Unmanned aerial vehicle trajectory tracking control method based on event triggering sliding mode control

Abstract

The invention discloses an event-triggered sliding mode control-based unmanned aerial vehicle trajectory tracking control method, and belongs to the technical field of unmanned aerial vehicle control. The method comprises the following steps: firstly, establishing an improved second-order control model for a four-rotor unmanned aerial vehicle; secondly, designing a trajectory tracking controller of the four-rotor unmanned aerial vehicle by adopting a sliding mode control method based on a fixed threshold event triggering mechanism and an improved exponential reaching law, proving the stability of the system by utilizing a Lyapunov stability theorem, ensuring that an event triggering interval has a lower bound greater than 0, and excluding a sesame behavior of the system; and finally, based on the unmanned aerial vehicle control experiment platform of the indoor optical positioning system, establishing a Simulink control module of the indoor small unmanned aerial vehicle, and realizing trajectory tracking control of the indoor small unmanned aerial vehicle. According to the invention, accurate tracking of the flight path of the indoor small-sized quad-rotor unmanned aerial vehicle can be realized, the communication frequency of the quad-rotor unmanned aerial vehicle is reduced, and resources are saved.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle control, and mainly relates to a trajectory tracking control method of a quad-rotor unmanned aerial vehicle based on event-triggered sliding mode control. Background Art

[0002] With the rapid development of UAV technology, quadcopters have been widely used in industry, agriculture, security and other fields due to their flexibility and high maneuverability. However, high-precision trajectory tracking control of UAVs in complex environments still faces many challenges, such as environmental interference, model uncertainty and high computational requirements for real-time control. Sliding mode control has become a research hotspot for UAV trajectory tracking control due to its robustness and strong suppression of system uncertainty and interference. Sliding mode control is a nonlinear control method known for its strong robustness to system model uncertainty and external interference. In the trajectory tracking control of quadcopters, sliding mode control gradually guides the system state to the equilibrium point by designing the sliding surface. Compared with traditional linear controllers, sliding mode control can adapt to the nonlinear characteristics and complex environmental interference in UAV dynamics. However, traditional sliding mode control may face the problem of chattering in practical applications, and it is necessary to improve the design to enhance the stability and control accuracy of the system.

[0003] Traditional sliding mode control methods usually rely on fixed-cycle triggers, resulting in a waste of computing resources or insufficient real-time performance. Event-triggered control effectively reduces the control update frequency and improves resource utilization efficiency through a trigger mechanism based on the system state. Event-triggered control is a more efficient real-time control strategy compared to fixed-cycle control. Its basic principle is to update the control signal only when the system state meets certain trigger conditions. This mechanism significantly reduces the computing load and communication resource consumption of the control system while still maintaining high control performance. In quadrotor drones, event-triggered control detects state errors in real time and dynamically adjusts the control update frequency, thereby reducing the chattering phenomenon in sliding mode control and improving the energy efficiency and real-time performance of the system.

[0004] The indoor optical positioning system is a technology that uses optical sensors to obtain high-precision position and speed information. It is widely used in indoor drone navigation and trajectory tracking scenarios. Through infrared reflective markers and optical positioning cameras, the system can capture the three-dimensional position and speed data of the drone in real time, providing high-precision state feedback for the control algorithm.

[0005] Combined with a high-precision indoor optical positioning system, a real indoor small UAV flight experiment can be designed to actually verify the proposed quadrotor UAV event-triggered sliding mode control trajectory tracking algorithm.

[0006] After searching, the application publication number is CN113867374B, an adaptive trajectory tracking controller for parameter prediction and disturbance of a quadrotor UAV based on sliding mode control and its design method, based on the nonlinear mechanical model of the quadrotor UAV, according to the attitude angle target and flight position target of the quadrotor UAV trajectory tracking, it uses the sliding mode variable structure control method to obtain the attitude control input function of the system, at the same time, predicts the system, and uses the predicted value instead of the actual value to give adaptive control compensation in advance; uses the sliding mode variable structure control method to obtain the position control input function of the system, at the same time, predicts the system, and uses the predicted value instead of the actual value to give adaptive control compensation in advance; according to the expected yaw angle and virtual control input, the expected values ​​of the roll angle and pitch angle of the quadrotor UAV are inversely solved as the reference input of the inner loop.

[0007] Different from the patent, firstly, the present invention relies on the indoor optical positioning system and the flight control board of the UAV, regards the UAV as a particle model and establishes an improved second-order control model. The controller directly generates speed control instructions to act on the UAV without considering the underlying dynamics of the UAV. At the same time, unlike the continuous triggering used in the patent, the present invention introduces an event triggering mechanism combined with sliding mode control. This mechanism significantly reduces the computing load and communication resource consumption of the control system while still maintaining a high control performance. Summary of the invention

[0008] The present invention aims to solve the above problems of the prior art. A UAV trajectory tracking control method based on event-triggered sliding mode control is proposed. The technical solution of the present invention is as follows:

[0009] A UAV trajectory tracking control method based on event-triggered sliding mode control comprises the following steps:

[0010] Step 1: The quadrotor drone is regarded as a point mass model, and the improved second-order control model is established by introducing the drone's maneuvering constant and simulating the speed command tracking delay;

[0011] Step 2: Using the sliding mode control method of event trigger mechanism and improved exponential reaching law, the hyperbolic tangent switching function is used instead of the sign function to design the trajectory tracking controller of the quadrotor drone. The stability of the system is proved by Lyapunov stability theorem, and the event trigger interval is guaranteed to have a lower bound greater than 0, thus eliminating the Zeno behavior of the system.

[0012] Step three, based on the indoor optical positioning system experimental platform, establish the Simulink control module of the indoor small UAV to realize the trajectory tracking control of the indoor small UAV.

[0013] Furthermore, the step 1 of establishing an improved second-order control model of the quadrotor drone specifically includes:

[0014] Based on the UAV autopilot system, the quadcopter is regarded as a particle model, and the improved second-order control model of the quadcopter is established as follows:

[0015]

[0016] Where p = [p x ,p y ,p z ] T is the position of the drone in three-dimensional space, represents the derivative of position, v = [v x ,v y ,v z ] T is the speed of the drone in three-dimensional space, v c =[v cx ,v cy ,v cz ] T is the speed control command of the UAV; l is the speed control gain of the UAV, which represents the maneuverability of the UAV and is determined by the UAV's autopilot system.

[0017] Furthermore, in step 2, a sliding mode control method based on an event trigger mechanism and an improved exponential reaching law is used to design a trajectory tracking controller for a quadrotor drone, specifically including:

[0018] Define position error e = p d -p,p d =[p dx ,p dy ,p dz ] T is the expected position signal; the derivative of the position error Design sliding mode function:

[0019]

[0020] Where s(t)=[s x ,s y ,s z ] T , c = diag[c x ,c y ,c z ], c x ,c y ,c z are all positive numbers; taking the derivative of the sliding mode function, we get:

[0021]

[0022] The hyperbolic tangent switching function is used to replace the sign function in the exponential reaching law to weaken the chattering phenomenon. The method is to let In the following form:

[0023]

[0024] Among them, ε is a small constant that determines how fast the inflection point of the hyperbolic tangent smooth function changes;

[0025] k=diag[k x ,k y ,k z ],k x ,k y ,k z >0, D=diag[D x ,D y ,D z ], D x ,D f ,D z >0, k, and D are all controller parameters.

[0026] Lian Li The two equations can be solved to obtain the speed control command of the quadcopter:

[0027]

[0028] Furthermore, a fixed threshold event trigger mechanism is introduced to save communication resources, as follows:

[0029] Change the speed control command to:

[0030]

[0031] Among them, t k is the time when the quadrotor drone’s most recent event was triggered, t k+1 The next event triggering moment of the quadrotor drone is defined as the state measurement error E(t)

[0032]

[0033] Set the trigger condition to:

[0034] t k+1 = inf{t>t k :∥E(t)∥>σ}

[0035] Among them, σ represents the event trigger threshold. The larger the trigger threshold set by the controller, the fewer the trigger times; ∥E(t)∥ represents the Euclidean norm of the vector.

[0036] Furthermore, in step 2, the stability of the system is proved using the Lyapunov stability theorem, as follows:

[0037] Define the Lyapunov function:

[0038]

[0039] Taking the derivative of V, we get:

[0040]

[0041] According to the theorem:

[0042]

[0043] Then we have:

[0044]

[0045] From the expression of E(t), we can get:

[0046]

[0047] And when:

[0048]

[0049] have:

[0050]

[0051] Just design the controller parameters:

[0052] D>σ+1+η

[0053] η>0, and the value of ε is designed so that:

[0054]

[0055] Established, then:

[0056] when hour,

[0057]

[0058] The sliding mode variable can eventually stabilize within a range, namely:

[0059]

[0060] In order to avoid the phenomenon that an event is triggered infinitely many times in a finite time, i.e., the Zeno phenomenon, it is necessary to prove that the time interval between two triggers has a lower bound greater than 0. Let the time interval T k =tk+1 -t k ,

[0061] Taking the derivative of the measurement error ∥E(t)∥, we have:

[0062]

[0063] Right now:

[0064]

[0065] The solution of the differential equation under the initial condition ∥E(t)∥=0 satisfies:

[0066]

[0067] Further we can get:

[0068]

[0069] This ensures that there is a positive minimum lower bound on the event triggering interval, ruling out Zeno behavior.

[0070] Furthermore, in step 3, based on the indoor optical positioning system experimental platform, the control software of the indoor small UAV is established to realize the trajectory tracking control of the indoor small UAV. The specific method is:

[0071] Using the UAV control experimental platform based on the indoor optical positioning system, we first create a rigid body model of an indoor small UAV, and obtain the real-time position and velocity information of the UAV through optical positioning solution; then, we build the designed trajectory tracking controller of the UAV in Matlab / Simulink, and take the position information p(t) and velocity information v(t) as the control input, and the velocity control instruction v c (t) is used as output, and the control instructions are sent to the drone for execution through the WIFI module. Finally, the algorithm is verified by actual flight of a small indoor drone on the experimental platform, proving that the drone’s trajectory tracking effect is good.

[0072] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the quadrotor unmanned aerial vehicle trajectory tracking control method based on triggered sliding mode control as described in any one of the items is implemented.

[0073] A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a quadrotor unmanned aerial vehicle trajectory tracking control method based on triggered sliding mode control as described in any one of the items.

[0074] A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the quadrotor unmanned aerial vehicle trajectory tracking control method based on triggered sliding mode control as described in any one of the items is implemented. The advantages and beneficial effects of the present invention are as follows:

[0075] (1) The present invention establishes an improved second-order control model for a quad-rotor UAV, which combines the advantages of the first-order and second-order models, and can ensure the accuracy of the UAV dynamics while facilitating the design of the controller.

[0076] (2) A fixed threshold event-triggered sliding mode controller is designed for the quadrotor UAV to track the desired trajectory. It can not only accurately track the desired flight trajectory, but also control the signal to be updated only at the event triggering moment, effectively reducing the communication frequency and saving energy.

[0077] (3) Unlike most simulation experiments, the effectiveness of the model and control algorithm is verified by designing real experiments, which is conducive to the wider deployment and application of sliding mode control algorithms and event triggering mechanisms in UAV trajectory tracking control. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 The invention provides a preferred embodiment of an unmanned aerial vehicle control experimental platform for an indoor optical positioning system for actual flight experiments.

[0079] Figure 2 It is a UAV trajectory tracking control module built in Matlab / Simulink.

[0080] Figure 3 It is the actual flight trajectory of the drone recorded by the optical motion capture system.

[0081] Figure 4 It is the result of trajectory tracking experiment in Matlab.

[0082] Figure 5 is the error variable of the UAV.

[0083] Figure 6 are sliding mode variables with three components.

[0084] Figure 7 It is the curve of speed control instruction.

[0085] Figure 8 The time interval for event triggering.

[0086] Fig. 9 This is a flow chart of the implementation method of trajectory tracking control of a quadrotor UAV based on event-triggered sliding mode control. DETAILED DESCRIPTION

[0087] The following will describe the technical solutions in the embodiments of the present invention in detail in conjunction with the accompanying drawings in the embodiments of the present invention. The described embodiments are only part of the embodiments of the present invention.

[0088] The technical solution of the present invention to solve the above technical problems is:

[0089] Combination Figure 1 The present invention discloses a UAV trajectory tracking control method based on event-triggered sliding mode control, and the specific implementation steps are as follows:

[0090] Step 1: Establish an improved second-order control model for the quadcopter drone. Based on the autopilot system of the drone, the quadcopter drone is regarded as a point mass model. There is no need to consider the attitude control problem of the quadcopter drone. The improved second-order control model of the quadcopter drone is established as follows:

[0091]

[0092] Where p = [p x ,p y ,p z ] T is the position of the UAV in three-dimensional space, v = [v x ,v y ,v z ] T is the speed of the drone in three-dimensional space, v c =[v cx ,v cy ,v cz ] T is the speed control command of the drone; l is the speed control gain of the drone, representing the maneuverability of the drone, and its value is determined by the autopilot system of the drone. In the present invention, the quad-rotor drone used has l≈3.

[0093] In the second step, an event-triggered mechanism and an improved exponential reaching law sliding mode control method are adopted, and the hyperbolic tangent switching function is used instead of the sign function to design the trajectory tracking controller of the quadrotor UAV. The stability of the system is proved by Lyapunov stability theorem, and it is ensured that the event trigger interval has a lower bound greater than 0, eliminating the Zeno behavior of the system.

[0094] Design a trajectory tracking controller for a quadrotor drone, including:

[0095] Define position error e = p d -p,p d =[p dx ,p dy ,p dz ] T is the expected position signal; the derivative of the position error Design sliding mode function:

[0096]

[0097] Where s(t)=[s x ,s y ,s z ] T , c = diag[c x ,c y ,c z ], c x ,c y ,c z are all positive numbers; taking the derivative of the sliding mode function, we get:

[0098]

[0099] The hyperbolic tangent switching function is used to replace the sign function in the exponential reaching law to weaken the chattering phenomenon. The method is to let In the following form:

[0100]

[0101] Among them, ε is a small constant that determines how fast the inflection point of the hyperbolic tangent smooth function changes.

[0102] k=diag[k x ,k y ,k z ],k x ,k y ,k z >0, D=diag[D x ,D y ,D z ], D x ,D y ,D z >0, k, and D are all controller parameters.

[0103] Lian Li The two equations can be solved to obtain the speed control command of the quadcopter:

[0104]

[0105] A fixed threshold event trigger mechanism is introduced to save communication resources, as follows:

[0106] Rewrite the speed control command as:

[0107]

[0108] Among them, t kis the time when the quadrotor drone’s most recent event was triggered, t k+1 is the next event triggering time of the quadcopter. The state measurement error is defined as E(t)

[0109]

[0110] The trigger conditions are:

[0111] t k+1 = inf{t>t k :∥E(t)∥>σ}

[0112] Among them, σ represents the event trigger threshold. The larger the trigger threshold set by the controller, the fewer the trigger times; ∥E(t)∥ represents the Euclidean norm of the vector.

[0113] Define the Lyapunov function:

[0114]

[0115] Taking the derivative of V, we get:

[0116]

[0117] According to the theorem:

[0118]

[0119] Then we have:

[0120]

[0121] From the expression of E(t), we can get:

[0122]

[0123] And when:

[0124]

[0125] have:

[0126]

[0127] Just design the controller parameters:

[0128] D>σ+1+η

[0129] And design the value of ε so that:

[0130]

[0131] Established, then:

[0132] when hour,

[0133]

[0134] The sliding mode variable can eventually stabilize within a range, namely:

[0135]

[0136] In order to avoid the phenomenon that an event is triggered infinitely many times in a finite time, i.e., the Zeno phenomenon, it is necessary to prove that the time interval between two triggers has a lower bound greater than 0. Let the time interval T k =t k+1 -t k ,

[0137] Taking the derivative of the measurement error ∥E(t)∥, we have:

[0138]

[0139] Right now:

[0140]

[0141] The solution of the differential equation under the initial condition ∥E(t)∥=0 satisfies:

[0142]

[0143] Further we can get:

[0144]

[0145] This ensures that there is a positive minimum lower bound on the event triggering interval, ruling out Zeno behavior.

[0146] Step 3: Based on the indoor optical positioning system experimental platform, establish the Simulink control module of the indoor small UAV to realize the trajectory tracking control of the indoor small UAV. The specific method is:

[0147] First, if Figure 1 ,Using the UAV control experimental platform based on the indoor optical positioning system, we first create a rigid body model of a small indoor UAV, and obtain the real-time position and speed information of the UAV through optical positioning solution;

[0148] Then, if Figure 2 , the trajectory tracking controller of the UAV is designed in Matlab / Simulink, and the position information p(t) and speed information v(t) are used as control inputs. The speed control command v c (t) As output, the control instructions are sent to the drone for execution through the WIFI module;

[0149] Finally, the algorithm was verified by actual flight of a small indoor UAV on the experimental platform, and the UAV was made to fly with the expected trajectory p d (t) Flight

[0150] p d (t)=[1.3cos(0.15t),1.3sin(0.15t),1] T

[0151] The sampling time is 1 / 30 second.

[0152] Figure 3 It is the actual flight trajectory recorded by the optical motion capture system during the actual flight; Figure 4 This is the drawing effect of the flight trajectory in Matlab; Figure 5 The error curves of the three components show that the position error quickly converges to a value near 0. Figure 6 is a sliding mode variable with three components. When tracking the expected trajectory (after the 10th second), the sliding mode variable can be stabilized in a small range. Figure 7 is the speed control command v c From the curve of (t), we can see that only when the trigger condition is met, the speed control command is updated and sent to the drone for execution. If the trigger condition is not met, the speed control command will remain unchanged until the next trigger moment; Figure 8 The time interval for event triggering.

[0153] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions.

[0154] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0155] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0156] The above embodiments should be understood to be only used to illustrate the present invention and not to limit the protection scope of the present invention. After reading the contents of the present invention, technicians can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A UAV trajectory tracking control method based on event-triggered sliding mode control, characterized in that: The following steps are involved: Step 1: The quadrotor drone is regarded as a point mass model, and the improved second-order control model is established by introducing the drone's maneuvering constant and simulating the speed command tracking delay; Step 2: Using the sliding mode control method of event trigger mechanism and improved exponential reaching law, the hyperbolic tangent switching function is used instead of the sign function to design the trajectory tracking controller of the quadrotor drone. The stability of the system is proved by Lyapunov stability theorem, and the event trigger interval is guaranteed to have a lower bound greater than 0, thus eliminating the Zeno behavior of the system. Step three, based on the indoor optical positioning system experimental platform, establish the Simulink control module of the indoor small UAV to realize the trajectory tracking control of the indoor small UAV.

2. The UAV trajectory tracking control method based on event-triggered sliding mode control according to claim 1 is characterized in that: The improved second-order control model of the quadrotor drone established in step 1 specifically includes: Based on the UAV autopilot system, the quadcopter is regarded as a particle model, and the improved second-order control model of the quadcopter is established as follows: Where p = [p x ,p y ,p z ] T is the position of the drone in three-dimensional space, is the derivative of the drone position, v = [v x ,v y ,v z ] T is the speed of the drone in three-dimensional space, v c =[v cx ,v cy ,v cz ] T is the speed control command of the UAV; l is the speed control gain of the UAV, also known as the maneuvering constant, which represents the maneuverability of the UAV and is determined by the UAV's autopilot system.

3. The UAV trajectory tracking control method based on event-triggered sliding mode control according to claim 2 is characterized in that: In step 2, a sliding mode control method based on an event trigger mechanism and an improved exponential reaching law is used to design a trajectory tracking controller for a quadrotor drone, specifically including: Define position error e = p d -p,p d =[p dx ,p dy ,p dz ] T is the expected position signal; the derivative of the position error Design sliding mode function: Where s(t)=[s x ,s y ,s z ] T , c = diag[c x ,c y ,c z ], c x ,c y ,c z are all positive numbers; taking the derivative of the sliding mode function, we get: The hyperbolic tangent switching function is used to replace the sign function in the exponential reaching law to weaken the chattering phenomenon. The method is to let In the following form: Among them, ε is a small constant that determines how fast the inflection point of the hyperbolic tangent smooth function changes; k=diag[k x ,k y ,k z ],k x ,k y ,k z >0, D=diag[D x ,D y ,D z ], D x ,D y ,D z >0, k, and D are all controller parameters. Lian Li The two equations can be solved to obtain the speed control command of the quadcopter:

4. The quadrotor UAV trajectory tracking control method based on triggered sliding mode control according to claim 3 is characterized in that: A fixed threshold event trigger mechanism is introduced to save communication resources, as follows: Change the speed control command to: Among them, t k is the time when the quadrotor drone’s most recent event was triggered, t k+1 The next event triggering moment of the quadrotor drone is defined as the state measurement error E(t) Set the trigger condition to: t k+1 =inf{t>t k :∥E(t)∥>σ} Among them, σ represents the event trigger threshold. The larger the trigger threshold set by the controller, the fewer the trigger times; ∥E(t)∥ represents the Euclidean norm of the vector.

5. The UAV trajectory tracking control method based on event-triggered sliding mode control according to claim 4 is characterized in that: In step 2, the stability of the system is proved by using the Lyapunov stability theorem, as follows: Define the Lyapunov function: Taking the derivative of V, we get: According to the theorem: Then we have: From the expression of E(t), we can get: And when: have: Just design the controller parameters: D>σ+1+η η>0, and the value of ε is designed so that: Established, then: when hour, The sliding mode variable can eventually stabilize within a range, namely: In order to avoid the phenomenon that an event is triggered infinitely many times in a finite time, i.e., the Zeno phenomenon, it is necessary to prove that the time interval between two triggers has a lower bound greater than 0. Let the time interval T k =t k+1 -t k , Taking the derivative of the measurement error ∥E(t)∥, we have: Right now: The solution of the differential equation under the initial condition ∥E(t)∥=0 satisfies: Further we can get: This ensures that there is a positive minimum lower bound on the event triggering interval, ruling out Zeno behavior.

6. The UAV trajectory tracking control method based on event-triggered sliding mode control according to claim 5 is characterized in that: In step 3, based on the indoor optical positioning system experimental platform, a Simulink control module of an indoor small UAV is established to realize the trajectory tracking control of the indoor small UAV. The specific method is: Using the UAV control experimental platform based on the indoor optical positioning system, we first create a rigid body model of an indoor small UAV, and obtain the real-time position and velocity information of the UAV through optical positioning solution; then, we build the designed trajectory tracking controller of the UAV in Matlab / Simulink, and take the position information p(t) and velocity information v(t) as the control input, and the velocity control instruction v c (t) is used as output, and the control instructions are sent to the drone for execution through the WIFI module. Finally, the algorithm is verified by actual flight of a small indoor drone on the experimental platform, proving that the drone’s trajectory tracking effect is good.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the quadrotor unmanned aerial vehicle trajectory tracking control method based on event-triggered sliding mode control as described in any one of claims 1 to 6 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the UAV trajectory tracking control method based on event-triggered sliding mode control as described in any one of claims 1 to 6 is implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the four-UAV trajectory tracking control method based on event-triggered sliding mode control as described in any one of claims 1 to 6 is implemented.

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