Adaptive predefined time control method for single-link robotic arm based on event triggering

Abstract

The present invention relates to the field of robot control technology. The present invention discloses an adaptive predefined time control method for a single-link robot arm based on event triggering, including determining the parameters of the robot arm through modeling; designing a control protocol of an event triggering mechanism to adapt to the measurement error of the system output; establishing a first virtual controller and a second virtual controller through coordinate transformation and designing an adaptive law, and constructing an event triggering controller in combination with an event triggering mechanism to achieve the predefined time stability of the robot arm. The present invention effectively improves the control accuracy and robustness of the robot arm through adaptive control and event triggering mechanisms, while reducing the computational complexity, simplifying the parameter estimation process, and enhancing the real-time performance, providing an efficient and stable solution for the control of intelligent robots and automation technologies in actual industrial applications.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to an event-triggered self-adaptive predefined time control method for a single-link robot arm. Background Art

[0002] The robotic arm is a complex mechanical system that mimics the movement of the human arm and has high nonlinearity, strong coupling and superior controllability.

[0003] With the continuous development of control technology, many control algorithms have been successfully applied to the control of robot manipulators and achieved remarkable results. For example, PID control is one of the most widely used control algorithms. The PID controller determines the control input by calculating the error between the desired position and the actual position and its integral and derivative, thereby adjusting the movement of the robot manipulator. However, during the control process, the complex parameter adjustment process of the PID controller makes the controller design and debugging complicated. In addition, in the presence of interference or when a fast response is required, PID control may not be able to adjust the control input in time, resulting in system response delay or overshoot. Therefore, it becomes imperative to develop more robust control algorithms.

[0004] At the same time, in order to further improve the control performance, many control algorithms give priority to solving the inherent uncertainty of the manipulator system. Adaptive control provides semi-global or global stability for nonlinear systems with parameter uncertainty. However, with the increasing demand for higher performance and the intensification of system uncertainty, the application of adaptive control to increasingly complex systems faces many challenges, including the complexity of the adaptive controller structure and the inability of adaptive control systems to guarantee steady-state errors under disturbances. In recent years, the emergence of adaptive neural network control has provided a new perspective to overcome the limitations of traditional adaptive control methods. The adaptive neural network control strategy has a powerful nonlinear function approximation capability and can accurately simulate the dynamic behavior of complex systems, thereby improving control accuracy and adaptability. Therefore, adaptive control strategies using neural network approximation have been widely used in nonlinear systems. The above research has achieved positive results in improving the performance and efficiency of robot manipulator trajectory tracking. However, the transmission of control signals is usually carried out at fixed time intervals, which requires a shorter sampling period to ensure stability and effectiveness, but too high a sampling rate will lead to unnecessary frequent updates after the system is stable, thereby wasting communication resources. The event trigger mechanism effectively solves the above problems. In addition, in actual industrial engineering, high-performance time response of the robot system is also required, so it is of practical significance to take the predefined time control strategy into consideration from the perspective of theoretical analysis. Based on the above analysis, in the present invention, considering the robot system with uncertainty, we design an adaptive predefined time control strategy for a single-link robot based on an event trigger mechanism, which ultimately enables the robot to achieve trajectory tracking.

[0005] The present invention combines the event triggering mechanism of time-varying threshold with the adaptive neural network to solve the above problems.

[0006] In terms of research problems, the control methods discussed above mainly focus on the asymptotic stability or uniformly boundedness of the system. This means that it may not be feasible to achieve system stability within a finite time frame or to achieve a stable control target within a specified time. In scenarios where precise control of the operation of a robotic manipulator is required, traditional incremental control algorithms often fail to meet these practical requirements. To overcome this challenge, finite-time and fixed-time control theories are introduced in robotic manipulator control. However, the convergence efficiency of the finite-time control strategy, especially its convergence speed and performance, depends largely on the design of the control parameters and the initial conditions of the system. A significant advantage of the finite-time control strategy is that it can ensure the stability and tracking accuracy of the system within a finite time, which is particularly important for application scenarios that require fast response and high precision. However, how to optimize the control parameters to achieve faster convergence speed and better control performance while maintaining the robustness and stability of the system is a problem that requires in-depth research.

[0007] In contrast, fixed-time control strategies have stronger constraints on convergence time, that is, no matter what the initial conditions of the system are, they can be guaranteed to reach a stable state within a fixed time. This feature makes fixed-time control strategies more adaptable when dealing with systems with uncertainties or time-varying characteristics. However, the design and implementation of fixed-time control strategies are usually more complex than finite-time control strategies, requiring more theoretical support and technical means. At the same time, fixed-time control does not directly establish the relationship between convergence time and controller parameters, which may complicate the design and adjustment of parameters and make it difficult to match the needs of the actual system.

[0008] In recent years, predefined time control strategies have successfully overcome the limitations of finite time and fixed time control. This method can predetermine the upper limit of the system stabilization time and ensure that the system has high performance time response.

[0009] In terms of communication resources, the transmission of control signals is usually carried out at fixed time intervals, which requires a shorter sampling period to ensure stability and effectiveness. The present invention combines the event triggering mechanism of time-varying thresholds with an adaptive neural network to solve the above problem. Summary of the invention

[0010] In view of the above existing problems, the present invention is proposed.

[0011] Therefore, the present invention provides an event-triggered single-link manipulator adaptive predefined time control method, which can use the time-varying threshold event trigger mechanism to achieve predetermined time tracking. Compared with the traditional time trigger method, the time-varying threshold event trigger mechanism can not only significantly reduce the waste of communication resources, but also ensure that the system performance is not damaged. In addition, the method ensures that the tracking error converges to a small range near the origin within a predetermined time frame and ensures that all signals in the closed-loop system are bounded. By adjusting the parameters related to the controller, we can predefine the upper limit of the convergence time.

[0012] To solve the above technical problems, the present invention provides the following technical solutions, a method for adaptive predefined time control of a single-link robotic arm based on event triggering, comprising: determining the parameters of the robotic arm through modeling; designing a control protocol of an event triggering mechanism to adapt to the measurement error of the system output; establishing a first virtual controller and a second virtual controller through coordinate transformation and designing an adaptive law, and constructing an event triggering controller in combination with the event triggering mechanism to achieve the predefined time stability of the robotic arm.

[0013] As a preferred scheme of the event-triggered single-link robotic arm adaptive predefined time control method described in the present invention, the parameters of the robotic arm include determining the angle, angular velocity, angular acceleration, output torque, moment of inertia, robotic arm mass, robotic arm length, viscous friction coefficient, disturbance and gravitational acceleration of the robotic arm.

[0014] As a preferred solution of the method for adaptive predefined time control of a single-link mechanical arm based on event triggering according to the present invention, the modeling includes: the modeling of the single-link mechanical arm is:

[0015] ,

[0016] in, represents the angle of the robot arm, represents the angular velocity of the robot arm, represents the angular acceleration of the robot arm, represents the output torque, represents the moment of inertia, Represents the mass of the robot arm, represents the length of the robot arm, is the viscous friction coefficient, represents a continuous bounded disturbance, Represents the acceleration due to gravity.

[0017] set up

[0018] ,

[0019] ,

[0020] ,

[0021] in, represents the system input, and represents the output of the system, represents an uncertain nonlinear function, represents a known constant, , is the state variable of the system, , is the coordinate component in the original coordinate system.

[0022] As a preferred solution of the method for adaptive predefined time control of a single-link manipulator based on event triggering of the present invention, the control protocol includes: the control protocol of the event triggering mechanism is designed as follows:

[0023] ,

[0024] in, represents the measurement error, , represents a positive parameter, is the control input signal, It is a time-dependent The function of is the time point when the next event is triggered. It means taking the lower bound. is the set of real numbers, is the weight coefficient.

[0025] As a preferred solution of the method for adaptive predefined time control of a single-link manipulator based on event triggering of the present invention, the establishment of the first virtual control includes designing a control protocol in combination with an event triggering mechanism, and the coordinate transformation is defined as follows:

[0026] ,

[0027] in, are the new coordinate components, , is the coordinate component in the original coordinate system, represents the ideal tracking signal, Represents the first virtual controller. The specific expression is as follows:

[0028] ,

[0029] ,

[0030] in represents the disturbance term, is a positive constant, and Represents a predefined time parameter, is the expected value of the first virtual controller, is an estimate of the ideal tracking signal.

[0031] As a preferred solution of the event-triggered single-link robotic arm adaptive predefined time control method of the present invention, wherein: the second virtual controller includes: designing a second virtual controller And predefined adaptive law :

[0032] ,

[0033] ,

[0034] ,

[0035] in, is the expected value of the first virtual controller, is the gain related to the system dynamics, Represents a constant. , , is an adaptive parameter, is a positive proportionality coefficient, is the switching function, is the step size parameter.

[0036] As a preferred solution of the method for adaptive predefined time control of a single-link robotic arm based on event triggering according to the present invention, the construction of an event triggering controller includes combining the above-mentioned virtual controller with the event triggering mechanism to construct the following event triggering controller:

[0037] ,

[0038] in, is the expected value;

[0039] Combined with the event trigger mechanism again, there is a continuous time-varying parameter , satisfying the conditions , ,

[0040] and , ;

[0041] ,

[0042] in ,because and , can be obtained ;

[0043] We can get:

[0044] ,

[0045] Controller based on event triggering mechanism at predefined time Under the control of the closed-loop system, the system can achieve stability within a predefined time. is a normal number, is the gain coefficient, For controller The rounding operation of the sign function.

[0046] As a preferred solution of the event-triggered single-link mechanical arm adaptive predefined time control system described in the present invention, it includes: a modeling module, an event trigger mechanism design module, a virtual controller establishment module, and an event trigger controller construction module;

[0047] The modeling module is used to determine the dynamic parameters of the manipulator, including angle, angular velocity, angular acceleration, output torque, moment of inertia, manipulator mass, length, viscous friction coefficient, disturbance and gravitational acceleration, and to represent the dynamic behavior of the manipulator through a mathematical model;

[0048] The event trigger mechanism design module designs a control protocol for the event trigger mechanism. The protocol adjusts the control input signal according to the measurement error of the system output. This module ensures that the control input is updated only when the error exceeds a certain threshold, thereby reducing the computational burden and communication frequency.

[0049] The virtual controller establishment module establishes a first virtual controller and a second virtual controller through coordinate transformation, and designs an adaptive law. The virtual controller is combined with an event trigger mechanism to achieve a predefined time stability of the robot arm;

[0050] The event-triggered controller building module combines the virtual controller and the event-triggered mechanism to build a complete event-triggered controller. The module ensures that the closed-loop system reaches a stable state within a predefined time.

[0051] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of a method for adaptively controlling a single-link robotic arm based on event triggering and predefined time are implemented.

[0052] A computer-readable storage medium stores a computer program thereon, characterized in that when the computer program is executed by a processor, the steps of a method for adaptively controlling a single-link robotic arm based on event triggering and predefined time are implemented.

[0053] Beneficial effects of the present invention: The present invention first models the single-link robotic arm system and simultaneously constructs an event trigger mechanism to ensure that while meeting the control requirements, network communication resources are effectively saved, thereby improving economic benefits. In the process of designing the adaptive backstepping controller, a predefined time control strategy is introduced to improve the time performance of the system to a relatively good level. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0055] Figure 1 A schematic flow chart of a method for adaptively controlling a single-link robotic arm at a predefined time based on event triggering provided by an embodiment of the present invention.

[0056] Figure 2 A schematic diagram of working modules of an event-triggered single-link robotic arm adaptive predefined time control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0058] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0059] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0060] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0061] Meanwhile, in the description of the present invention, it should be noted that the orientation or positional relationship indicated by terms such as "upper, lower, inner, and outer" is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, the terms "first, second, or third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0062] Unless otherwise clearly defined and limited in the present invention, the terms "installed, connected, and coupled" shall be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can also be a mechanical connection, an electrical connection, or a direct connection, and can also be indirectly connected through an intermediate medium, or can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] Example 1, referring to Figure 1 , is the first embodiment of the present invention. This embodiment provides an adaptive predefined time control method for a single-link manipulator based on event triggering, including:

[0064] S1: Determine the parameters of the manipulator through modeling;

[0065] S2: Design the control protocol of the event-triggering mechanism to adapt to the measurement error of the system output;

[0066] S3: Establish a first virtual controller and a second virtual controller through coordinate transformation and design the adaptation law, and construct an event-triggering controller in combination with the event-triggering mechanism to achieve the predefined time stability of the manipulator.

[0067] The following are some lemmas that may be used in the present invention.

[0068] Lemma 1:

[0069] ,

[0070] where , and is a constant.

[0071] Lemma 2: For any , , the following inequality holds:

[0072] ,

[0073] Lemma 3:

[0074] ,

[0075] in and .

[0076] Lemma 4: For the system , define a continuous function And establish parameters , , To meet the conditions:

[0077] ,

[0078] At this point, the trajectory of the system is Predefined Time Stable (PPTS), and its convergence region is:

[0079] ,

[0080] in, represents the settling time and satisfies the condition , For its upper limit.

[0081] Lemma 5

[0082] ,

[0083] in is a constant, .

[0084] Lemma 6:

[0085] ,

[0086] in, , , , is a constant, and is a non-negative function. If , then, for , Heng established.

[0087] Lemma 7:

[0088] ,

[0089] in, , , , , , .

[0090] Theorem 1: Considering the robotic arm system, virtual controller, actual controller, and adaptive law, under the event-triggered mechanism and Lemma 4, the system is a PPTS, and the system error signal converges to a set within , where represents the settling time and satisfies , and all signals in the closed-loop robotic arm system are bounded.

[0091] Proof: The following Lyapunov function has been designed:

[0092] ,

[0093] The first derivative of

[0094] ;

[0095] Combining Lemma 5, we can obtain:

[0096] ,

[0097] Define the second Lyapunov function:

[0098] ,

[0099] where represents the adaptive parameter error, and r > 0 represents a constant.

[0100] The first derivative of

[0101] ,

[0102] Combining the first Lyapunov function, we can get:

[0103] ,

[0104] where represents an uncertain nonlinear function.

[0105] Using the RBF neural network and combining Lemma 1, we fit the above nonlinearity:

[0106] ,

[0107] where

[0108] ,

[0109] where , represents a constant, .also, As the input of RBFNN, Represents the output vector of the hidden layer nodes of RBFNN.

[0110] Substituting in, we get:

[0111] ,

[0112] It can be expressed as follows:

[0113] ;

[0114] in, and .

[0115] Through further analysis, we can easily get: .

[0116] Combined with Lemma 5, the second virtual controller And predefined adaptive law , and further obtained:

[0117] ;

[0118] Substituting the above formula into:

[0119] ;

[0120] in, .

[0121] At this time, substitute the adaptive law into the above formula:

[0122] ,

[0123] According to Young's inequality:

[0124] ,

[0125] Applying Lemma 3, we can obtain:

[0126] ,

[0127] Substituting the above results into We can get:

[0128] ;

[0129] Applying Lemma 7, we obtain the following inequality:

[0130] ,

[0131] From the adaptive law, we can get:

[0132] ;

[0133] ,

[0134] Substituting the above results into the equation, we get:

[0135] ,

[0136] in, , .

[0137] Applying Lemma 2, the following inequality holds:

[0138] ,

[0139] ,

[0140] Substituting the above formula into the equation yields:

[0141] ,

[0142] Applying Lemma 2 again, we can obtain the following inequality:

[0143] ,

[0144] ,

[0145] Integrate the inequalities, It can be expressed as follows:

[0146] ,

[0147] in, is a positive constant.

[0148] According to Lemma 4 and the above inequality, the system is PPTS, and the error signal Can converge to a compact set:

[0149] ,

[0150] in, Indicates the settling time, satisfying . From now on, the convergence of the system in the predefined time has been proved.

[0151] Embodiment 2, the second embodiment of the present invention, is different from the previous embodiment in that:

[0152] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0153] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0154] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0155] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0156] Example 4, reference Figure 2 , which is an embodiment of the present invention, provides an event-triggered single-link robotic arm adaptive predefined time control system, characterized by: comprising a modeling module 1, an event triggering mechanism design module 2, a virtual controller establishment module 3, and an event triggering controller construction module 4;

[0157] The modeling module 1 is used to determine the dynamic parameters of the robot arm, including angle, angular velocity, angular acceleration, output torque, moment of inertia, robot arm mass, length, viscous friction coefficient, disturbance and gravity acceleration, and to represent the dynamic behavior of the robot arm through a mathematical model;

[0158] The event trigger mechanism design module 2 designs a control protocol for the event trigger mechanism. The protocol adjusts the control input signal according to the measurement error of the system output. This module ensures that the control input is updated only when the error exceeds a certain threshold, thereby reducing the computational burden and communication frequency.

[0159] The virtual controller establishment module 3 establishes the first virtual controller and the second virtual controller through coordinate transformation, and designs an adaptive law. The virtual controller is combined with an event trigger mechanism to achieve a predefined time stability of the robot arm;

[0160] The event-triggered controller construction module 4 combines the virtual controller and the event-triggered mechanism to construct a complete event-triggered controller, which ensures that the closed-loop system reaches a stable state within a predefined time.

[0161] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An adaptive predefined time control method for a single-link robotic arm based on event triggering, characterized in that: include, Determine the parameters of the robot arm through modeling; The parameters of the robot arm include the angle, angular velocity, angular acceleration, output torque, moment of inertia, mass, length, viscous friction coefficient, disturbance and gravitational acceleration of the robot arm; The modeling includes the modeling of a single-link robotic arm as follows: Where q∈R represents the angle of the robot arm, R is a real number set, represents the angular velocity of the robot arm, represents the angular acceleration of the robot arm, τ∈R represents the output torque, represents the moment of inertia, m represents the mass of the robot, L represents the length of the robot, c0 represents the viscous friction coefficient, d represents the continuous bounded disturbance, g represents the gravitational acceleration, set up Among them, u = τ represents the system input, and y = x1 represents the system output, f represents an uncertain nonlinear function, g1 represents a known constant, is the state variable of the system, x1 and x2 are the coordinate components in the original coordinate system; Design control protocols for event-triggered mechanisms to accommodate measurement errors in system outputs; The control protocol includes that the control protocol of the event trigger mechanism is designed as follows: where \(e(t)=\psi(t)-u(t)\) represents the measurement error, \(0 < v < 1\), \(r_1\) represents a positive parameter, \(u(t)\) is the control input signal, and \(\psi(t k )\) is a function that depends on the time point \(t k \), and \(t k+1 \) is the time point at which the next event is triggered, \(\inf\) represents taking the infimum, \(\mathbb{R}\) is the set of real numbers, and \(v\) is the weight coefficient; The first virtual controller and the second virtual controller are established through coordinate transformation and the adaptive law is designed. The event-triggered controller is constructed in combination with the event-triggered mechanism to achieve the predefined time stability of the robot arm. The establishment of the first virtual controller includes designing a control protocol in combination with an event trigger mechanism, and the coordinate transformation is defined as follows: Among them, z1 and z2 are the new coordinate components, x1 and x2 are the coordinate components in the original coordinate system, and y d represents the ideal tracking signal, α1 represents the first virtual controller, and the specific expression is as follows: Where ε1 represents the disturbance term, 0<β<1 is a positive constant, and T c >0 represents a predefined time parameter, is the expected value of the first virtual controller, is an estimate of the ideal tracking signal; the second virtual controller includes designing a second virtual controller α2 and a predefined adaptive law in, is the expected value of the first virtual controller, g1 is the gain related to the system dynamics, ε2>0 represents a constant, is an adaptive parameter, r is a positive proportional coefficient, S(x) is a switching function, and ρ is a step size parameter.

2. The method for adaptive predefined time control of a single-link robot arm based on event triggering according to claim 1, characterized in that: The construction of the event trigger controller includes combining the above virtual controller with the event trigger mechanism to construct the following event trigger controller: in, is the expected value; Combined with the event trigger mechanism, there exists a continuous time-varying parameter τ2(t) that satisfies the condition τ2(t k )=0,τ2(t k+1 )=±1, and |τ2(t)|≤1, where τ1(t)=τ2(t)sgn|u(t)|; since |τ2(t|≤1 and Available We can get: Under the control of the controller u(t) based on the event trigger mechanism at a predefined time, the closed-loop system can achieve stability at a predefined time, where ξ is a positive constant, ν is a gain coefficient, is the rounding operation of the sign function of the controller u(t).

3. A system using the event-triggered single-link robotic arm adaptive predefined time control method as claimed in any one of claims 1 to 2, characterized in that: It includes modeling module, event trigger mechanism design module, virtual controller establishment module and event trigger controller construction module; The modeling module is used to determine the dynamic parameters of the manipulator, including angle, angular velocity, angular acceleration, output torque, moment of inertia, manipulator mass, length, viscous friction coefficient, disturbance and gravitational acceleration; The event trigger mechanism design module designs a control protocol for the event trigger mechanism, wherein the protocol adjusts the control input signal according to the measurement error of the system output; The virtual controller establishment module establishes the first virtual controller and the second virtual controller through coordinate transformation, and designs an adaptive law, and the virtual controller is combined with an event trigger mechanism; The event-triggered controller building module combines the virtual controller and the event-triggered mechanism to build a complete event-triggered controller.

4. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 2 are implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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