Motion control method and system for service robot under extreme working condition

Abstract

The invention discloses a motion control method and system for a service robot under an extreme working condition. The method comprises the following steps: estimating lumped disturbance of the robot by a fuzzy approximator based on a self-adaptive updating law; according to the lumped disturbance, a disturbed second-order system model is used for expressing the dynamic characteristics of the service robot under the extreme working condition; designing a self-tuning predetermined performance function of the robot; designing a coordinate transformation mechanism according to the self-tuning predetermined performance function; and designing a robot motion controller based on a global predetermined performance control law in combination with the dynamic characteristics, the coordinate transformation mechanism and a backstepping control strategy. Therefore, the robot can effectively cope with the multi-dimensional composite disturbance impact under the extreme working condition, and the preset performance requirement is met while it is guaranteed that the output response is converged at the fixed time.

Description

Technical Field

[0001] The present invention relates to the technical field of robot motion control, and in particular to a motion control method and system for a robot serving in extreme working conditions. Background Art

[0002] In recent years, robots have become increasingly widely used in complex and extreme working conditions, such as high temperature and high pressure, strong electromagnetic interference, and multi-source impact loads. To meet the mission requirements under these extreme working conditions, robots must be able to cope with the impact of external environmental disturbances and ensure stable and efficient operation under complex and unpredictable working conditions. Under extreme working conditions, robots are subject to disturbances primarily from two sources: first, drastic changes in the external environment, such as wind speed fluctuations, uneven ground, and temperature fluctuations; second, dynamic changes in the internal structure, such as perturbations in mechanical parameters and unmodeled dynamics. These disturbances can cause instability in the robot's control system, thereby affecting key performance indicators such as motion accuracy, response speed, and trajectory tracking.

[0003] At the same time, practical applications are increasingly demanding the comprehensive performance of robotic systems. There is an urgent need for robots to maintain the desired control performance, ensuring that the output response remains within the expected range, even in the presence of disturbances and uncertainties. To this end, the predetermined performance control method has emerged. This method combines a predetermined performance function with a potential barrier Lyapunov function to design a feedback control law that ensures that the output feedback error converges stably within predetermined boundaries. Fuzzy estimators, neural network estimators, or disturbance observers are also introduced to handle disturbances and uncertainties. Fuzzy estimators, in particular, show considerable application potential due to their universal approximation properties.

[0004] In existing robot controller designs for predetermined performance, the following assumptions are essential: the initial output feedback error must be within the boundaries of the predetermined performance function and the system state must not change suddenly. However, during the operation of robots operating in extreme conditions, multi-dimensional and complex extreme disturbances can easily disrupt the system's equilibrium. This can cause these strict assumptions to no longer hold, and the system will no longer maintain the predetermined performance after the state changes. Furthermore, robots operating in extreme conditions not only expect the system output to meet the predetermined performance but also to converge as quickly as possible. However, effective solutions to these problems remain lacking. Summary of the Invention

[0005] The present invention provides a motion control method and system for a robot serving in extreme working conditions, which relaxes the strict assumptions required by existing predetermined performance control designs. At the same time, it not only ensures that the robot serving in extreme working conditions can still maintain the predetermined performance under disturbance, but also improves the error convergence speed. In a first aspect, a motion control method for a robot serving in extreme working conditions is provided, comprising the following steps: A fuzzy approximator based on an adaptive update law estimates the robot's lumped disturbance; According to the lumped disturbance, the dynamic characteristics of the service robot under extreme working conditions are described using a disturbed second-order system model; Design the robot's self-tuning predetermined performance function; designing a coordinate transformation mechanism according to the self-tuning predetermined performance function; Combining the dynamic characteristics, the coordinate transformation mechanism and the backstepping control strategy, a robot motion controller based on a global predetermined performance control law is designed.

[0006] In some embodiments, the method for estimating the lumped disturbance of the robot using the fuzzy approximator based on the adaptive update law is shown in the following formula: ; The adaptive update law is as follows: ; Where, is the adaptive update law; for The derivative of Lumped disturbance estimated value of; is the basis vector function; T is the matrix transpose; 、 and For adjustable gain; is the control variable.

[0007] In some embodiments, the step of expressing the dynamic characteristics of the service robot under extreme working conditions using a disturbed second-order system model based on the lumped disturbance includes: The disturbed second-order system model is shown as follows: ; in, ; ; ; ; ; ; ; ; Where, and is the system status; and System status and The derivative of and is the coefficient; is the control input; b is the coefficient of the control input; interference terms that can be theoretically modeled; is the lumped disturbance; For output feedback; , , are the robot position, velocity and acceleration respectively; 、 and are the inertia matrix, Coriolis force matrix and gravity matrix respectively; is the input torque; For disturbance.

[0008] In some embodiments, the self-tuning predetermined performance function of the design robot is shown as follows: ; Adaptive adjustment of time-varying weight factors is based on the following method and : ; Among them, the bounded performance function As shown in the following formula: ; Where, is the convergence speed; is an initial positive value; is a positive value regarding stable tracking accuracy; for and The current value of for and Adjusted value; is the adjustment step; e is the output feedback error; t is the time.

[0009] In some embodiments, the coordinate transformation mechanism designed according to the self-tuning predetermined performance function is shown as follows: ; Among them, the virtual reference As shown in the following formula: ; Where, and is the error variable; is a bounded performance function The derivative of Output reference trajectory The derivative of and is an adjustable control gain; is the system state; e is the output feedback error; and is the time-varying weight factor.

[0010] In some embodiments, the step of combining the dynamic characteristics, the coordinate transformation mechanism, and the backstepping control strategy to design a robot motion controller based on a global predetermined performance control law includes: The robot motion controller u is shown as follows: Among them, the variable As shown in the following formula: ; variable As shown in the following formula: ; Where, and is an adjustable control gain; is the basis vector function; is the adaptive update law; and is the system status; and is the coefficient; e is the output feedback error; and is the time-varying weight factor; is a bounded performance function; Lumped disturbance estimated value of; is the disturbance term that can be modeled theoretically; b is the control input system; and is the error variable.

[0011] Secondly, a motion control system for a robot serving in extreme working conditions is provided, comprising: The lumped disturbance module is used to estimate the lumped disturbance of the robot based on the fuzzy approximator of the adaptive update law; a dynamics description module, in communication with the lumped disturbance module, for describing the dynamic characteristics of the service robot under extreme working conditions based on the lumped disturbance and using a disturbed second-order system model; A predetermined performance function module is used to design the robot's self-tuning predetermined performance function; a coordinate transformation mechanism module, in communication with the predetermined performance function module, for designing a coordinate transformation mechanism according to the self-tuning predetermined performance function; and A motion controller module is in communication with the dynamic representation module and the coordinate transformation mechanism module, and is used to combine the dynamic characteristics, the coordinate transformation mechanism and the backstepping control strategy to design a robot motion controller based on a global predetermined performance control law.

[0012] In a third aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the motion control method of the robot serving in extreme working conditions as described above is implemented.

[0013] In a fourth aspect, an electronic device is provided, comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein when the processor executes the computer program, the motion control method for a robot serving in extreme working conditions as described above is implemented.

[0014] Compared with the existing technology, the advantages of the present invention are as follows: a new self-tuning predetermined performance function is proposed, which adaptively adjusts the boundaries of the performance function according to the output feedback error, relaxes the strict assumptions required by the existing predetermined performance control design, and thus provides a new solution for achieving predetermined performance control of robots serving in extreme working conditions.

[0015] The proposed motion controller, based on a global predetermined performance control law, incorporates dynamics-based feedforward compensation, disturbance compensation using a fuzzy estimator, feedback control of predetermined performance, and fixed-time convergence regulation. Compared to existing methods, it not only ensures that robots operating in extreme conditions maintain predetermined performance despite disturbances, but also accelerates error convergence. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic structural diagram of the extreme working condition service robot of the present invention; Figure 2 It is a schematic structural diagram of the multifunctional manipulator of the present invention; Figure 3 This is a flow chart of an embodiment of a motion control method for a robot serving in extreme working conditions according to the present invention; Figure 4 2 is a schematic diagram of a motion control structure according to an embodiment of the present invention.

[0017] Figure 5 It is a structural schematic diagram of a motion control system of a robot serving in extreme working conditions according to the present invention. DETAILED DESCRIPTION

[0018] Reference will now be made in detail to specific embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Although the present invention will be described in conjunction with specific embodiments, it will be understood that the present invention is not intended to be limited to those embodiments. On the contrary, it is intended to cover variations, modifications, and equivalents within the spirit and scope of the present invention as defined by the appended claims. It should be noted that the method steps described herein can be implemented by any functional block or functional arrangement, and any functional block or functional arrangement can be implemented as a physical entity or a logical entity, or a combination of the two.

[0019] In order to enable those skilled in the art to better understand the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] Note: The following example is only a specific example and is not intended to limit the embodiments of the present invention to the following specific steps, values, conditions, data, sequence, etc. Those skilled in the art can apply the concepts of the present invention to construct more embodiments not described in this specification by reading this specification.

[0021] The extreme working condition service robot of this embodiment is a UHV line maintenance robot, and its structure is as follows: Figure 1 and Figure 2 As shown in the figure, the UHV line maintenance robot is an intelligent maintenance device specifically designed for UHV transmission lines (typically voltage levels of 1000 kV and above). It can replace or assist manual labor in performing difficult and high-risk tasks such as line inspection, fault detection, and maintenance. Its core components are a multifunctional manipulator, a mobile chassis, and a multi-angle, wide-field-of-view camera system. It can perform precise operations such as conductor inspection, insulator replacement, and emergency repairs on UHV lines. In actual use, UHV line maintenance robots often face extreme operating conditions such as strong electromagnetic interference, high altitudes, and severe temperature fluctuations, as well as multiple sources of disturbances caused by dynamic changes in the internal structure, such as perturbations of mechanical parameters and unmodeled dynamics. These disturbances can cause instability in the robot's control system, thereby affecting key performance indicators such as motion accuracy, response speed, and trajectory tracking. To ensure high-precision and efficient control of the robot, the UHV line maintenance robot requires a motion control method that can withstand these extreme conditions.

[0022] See also Figure 3 As shown, an embodiment of the present invention provides a motion control method for a robot serving in extreme working conditions, comprising the following steps: S100, estimation of the robot's lumped disturbance using a fuzzy approximator based on an adaptive update law; S200, describing the dynamic characteristics of the service robot under extreme working conditions using a disturbed second-order system model based on the lumped disturbance; S300, designing the robot's self-tuning predetermined performance function; S400, designing a coordinate transformation mechanism according to the self-tuning predetermined performance function; S500 , combining the dynamic characteristics, the coordinate transformation mechanism, and the backstepping control strategy to design a robot motion controller based on a global predetermined performance control law.

[0023] The beneficial effects of the present invention are: 1. The present invention proposes a new self-tuning predetermined performance function, which adaptively adjusts the boundaries of the performance function according to the output feedback error, relaxing the strict assumptions required by existing predetermined performance control designs, thereby providing a new solution for achieving predetermined performance control of robots serving in extreme working conditions.

[0024] 2. This paper proposes a motion controller based on a global predetermined performance control law. This controller incorporates dynamics-based feedforward compensation, disturbance compensation using a fuzzy estimator, feedback control of predetermined performance, and fixed-time convergence regulation. Compared to existing methods, this method not only ensures that robots operating in extreme conditions maintain predetermined performance despite disturbances, but also accelerates error convergence.

[0025] Preferably, in another embodiment of the present application, the step of S200, describing the dynamic characteristics of the service robot under extreme working conditions using a disturbed second-order system model according to the lumped disturbance, includes: First, external torque disturbance, friction and uncertainty dynamics are summarized as disturbance ; In this case, the dynamics of the robot in extreme working conditions can be described as: ; in, , , are the robot position, velocity and acceleration respectively; 、 and are the inertia matrix, Coriolis force matrix and gravity matrix respectively; is the input torque; The above formula can be rewritten as: ; make ; ; ; ; ; ; ; ; The dynamics of the robot in service under extreme working conditions can be expressed using the following disturbed two-level system model: ; Where, and is the system status; and System status and The derivative of and is the coefficient; is the control input; b is the coefficient of the control input; interference terms that can be theoretically modeled; is the lumped disturbance; For output feedback.

[0026] To identify the lumped disturbance , the fuzzy approximator based on the adaptive update law is designed as follows: ; in, ; Where, is the adaptive update law; for The derivative of Lumped disturbance estimated value of; is the basis vector function; T is the matrix transpose; 、 and For adjustable gain; is the control variable.

[0027] The adaptive update law is a core component of adaptive control, used to adjust controller parameters online to address system model uncertainties (such as unknown parameters and time-varying disturbances). Its core concept is to estimate system parameters in real time and dynamically modify the control strategy to achieve the desired system performance.

[0028] The basis vector function is defined as: ; Where, is the number of the fuzzy rule, is a Gaussian type function.

[0029] Preferably, in another embodiment of the present application, the step of designing a self-tuning predetermined performance function of the robot in S300 includes: In order to realize the predetermined performance control of the above-mentioned robot system, the following self-tuning predetermined performance function is constructed as shown in the following formula: ; in and is the time-varying weight factor, abbreviated as and ; Represents a bounded performance function, abbreviated as .

[0030] Bounded Performance Function As shown in the following formula: ; Where, is the convergence speed; is an initial positive value; is a positive value for stable tracking accuracy.

[0031] Adaptive adjustment of time-varying weight factors is based on the following method and : ; Where, for and The current value of for and Adjusted value; To adjust the step size, it is a fixed value.

[0032] also, 、 and Initial value of , and The following design guidelines need to be observed: .

[0033] e is the output feedback error, is the initial output feedback error.

[0034] ; Where, is the output reference trajectory of the robot, Abbreviated as e.

[0035] Preferably, in another embodiment of the present application, the step of designing a coordinate transformation mechanism according to the self-tuning predetermined performance function in S400 includes: Combined with the above predetermined performance functions, the following auxiliary variables are designed: ; Furthermore, the design status The virtual reference is as follows: ; In the formula yes The derivative of is the output reference trajectory The derivative of and is the control gain.

[0036] Derivative of the virtual control law yes ,use To obtain it, a fuzzy approximator is constructed as follows: ; Where, is the basis vector function, is the adaptive update law, which is defined as follows: ; Where, , and is adjustable gain; Combine the above predetermined performance function and virtual reference , construct the following coordinate transformation mechanism:

[0037] Where, and is the error variable.

[0038] Preferably, in another embodiment of the present application, the step of designing a robot motion controller based on a global predetermined performance control law in combination with the dynamic characteristics, the coordinate transformation mechanism, and the backstepping control strategy in S500 includes: Backstepping control is a recursive design method for nonlinear systems, an extension of adaptive control and Lyapunov stability theory. Its core idea is to decompose a complex system into multiple subsystems by gradually constructing virtual control variables and Lyapunov functions, gradually stabilizing each layer and ultimately achieving global stability.

[0039] See also Figure 4 As shown, combined with the backstepping control strategy, a motion controller based on the global predetermined performance control law with the following form is designed: ; Right now: in, ; In the above, represents feedback control for predetermined performance, represents the dynamics-based feedforward compensation, represents disturbance compensation based on fuzzy estimator, Indicates fixed-time convergence regulation.

[0040] See also Figure 5 As shown, an embodiment of the present invention provides a motion control system for a robot serving in extreme working conditions, comprising: The lumped disturbance module is used to estimate the lumped disturbance of the robot based on the fuzzy approximator of the adaptive update law; a dynamics description module, in communication with the lumped disturbance module, for describing the dynamic characteristics of the service robot under extreme working conditions based on the lumped disturbance and using a disturbed second-order system model; A predetermined performance function module is used to design the robot's self-tuning predetermined performance function; a coordinate transformation mechanism module, in communication with the predetermined performance function module, for designing a coordinate transformation mechanism according to the self-tuning predetermined performance function; and A motion controller module is in communication with the dynamic representation module and the coordinate transformation mechanism module, and is used to combine the dynamic characteristics, the coordinate transformation mechanism and the backstepping control strategy to design a robot motion controller based on a global predetermined performance control law.

[0041] In summary, the beneficial effects of the present invention are: 1. The present invention proposes a new self-tuning predetermined performance function, which adaptively adjusts the boundaries of the performance function according to the output feedback error, relaxing the strict assumptions required by existing predetermined performance control designs, thereby providing a new solution for achieving predetermined performance control of robots serving in extreme working conditions.

[0042] 2. This paper proposes a motion controller based on a global predetermined performance control law. This controller incorporates dynamics-based feedforward compensation, disturbance compensation using a fuzzy estimator, feedback control of predetermined performance, and fixed-time convergence regulation. Compared to existing methods, this method not only ensures that robots operating in extreme conditions maintain predetermined performance despite disturbances, but also accelerates error convergence.

[0043] Specifically, this embodiment corresponds one-to-one to the above method embodiment, and the functions of each module have been described in detail in the corresponding method embodiment, so they will not be repeated here.

[0044] Based on the same inventive concept, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, all or part of the method steps of the above method are implemented.

[0045] The present invention may implement all or part of the above-described method processes by instructing related hardware through a computer program. The computer program may be stored in a computer-readable storage medium. When executed by a processor, the computer program may implement the steps of each of the above-described method embodiments. The computer program includes computer program code, which may be in source code form, object code form, an executable file, or some intermediate form. Computer-readable media may include any entity or device capable of carrying computer program code, recording media, USB flash drives, removable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunications signals, and software distribution media. It should be noted that the content of a computer-readable medium may be appropriately expanded or reduced based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, computer-readable media do not include electric carrier signals or telecommunications signals.

[0046] Based on the same inventive concept, an embodiment of the present application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program running on the processor, and when the processor executes the computer program, all or part of the method steps in the above method are implemented.

[0047] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor. The processor is the control center of a computer device, connecting all parts of the entire computer device using various interfaces and circuits.

[0048] The memory can be used to store computer programs and / or modules. The processor implements the various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and accessing the data stored in the memory. The memory may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (e.g., a sound playback function, an image playback function, etc.); the data storage area may store data generated based on the use of the mobile phone (e.g., audio data, video data, etc.). Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0049] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, servers, 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 magnetic disk storage and optical storage) containing computer-usable program code.

[0050] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), servers, 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.

[0051] 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.

[0052] 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 The steps for the function specified in one or more boxes.

[0053] 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.

Claims

1. A motion control method for a robot serving in extreme working conditions, characterized in that: The following steps are involved: A fuzzy approximator based on an adaptive update law estimates the robot's lumped disturbance; According to the lumped disturbance, the dynamic characteristics of the service robot under extreme working conditions are described using a disturbed second-order system model; Design the robot's self-tuning predetermined performance function; designing a coordinate transformation mechanism according to the self-tuning predetermined performance function; Combining the dynamic characteristics, the coordinate transformation mechanism and the backstepping control strategy, a robot motion controller based on a global predetermined performance control law is designed.

2. The motion control method for a robot in extreme working conditions according to claim 1, characterized in that: The method for estimating the lumped disturbance of the robot using the fuzzy approximator based on the adaptive update law is shown in the following formula: ； The adaptive update law is as follows: ； Where, is the adaptive update law; for The derivative of Lumped disturbance estimated value of; is the basis vector function; T is the matrix transpose; 、 and For adjustable gain; is the control variable.

3. The motion control method for a robot in extreme working conditions according to claim 1, characterized in that: The step of expressing the dynamic characteristics of the service robot under extreme working conditions using a disturbed second-order system model based on the lumped disturbance includes: The disturbed second-order system model is shown as follows: ； in, ; ; ; ; ; ; ; ; Where, and is the system status; and System status and The derivative of and is the coefficient; is the control input; b is the coefficient of the control input; interference terms that can be theoretically modeled; is the lumped disturbance; For output feedback; , , are the robot position, velocity and acceleration respectively; 、 and are the inertia matrix, Coriolis force matrix and gravity matrix respectively; is the input torque; For disturbance.

4. The motion control method for a robot in extreme working conditions according to claim 1, characterized in that: The self-tuning predetermined performance function of the designed robot is shown in the following formula: ； Adaptive adjustment of time-varying weight factors is based on the following method and : ； Among them, the bounded performance function As shown in the following formula: ； Where, is the convergence speed; is an initial positive value; is a positive value regarding stable tracking accuracy; for and The current value of for and Adjusted value; is the adjustment step; e is the output feedback error; t is the time.

5. The motion control method for a robot serving in extreme working conditions according to claim 1, characterized in that: The coordinate transformation mechanism designed according to the self-tuning predetermined performance function is shown as follows: ； Among them, the virtual reference As shown in the following formula: ； Where, and is the error variable; is a bounded performance function The derivative of Output reference trajectory The derivative of and is an adjustable control gain; is the system state; e is the output feedback error; and is the time-varying weight factor.

6. The motion control method for a robot serving in extreme working conditions according to claim 1, characterized in that: The steps of designing a robot motion controller based on a global predetermined performance control law by combining the dynamic characteristics, the coordinate transformation mechanism, and the backstepping control strategy include: The robot motion controller u is shown as follows: ； Among them, fixed time convergence adjustment As shown in the following formula: ； Fuzzy Approximator As shown in the following formula: ； Where, and is an adjustable control gain; is the basis vector function; is the adaptive update law; and is the system status; and is the coefficient; e is the output feedback error; and is the time-varying weight factor; is a bounded performance function; Lumped disturbance estimated value of; is the disturbance term that can be theoretically modeled; b is the control input coefficient; Z1 and Z2 are error variables.

7. A motion control system for a robot serving in extreme working conditions, characterized in that: include: The lumped disturbance module is used to estimate the lumped disturbance of the robot based on the fuzzy approximator of the adaptive update law; a dynamics description module, in communication with the lumped disturbance module, for describing the dynamic characteristics of the service robot under extreme working conditions based on the lumped disturbance and using a disturbed second-order system model; A predetermined performance function module is used to design the robot's self-tuning predetermined performance function; a coordinate transformation mechanism module, in communication with the predetermined performance function module, for designing a coordinate transformation mechanism based on the self-tuning predetermined performance function; as well as, A motion controller module is in communication with the dynamic representation module and the coordinate transformation mechanism module, and is used to combine the dynamic characteristics, the coordinate transformation mechanism and the backstepping control strategy to design a robot motion controller based on a global predetermined performance control law.

8. The motion control system of the robot serving in extreme working conditions according to claim 7, characterized in that: The lumped disturbance module is used to: The method for estimating the lumped disturbance of the robot using the fuzzy approximator based on the adaptive update law is shown in the following formula: ； Among them, the method of adaptive update law is shown as follows: ； Where, is the adaptive update law; for The derivative of Lumped disturbance estimated value of; is the basis vector function; T is the matrix transpose; 、 and For adjustable gain; is the control variable.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the motion control method for a robot serving in extreme working conditions according to any one of claims 1 to 7 is implemented.

10. An electronic device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein: When the processor runs the computer program, the motion control method for the robot serving in extreme working conditions is implemented according to any one of claims 1 to 7.

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