment into a robotic arm controller and a prediction model respectively; A second processing module (330) that outputs the target parameters at the current moment in the robotic arm controller according to the state parameters at the current moment, and outputs the prediction parameters at the next moment in the prediction model according to the state parameters at the current moment; A calculation and control module (340) that sums the target parameters and the prediction parameters to obtain combined parameters, and controls the robotic arm to move to the target position with the combined parameters; Wherein, the state parameters include the angle and angular velocity of the robotic arm; The following formula is used to output the predicted parameters at the next moment in the prediction model according to the state parameters at the current moment: x(k + 1) = Ax(k) + Bu(k) y(k) = Cx(k) where A, B, and C are constants, x(k + 1) represents the angle vector of each joint in the robotic arm input at time k + 1, x(k) represents the angle vector of each joint in the robotic arm input at time k, u(k) represents the angular velocity vector of each joint in the robotic arm input at time k, and y(k) represents the angle vector of each joint in the robotic arm output at time k; Outputting the state parameters at the current moment according to the initial position and the target position in the model predictive controller includes: using a minimized cost function to output the state parameters at the current moment in the model predictive controller according to the initial position and the target position.

4. The control device (300) according to claim 3, characterized in that, The device (300) further includes: calculating the current position of the robotic arm corresponding to the combined parameter, comparing the current position with a threshold, and when the current position is greater than the threshold, adding the current position and the target position, and inputting the sum value of the current position and the target position into the model predictive controller.

5. A control system (400) of a robotic arm, characterized in that, The control system (400) of the robotic arm includes: A model predictive controller (410) that outputs the state parameters at the current moment according to the received initial position and target position; A robotic arm controller (420) that receives the state parameters at the current moment and outputs the target parameters at the current moment according to the state parameters at the current moment; A prediction model (430) that receives the state parameters at the current moment and outputs the predicted parameters at the next moment according to the state parameters at the current moment; An adder (440) that adds the target parameters and the predicted parameters to obtain a combined parameter, and the combined parameter is used to control the robotic arm to move to the target position with the combined parameter; where the state parameters include the angle and angular velocity of the robotic arm; The following formula is used to output the predicted parameters at the next moment in the prediction model according to the state parameters at the current moment: x(k + 1) = Ax(k) + Bu(k) y(k) = Cx(k) where A, B, and C are constants, x(k + 1) represents the angle vector of each joint in the robotic arm input at time k + 1, x(k) represents the angle vector of each joint in the robotic arm input at time k, u(k) represents the angular velocity vector of each joint in the robotic arm input at time k, and y(k) represents the angle vector of each joint in the robotic arm output at time k; Outputting the state parameters at the current moment according to the received initial position and target position includes: using a minimized cost function to output the state parameters at the current moment in the model predictive controller according to the initial position and the target position.

6. A mechanical system (500), characterized in that, The mechanical system includes a robotic arm (520) and the control system as claimed in claim 5, and the control system is used to control the robotic arm (520).

7. An electronic device (600) includes a processor (610), a memory (620), and instructions stored in the memory (620), wherein when the instructions are executed by the processor (610), the method according to claim 1 or 2 is implemented.

8. A computer-readable storage medium having computer instructions stored thereon, and the computer instructions, when run, execute the method according to claim 1 or 2.

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