Inspection unmanned aerial vehicle event triggering preset performance control method for power transmission line insulator state monitoring

Abstract

The invention discloses a patrol unmanned aerial vehicle event triggering preset performance control method for power transmission line insulator state monitoring, and belongs to the field of unmanned aerial vehicle control. Aiming at the problems that the trajectory tracking precision is insufficient, the flight performance constraint is difficult to meet and the communication resource utilization efficiency is not high in an existing power transmission line inspection unmanned aerial vehicle in an inspection task, a trajectory tracking simplified control model based on the dynamic characteristics of the unmanned aerial vehicle is constructed; designing a trajectory tracking sliding mode variable, and introducing a preset performance function to convert a constrained sliding mode variable into an unconstrained preset performance error variable; on the basis, a preset performance trajectory tracking controller is designed; judging whether to update the current position loop control instruction or not through an event triggering mechanism; and if the position loop control instruction is updated, based on the updated position loop control instruction, calculating and generating a total thrust instruction, an expected attitude angle instruction and an expected angular velocity instruction of the inspection unmanned aerial vehicle, and realizing preset performance event trigger control of the inspection track of the inspection unmanned aerial vehicle. The method is mainly used for power transmission line inspection.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) control. Background Technology

[0002] In recent years, with the continuous expansion of my country's power system and the increasingly complex operating environment of transmission lines, the demand for intelligent and high-performance control of inspection drones has become increasingly prominent as an important piece of equipment to ensure the safe operation of transmission lines. Traditional manual inspection methods are difficult to meet the requirements of modern power grid operation in terms of real-time performance, efficiency, and safety. Drones, with their advantages of low cost, high mobility, and multi-functionality, have become an important tool for transmission line condition perception and hidden danger investigation, playing a crucial role, especially in applications such as insulator condition monitoring and inspection. For example, they have irreplaceable advantages in typical application scenarios such as insulator defect identification and pollution level detection to prevent excessive insulator leakage current. However, with the increasing complexity of application scenarios, during insulator condition monitoring and inspection tasks, inspection drones often need to fly close to the transmission line and maintain high trajectory tracking accuracy and attitude stability in the insulator target area. This presents new technical bottlenecks for the stable control of drones in fast, high-precision trajectory tracking and strong interference environments. Existing trajectory tracking control methods struggle to ensure that UAVs consistently meet preset dynamic and steady-state performance requirements throughout the entire inspection mission cycle. This leads to position errors easily exceeding limits under complex operating conditions, impacting the quality of insulator inspection and monitoring, as well as the safety of inspection operations. Furthermore, since the position loop bandwidth is typically lower than that of the velocity and attitude loops, traditional event-triggered position control methods are prone to redundant triggering during state updates, resulting in inefficient use of communication resources and hindering the stable operation of inspection UAVs in long-endurance, high-frequency insulator inspection missions. Summary of the Invention

[0003] This invention addresses the problems of insufficient trajectory tracking accuracy, unmet flight performance constraints, and low communication resource utilization efficiency of existing transmission line inspection drones, especially in insulator condition monitoring applications aimed at preventing excessive leakage current in insulators. It proposes an event-triggered preset performance control method for transmission line insulator condition monitoring drones.

[0004] The present invention discloses an event-triggered preset performance control method for inspection drones used for monitoring the condition of insulators in transmission lines, comprising:

[0005] Step 1: Based on the dynamic characteristics of the UAV for monitoring the condition of transmission line insulators, establish a system dynamic model, and construct a simplified control model for the trajectory tracking of the UAV by means of variable substitution and model simplification.

[0006] Step 2: Construct sliding mode variables for the trajectory tracking of the inspection drone. Design a preset performance function based on the preset state response performance requirements of the drone throughout the entire inspection mission. Use the preset performance function to perform a nonlinear transformation on the sliding mode variables, converting the constrained sliding mode variables into unconstrained preset performance error variables.

[0007] Step 3: Based on the preset performance error variables, design a preset performance trajectory tracking controller for the simplified control model; calculate the position loop control command for the inspection UAV;

[0008] Step 4: Based on the current position loop control command and the position loop control command at the previous trigger time, determine whether the current position loop control command needs to be updated;

[0009] When the judgment result indicates that an update is needed, the total thrust command, desired attitude angle command, and desired angular velocity command of the inspection UAV are calculated and generated based on the updated position loop control command.

[0010] Step 5: Input the total thrust, desired attitude, and desired angular velocity signals into the speed loop and attitude loop control modules of the inspection drone itself, and drive the drone to perform preset performance event-triggered trajectory tracking control on the power transmission line inspection trajectory.

[0011] Furthermore, in this invention, the specific expression of the system dynamics model in step one is as follows:

[0012] (1)

[0013] in: Let be the position vector of the UAV's centroid. , , These represent the positions of the UAV's center of mass along the x, y, and z coordinate axes, respectively. Let the velocity vector be the center of mass. , , These represent the velocities of the UAV's center of mass along the x, y, and z coordinate axes, respectively. Let them be Euler angle vectors. , , These represent the roll angle, pitch angle, and yaw angle of the UAV, respectively. It is the angular velocity vector. , , These represent the angular velocities of the UAV along the x, y, and z coordinate axes, respectively. For thrust vector, For the total thrust of the drone, The gravity vector M is the gravitational constant; M and These represent the mass and moment of inertia matrices of the UAV, respectively. Represents the torque vector. and These represent the total disturbances acting on the translational and rotational dynamics, respectively; where the velocity rotation matrix is... With attitude rotation matrix ; Represents a three-dimensional real vector space. Represents the space of a third-order real square matrix. Represents the rotation group in three-dimensional Euclidean space;

[0014] (2)

[0015] (3)

[0016] Among them, for any ,have , .

[0017] Furthermore, in this invention, the simplified control model for tracking the trajectory of the inspection drone in step one is as follows:

[0018] (4)

[0019] in: This is the input vector for UAV position tracking control. , , These represent the position tracking control inputs of the UAV in the x, y, and z coordinate axes, respectively. The total disturbance of the simplified control model for tracking the trajectory of the inspection drone. , , These represent the total disturbances of the simplified control model of the UAV in the x, y, and z coordinate axes, respectively.

[0020] Furthermore, in this invention, the method for constructing the sliding mode variable for trajectory tracking of the inspection drone in step two is as follows:

[0021] (5)

[0022] in: , , These are represented by the sliding surface variables in the x, y, and z coordinate axes, respectively. , , Let x, y, and z represent the expected velocities of the UAV's center of mass along the x, y, and z coordinate axes, respectively. , , These represent the desired positions of the UAV's center of mass along the x, y, and z coordinate axes, respectively. , , These are the sliding mode variable parameters corresponding to the x, y, and z coordinate axes, respectively.

[0023] Furthermore, in this invention, in step two, the formula for transforming the original constrained error into an unconstrained preset performance error variable is as follows:

[0024] (6)

[0025] in: , , These are the preset performance error variables in the x, y, and z coordinate axes, respectively. , , These are the preset performance functions for the x, y, and z coordinate axes, respectively.

[0026] (7)

[0027] in: , , These represent the initial value, final value, and convergence rate of the preset performance function along the x-axis, respectively. , , These represent the initial value, final value, and convergence rate of the preset performance function along the y-axis, respectively. , , These represent the initial value, final value, and convergence rate of the preset performance function along the z-axis, respectively. , , The settings must meet the following requirements. , , The preset trajectory tracking error constraint for power transmission line inspection drones is:

[0028] (8)

[0029] Furthermore, in this invention, in step three, the preset performance trajectory tracking controller is:

[0030] (9)

[0031] in: , , These represent the gains of the preset performance error exponents in the x, y, and z coordinate axes, respectively. , , These represent the preset performance error index gains in the x, y, and z coordinate axes, respectively. , , These represent the gain of the preset performance error integral term in the x, y, and z coordinate axes, respectively. , , These are represented as equivalent control terms in the x, y, and z coordinate axes, respectively. , , These are represented as the desired acceleration signals in the x, y, and z coordinate axes, respectively. , , The preset performance error sign function in the x, y, and z coordinate axes satisfies:

[0032] (10)

[0033] Furthermore, in this invention, the formula for determining whether the current position loop control command needs to be updated in step four is as follows:

[0034] (11)

[0035] in: The current trigger time, For the next triggering time, , , The x, y, and z coordinate axes represent the event trigger thresholds, respectively. o represents a logical "OR", meaning that when the change in control input in any direction exceeds its corresponding threshold, a control command update is triggered. t is the current time, which is a continuous quantity.

[0036] Furthermore, in this invention, the method for calculating and generating the total thrust command, desired attitude angle command, and desired angular velocity command of the inspection UAV in step four is as follows:

[0037] For a given desired yaw angle command The relationships between the total thrust, desired roll angle, desired pitch angle, and desired angular velocity signal of the UAV are as follows:

[0038] (12)

[0039] in: The desired angular velocity gain constant, The total thrust command for the inspection drone at time t. To obtain the desired pitch angle command of the inspection UAV at time t, To obtain the expected roll angle command of the inspection drone at time t, To obtain the desired angular velocity command vector of the inspection UAV at time t, Let be the actual Euler angle vector of the inspection drone at time t. Let be the expected Euler angle vector of the inspection drone at time t. , These represent the desired roll angle command and desired pitch angle command of the inspection drone at time t, respectively. The desired yaw angle command given in advance.

[0040] The event-triggered preset performance trajectory tracking control method for UAVs used for power transmission line inspection proposed in this invention effectively satisfies the dynamic and steady-state performance constraints of UAV trajectory tracking by pre-setting performance error transformation and constructing trajectory tracking sliding mode variables. Combined with the event triggering mechanism, it significantly reduces the update frequency of position loop control commands, saves communication resources, and improves system operating efficiency. Based on the inherent speed loop and attitude loop control structure of the UAV, it achieves high-precision, steady-state controllable trajectory tracking of the inspection UAV along the power transmission line, effectively improving the safety, efficiency, robustness, and reliability of power transmission line insulator condition monitoring and inspection operations. Attached Figure Description

[0041] Figure 1 This is a flowchart of the event-triggered preset performance trajectory tracking control method for inspection drones for monitoring the condition of insulators of transmission lines, as described in this invention.

[0042] Figure 2 This is the overall control block diagram of the event-triggered preset performance trajectory tracking control method for inspection drones for monitoring the condition of transmission line insulators as described in this invention;

[0043] Figure 3 The trajectory tracking error curve of the inspection drone when using the method of the present invention;

[0044] Figure 4 A schematic diagram illustrating that the sliding mode variables of the inspection drone satisfy preset performance constraints when using the method of the present invention;

[0045] Figure 5 The attitude angle response curve of the inspection drone when using the method of the present invention;

[0046] Figure 6 This is the control input curve of the event-triggered trajectory tracking controller when using the method of the present invention;

[0047] Figure 7 The trigger interval variation curve of the event-triggered trajectory tracking controller when using the method of the present invention;

[0048] Figure 8 This is a schematic diagram of the three-dimensional trajectory of the inspection drone when the method of the present invention is used. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0050] Specific implementation method one: Refer to Figures 1 to 8 This embodiment specifically describes an event-triggered preset performance control method for monitoring the condition of insulators on power transmission lines using an inspection drone, comprising:

[0051] Step 1: Based on the dynamic characteristics of the UAV for monitoring the condition of transmission line insulators, establish a system dynamic model, and construct a simplified control model for the trajectory tracking of the UAV by means of variable substitution and model simplification.

[0052] First, based on the centroid motion and attitude dynamics characteristics of the UAV for monitoring the condition of transmission line insulators, a complete six-degree-of-freedom dynamic model of the UAV is established, as shown in formula (1).

[0053] The model contains position vectors velocity vector Euler angle vector Angular velocity vector and thrust vector Torque vector Total translational dynamics disturbance Total disturbance of rotational dynamics .

[0054] Velocity rotation matrix With attitude rotation matrix The expression is shown in formulas (2)-(3). Based on this, a simplified model for the trajectory tracking of the inspection drone, as shown in formula (4), can be obtained, where the control input vector is... The input vectors for trajectory tracking control of the UAV in the x, y, and z directions are the disturbance terms. This represents a combination of disturbances such as external wind field and modeling errors. This simplified model provides a clearly controllable system expression for the design of position loop controllers.

[0055] Step 2: Construct sliding mode variables for the trajectory tracking of the inspection drone, and use a preset performance function to perform a nonlinear transformation on the tracking error, transforming the original constrained error into an unconstrained preset performance error variable;

[0056] Based on the trajectory instructions of the inspection task, construct sliding mode variables in the x, y, and z directions. , , As shown in formula (5). To ensure that the UAV's tracking error always meets the dynamic and steady-state performance requirements, a preset performance constraint is applied to the original tracking error. The constraint interval is defined by the preset performance function. , , The given form is shown in formula (7). The preset performance function is given by the initial value. , , Final value , , and attenuation rate , , Construct and satisfy the initial constraints , , To further transform the constrained error into an unconstrained variable, a nonlinear error transformation is introduced, as shown in formula (6), which transforms the sliding mode variable... , , Mapped to preset performance error variables , , This transformation ensures that the error trajectory is strictly limited within the preset performance boundaries.

[0057] Step 3: Based on the preset performance error variables and the preset state response performance requirements of the UAV throughout the inspection mission, design a preset performance trajectory tracking controller for the simplified control model; calculate the position loop control command of the inspection UAV;

[0058] Based on preset performance error variables , , A preset performance trajectory tracking controller is designed, and its expression is shown in formula (9). The control law of the preset performance trajectory tracking controller consists of three parts: an error power term, an integral term, and an equivalent control term. The error power term is obtained by exponentiation of the absolute value of the preset performance error variable. , , and symbolic functions , , This enhances the controller's ability to converge quickly when far from the equilibrium point; the integral term , , Suppress steady-state error through integral form to improve disturbance rejection performance;

[0059] Equivalent control items: , , With desired acceleration , , With this as the core, feedforward compensation for the simplified model is achieved.

[0060] Step 4: Based on the current position loop control command and the position loop control command at the previous trigger time, determine whether the current position loop control command needs to be updated;

[0061] When the judgment result indicates that an update is needed, the total thrust command, desired attitude angle command, and desired angular velocity command of the inspection UAV are calculated and generated based on the updated position loop control command.

[0062] To reduce the update frequency of position control commands, an event triggering mechanism is introduced in this invention. The triggering criterion is shown in formula (11). By comparing the deviation between the current control action and the control action at the last triggering moment, it is determined whether a new control update is needed. When the triggering condition is met, the controller updates the desired x, y, and z direction control inputs. , , Subsequently, based on the given desired yaw angle... Formula (12) is used to convert the control inputs in the x, y, and z directions into total thrust commands. Expected roll angle Desired pitch angle Desired angular velocity The triggering strategy ensures that the system updates control commands only when needed, thereby effectively reducing communication and computational load.

[0063] Step 5: Input the total thrust, desired attitude, and desired angular velocity signals into the speed loop and attitude loop control modules of the inspection drone itself to drive the drone to perform preset performance event-triggered trajectory tracking control on the power transmission line inspection trajectory.

[0064] The trajectory tracking of an inspection drone is achieved by combining a velocity loop and an attitude loop: the total thrust and desired attitude angle commands output by the event-triggered controller are sent to the drone's inherent velocity and attitude loop control modules. The velocity loop is responsible for converting the desired acceleration into attitude requirements, and the attitude loop further drives the motor actuators to generate thrust and torque, thereby achieving three-dimensional trajectory tracking of the drone. Through the preset performance event-triggered control method of this invention, the drone can achieve high-precision, low-error, and interference-resistant trajectory tracking control along power transmission lines, while significantly reducing the number of triggers and significantly improving the utilization rate of communication resources.

[0065] This invention is applicable to quadcopter, multi-rotor, and other inspection drones with equivalent dynamic structures. The parameters of the preset performance function can be adjusted according to the trajectory accuracy requirements of the inspection task, wind field level, and the drone's power capability, making it particularly suitable for power transmission line insulator condition monitoring applications. Event trigger parameters. , , It can be optimized based on communication limitations, bandwidth control, and task stability.

[0066] To verify the effectiveness of the UAV trajectory tracking control method based on event-triggered preset performance constraints described in this invention, a three-dimensional UAV dynamics model was used for simulation testing. The simulation conditions and parameters are as follows: the UAV mass is set to M = 1.5 kg, the gravitational acceleration is g = 9.81 m / s², the sampling frequency is set to 20 Hz, and the moments of inertia in the x, y, and z directions are set to 0.01745 m / s², respectively. 0.01745 And 0.03175 The initial positions of the UAV's centroid in the x, y, and z directions are respectively set as follows: , , The sliding mode variables in the x, y, and z directions are executed according to formula (5), and the sliding mode variable parameters are set as follows: , , The preset performance controller is given by equation (9), and the preset performance error exponent gains in the x, y, and z directions are respectively set as follows: , , The preset performance error exponent gains in the x, y, and z directions are respectively set to , , The preset performance error integral term gains in the x, y, and z directions are respectively set to... , , The preset performance boundary function is given by equation (8), and the relevant parameters are set as follows: , , Final value , , and attenuation rate , , The event triggering mechanism is executed according to formula (11), and the event triggering parameters are set to... , , . , , These represent the desired positions of the UAV's center of mass along the x, y, and z coordinate axes, respectively.

[0067] Track tracking performance verification: The expected reference path for the transmission line circling inspection task is selected as... , , . Figure 3 The variation of the position tracking error of the inspection UAV over time is presented. As shown in the figure, all three-axis errors converge monotonically within the preset performance boundary limits, verifying the effectiveness of the error transformation and sliding mode surface constructed in this invention. Meanwhile, Figure 8 The image shows the three-dimensional flight trajectory of the UAV. It can be seen that the UAV using the method of this invention can accurately follow the actual spatial path without any deviation, demonstrating high tracking accuracy.

[0068] Sliding mode variable preset performance satisfaction: Figure 4 The curves showing the change of the sliding mode variable over time are presented. It can be seen that the sliding mode variable is always constrained within the preset performance boundary and exhibits rapid convergence characteristics, indicating that the designed preset performance error transformation function can effectively limit the transient and steady-state performance of the system.

[0069] Attitude angle and control input analysis: Figure 5 The attitude angle changes during UAV flight are presented. The attitude angle changes are smooth with no high-frequency jitter, indicating that the event-triggered mechanism mitigates the rapid attitude changes caused by high-frequency control updates. Figure 6 The control input calculated by the controller is displayed. It is evident that the control input exhibits minimal fluctuation, no chattering, and remains within the actuation range of the actuator, indicating that the control law has good implementability.

[0070] Event-triggered characteristic verification: Figure 7The figure shows the variation of the event trigger interval. Simulation results show that the event trigger intervals are all greater than a certain positive lower limit, and the Zeno phenomenon does not occur. In the figure, ET-PPSTC (Event-Triggered Prescribed Performance Super-Twisting Control) represents event-triggered preset performance super-twisting control. Compared with periodic control, event-triggered control significantly reduces the number of control updates, thereby reducing the computational and communication burden on the control system. Furthermore, simulation results show that the event trigger mechanism triggers 704 times throughout the entire flight, while the traditional 20 Hz time-triggered method requires approximately 4000 triggers within the same duration, reducing the number of control updates by approximately 82.4%, significantly saving communication and computational resources.

[0071] In summary, the simulation examples above demonstrate that the method of the present invention can achieve high-precision tracking of the reference trajectory for power transmission line inspection by UAVs while ensuring strict satisfaction of preset performance constraints. Under the action of the event triggering mechanism, the control update frequency is effectively reduced and the system operating efficiency is improved, thereby verifying the effectiveness and superiority of the technical solution of the present invention.

[0072] While the invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that different dependent claims and features described herein can be combined in ways different from those described in the original claims. It is also understood that features described in conjunction with individual embodiments can be used in other described embodiments.

Claims

1. A method for event-triggered preset performance control of an inspection drone for monitoring the condition of insulators in transmission lines, characterized in that, include: Step 1: Based on the dynamic characteristics of the UAV for monitoring the condition of transmission line insulators, establish a system dynamic model, and construct a simplified control model for the trajectory tracking of the UAV by means of variable substitution and model simplification. Step 2: Construct sliding mode variables for the trajectory tracking of the inspection drone. Design a preset performance function based on the preset state response performance requirements of the drone throughout the entire inspection mission. Use the preset performance function to perform a nonlinear transformation on the sliding mode variables, converting the constrained sliding mode variables into unconstrained preset performance error variables. Step 3: Based on the preset performance error variable, design a preset performance trajectory tracking controller for the simplified control model; Calculate the position loop control command of the inspection drone; Step 4: Based on the current position loop control command and the position loop control command at the previous trigger time, determine whether the current position loop control command needs to be updated; When the judgment result indicates that an update is needed, the total thrust command, desired attitude angle command, and desired angular velocity command of the inspection UAV are calculated and generated based on the updated position loop control command. Step 5: Input the total thrust, desired attitude, and desired angular velocity signals into the speed loop and attitude loop control modules of the inspection drone itself, and drive the drone to perform preset performance event-triggered trajectory tracking control on the power transmission line inspection trajectory.

2. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step one, the specific expression of the system dynamics model is as follows: (1) in: Let be the position vector of the UAV's centroid. , , These represent the positions of the UAV's center of mass along the x, y, and z coordinate axes, respectively. Let the velocity vector be the center of mass. , , These represent the velocities of the UAV's center of mass along the x, y, and z coordinate axes, respectively. Let them be Euler angle vectors. , , These represent the roll angle, pitch angle, and yaw angle of the UAV, respectively. It is the angular velocity vector. , , These represent the angular velocities of the UAV along the x, y, and z coordinate axes, respectively. For thrust vector, For the total thrust of the drone, The gravity vector M is the gravitational constant; M and These represent the mass and moment of inertia matrices of the UAV, respectively. Represents the torque vector. and These represent the total disturbances acting on the translational and rotational dynamics, respectively; where the velocity rotation matrix is... With attitude rotation matrix ; (2) (3) Among them, for any ,have , .

3. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step one, the simplified control model for tracking the trajectory of the inspection drone is as follows: (4) in: This is the input vector for UAV position tracking control. , , These represent the position tracking control inputs of the UAV in the x, y, and z coordinate axes, respectively. The total disturbance of the simplified control model for tracking the trajectory of the inspection drone. , , These represent the total disturbances of the simplified control model of the UAV in the x, y, and z coordinate axes, respectively.

4. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step two, the method for constructing the sliding mode variables for the trajectory tracking of the inspection drone is as follows: (5) in: , , These are represented by the sliding surface variables in the x, y, and z coordinate axes, respectively. , , Let x, y, and z represent the expected velocities of the UAV's center of mass along the x, y, and z coordinate axes, respectively. , , These represent the desired positions of the UAV's center of mass along the x, y, and z coordinate axes, respectively. , , These are the sliding mode variable parameters corresponding to the x, y, and z coordinate axes, respectively.

5. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step two, the formula for transforming the original constrained error into an unconstrained preset performance error variable is as follows: (6) in: , , These are the preset performance error variables in the x, y, and z coordinate axes, respectively. , , These are the preset performance functions for the x, y, and z coordinate axes, respectively. (7) in: , , These represent the initial value, final value, and convergence rate of the preset performance function along the x-axis, respectively. , , These represent the initial value, final value, and convergence rate of the preset performance function along the y-axis, respectively. , , These represent the initial value, final value, and convergence rate of the preset performance function along the z-axis, respectively. , , The settings must meet the following requirements. , , The preset trajectory tracking error constraint for power transmission line inspection drones is: (8)。 6. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step three, the preset performance trajectory tracking controller is: (9) in: , , These represent the gains of the preset performance error exponents in the x, y, and z coordinate axes, respectively. , , These represent the preset performance error index gains in the x, y, and z coordinate axes, respectively. , , These represent the gain of the preset performance error integral term in the x, y, and z coordinate axes, respectively. , , These are represented as equivalent control terms in the x, y, and z coordinate axes, respectively. , , These are represented as the desired acceleration signals in the x, y, and z coordinate axes, respectively. , , The preset performance error sign function in the x, y, and z coordinate axes satisfies: (10)。 7. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step four, the formula for determining whether the current position loop control command needs to be updated is: (11) in: The current trigger time, For the next triggering time, , , These represent the event trigger thresholds in the x, y, and z coordinate axes, respectively, where t represents the current time and or represents a logical OR.

8. The event-triggered preset performance control method for inspection drones for monitoring the condition of transmission line insulators according to claim 1, characterized in that, In step four, the method for calculating and generating the total thrust command, desired attitude angle command, and desired angular velocity command of the inspection UAV is as follows: For a given desired yaw angle command The relationships between the total thrust, desired roll angle, desired pitch angle, and desired angular velocity signal of the UAV are as follows: (12) in: The desired angular velocity gain constant, The total thrust command for the inspection drone at time t. To obtain the desired pitch angle command of the inspection UAV at time t, To obtain the expected roll angle command of the inspection drone at time t, To obtain the desired angular velocity command vector of the inspection UAV at time t, Let be the actual Euler angle vector of the inspection drone at time t. Let be the expected Euler angle vector of the inspection drone at time t. , These represent the desired roll angle command and desired pitch angle command of the inspection drone at time t, respectively. The desired yaw angle command given in advance.

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