Control method and system for quadrotor drone against random pulse deception attacks

Abstract

This disclosure provides a control method and system for a quadcopter drone against random pulse spoofing attacks, relating to the field of drone control technology. It constructs inner and outer loop system dynamic models; based on these models and erroneous data injected by random pulses, it establishes inner and outer loop error equations under random pulse spoofing attacks; it constructs continuous outer and inner loop controllers, designing controller gains according to the intensity and frequency of the random pulse spoofing attack. The outer loop controller performs continuous control of the quadcopter drone in a leader-follower mission and sends desired control values ​​to the inner loop controller. The inner loop controller performs actual control of the quadcopter drone based on the desired control values. When the error between the desired control value and the actual control value of the inner loop controller approaches zero, the control achieves the leader-follower mission for the quadcopter drone. This disclosure enables quadcopter drones to resist random pulse spoofing attacks when performing leader-follower missions.

Description

Technical Field

[0001] This disclosure relates to the field of unmanned aerial vehicle (UAV) control technology, specifically to a control method and system for quadcopter UAVs against random pulse deception attacks. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] In recent years, with the rapid development of unmanned systems technology, quadcopter drones have been widely used in many fields such as express delivery, power line inspection, and pesticide spraying due to their significant advantages such as light weight, compact structure, low wear and tear, and ease of operation. Technological upgrades have not only enabled them to perform complex and challenging tasks but have also driven their gradual replacement of some traditional jobs. However, individual drones, limited by their endurance and payload capacity, are unable to meet the demands of specific operational scenarios. Therefore, coordinated operation of multiple drones in formation has become a key solution. Through swarming, drone systems can overcome the limitations of individual drones and adapt to a wider range of application scenarios, demonstrating profound application value. Given these practical needs, achieving precise trajectory tracking control of a single quadcopter drone is crucial, based on an in-depth study of the characteristics of quadcopter drone system models; and, more importantly, achieving formation tracking control of multiple drones according to preset trajectories is even more significant.

[0004] As a type of cyber-physical system, quadcopter drones are vulnerable to malicious external attacks during formation control. Specifically, spoofing attacks are a typical example, where attackers send false information to trick sensors or users into believing incorrect data, thus causing them to take erroneous actions. Unlike traditional spoofing attacks, pulse spoofing attacks are discontinuous. This discrete spoofing attack can be viewed as a pulsed interference attack, meaning that erroneous data is injected into the controller at some point, causing pulsed, instantaneous jumps in system state data, leading the quadcopter drone to make incorrect flight attitudes or flight plans. Furthermore, the timing of pulsed spoofing is usually random; attackers can send pulsed spoofing signals at any time, making the attack more covert and potentially fatal.

[0005] However, existing technical solutions and theoretical frameworks have significant shortcomings in dealing with pulse spoofing attacks, specifically the following problems:

[0006] 1) Most research focuses on continuous deception attacks or denial-of-service (DoS) attacks, with very little research on effective control strategies for pulse deception attacks. This directly leads to a severe performance degradation and even mission failure for UAV formations subjected to pulse deception attacks under existing control frameworks.

[0007] 2) In the face of complex and highly dangerous pulse deception attack environments, existing solutions cannot suppress the negative impact of random pulse deception attacks, and UAVs cannot make timely attitude adjustments, resulting in insufficient robustness. Summary of the Invention

[0008] To address the aforementioned issues, this disclosure proposes a control method and system for quadcopter drones against random pulse deception attacks. It designs an inner-loop controller and an outer-loop controller, introduces inner-loop control gain and outer-loop control gain, and combines these with the frequency and intensity of the random deception attack to eventually stabilize the error system, enabling the quadcopter drone to complete the leader-follower mission and reducing the harm of random pulse deception attacks to leader-follower formation missions.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions:

[0010] Control methods for quadcopter drones against random pulse deception attacks include:

[0011] Based on the motion characteristics and motion data of the quadcopter UAV, the outer loop system dynamic model and the inner loop system dynamic model are constructed respectively.

[0012] Based on the outer loop system dynamics model and the position information of the leader and followers, an outer loop position error equation is constructed. Based on the outer loop position error equation and the erroneous data injected by random pulses, an outer loop error equation under random pulse deception attack is established.

[0013] Based on the inner loop system dynamics model and the position information of the leader and followers, an inner loop position error equation is constructed. Based on the inner loop position error equation and the erroneous data injected by random pulses, an inner loop error equation under random pulse deception attack is established.

[0014] A continuous outer-loop controller and an inner-loop controller are constructed based on the outer-loop error equation and the inner-loop error equation. The controller gain is designed according to the strength and frequency of the random pulse spoofing attack. The outer-loop controller performs continuous control on the quadrotor UAV leader-follower mission and sends the desired control quantity to the inner-loop controller. The inner-loop controller performs actual control on the quadrotor UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leader-follower mission of the quadrotor UAV.

[0015] According to some embodiments, the present disclosure adopts the following technical solutions:

[0016] A control system for a quadcopter drone designed to counter random pulse deception attacks, including:

[0017] The dynamics model building module is used to construct the outer loop system dynamics model and the inner loop system dynamics model respectively based on the motion characteristics and motion data of the quadcopter UAV;

[0018] The attack injection error construction module is used to construct the outer loop position error equation based on the outer loop system dynamics model and the position information of the leader and followers. Based on the outer loop position error equation and the error data injected by random pulses, the outer loop error equation under random pulse deception attack is established. Based on the inner loop system dynamics model and the position information of the leader and followers, the inner loop position error equation is constructed. Based on the inner loop position error equation and the error data injected by random pulses, the inner loop error equation under random pulse deception attack is established.

[0019] The inner and outer loop control modules are used to construct continuous outer and inner loop controllers based on the outer loop error equation and the inner loop error equation. The controller gain is designed according to the strength and frequency of the random pulse spoofing attack. The outer loop controller performs continuous control on the quadcopter UAV leader-follower mission and sends the desired control quantity to the inner loop controller. The inner loop controller performs actual control on the quadcopter UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner loop controller approaches 0, the control realizes the leader-follower mission of the quadcopter UAV.

[0020] According to some embodiments, the present disclosure adopts the following technical solutions:

[0021] A computer program product includes a computer program that, when executed by a processor, implements the control method for a quadcopter drone against random pulse deception attacks.

[0022] According to some embodiments, the present disclosure adopts the following technical solutions:

[0023] A non-transitory computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement the control method for a quadcopter drone against random pulse deception attacks.

[0024] According to some embodiments, the present disclosure adopts the following technical solutions:

[0025] An electronic device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the control method for a quadcopter drone against random pulse deception attacks.

[0026] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0027] This disclosure presents a control method for quadrotor drones against random pulse spoofing attacks. It applies continuous inner-loop control and outer-loop control to the leader-follower formation control of quadrotor drones. Traditional control methods cannot protect quadrotor drones from random pulse spoofing attacks during leader-follower missions. This disclosure introduces inner-loop and outer-loop control gains, designs inner-loop and outer-loop controllers, and combines the frequency and intensity of random spoofing attacks to eventually stabilize the error system. This reduces the harm of random pulse spoofing attacks to leader-follower formation missions, effectively adjusts the control gain, ensures the completion of leader-follower missions for quadrotor drones, and effectively improves the flexibility and adaptability of controller design, saving approximately 20% of network computing resources.

[0028] This disclosure discloses a control method for a quadcopter drone against random pulse deception attacks. It designs and establishes dynamic models of the inner and outer loop systems of the quadcopter drone, and calculates the desired velocity of the follower using the outer loop error. The desired position and velocity information of the follower from the outer loop is transmitted to the inner loop attitude control loop through the established relationship, allowing the inner loop attitude control loop to adjust in a timely manner. Furthermore, considering a random deception network attack environment, the method sets the pulse occurrence time, and the length of the pulse time interval satisfies the following parameters: By using the Poisson distribution to obtain pulse intensity parameters, a pulse time series and a random pulse deception attack model are constructed to improve the accuracy of the theoretical model of the quadcopter UAV, enabling the theoretical control accuracy to reach over 95%, greatly improving the flight accuracy of the quadcopter UAV, and simultaneously resisting the negative impact of random pulse deception attacks.

[0029] The control method for quadcopter drones against random pulse spoofing attacks disclosed herein achieves a breakthrough improvement in the anti-interference performance of quadcopter drones, optimizes the efficiency of formation information transmission, and reduces the overall cost of the control system, while ensuring the reliable completion of leader-follower formation tasks. It is also scalable and applicable not only to pulse spoofing attack environments but also to certain scenarios with data transmission packet loss and sensor failure. Attached Figure Description

[0030] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0031] Figure 1 This is a schematic diagram of the outer ring system control model of a quadcopter UAV according to an embodiment of the present disclosure;

[0032] Figure 2 This is a schematic diagram of the inner loop system control model of a quadcopter UAV according to an embodiment of this disclosure;

[0033] Figure 3 This is a schematic diagram showing the relationship between the inner and outer ring systems of a quadcopter drone according to an embodiment of the present disclosure;

[0034] Figure 4 This is a schematic diagram illustrating a quadcopter drone subjected to a random pulse deception attack according to an embodiment of this disclosure;

[0035] Figure 5 This is a position phase diagram in the leader-follower task of this disclosure embodiment, that is, the trajectory of the x-direction position and y-direction position over time. Detailed Implementation

[0036] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0037] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0038] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0039] Terminology Explanation

[0040] (1) Quadcopter UAV: ​​A type of unmanned aerial vehicle that can achieve vertical take-off and landing, hovering and multi-directional flight by adjusting the speed of its four rotors. It has the characteristics of compact structure and flexible operation, and is mainly used in aerial photography, disaster relief and other fields. As early as 1907, the Breguet-Richet N.1, jointly built by the Breguet brothers in France, was the first recorded and successfully test-flown quadcopter UAV in history.

[0041] (2) Pulse Spoofing Attack: A pulse spoofing attack is a discontinuous spoofing attack that modifies the data transmission process from the sensor to the controller at certain moments, causing the controller to obtain incorrect data and thus disrupting the original control function. Typical data tampering methods include multiplying the sensor data by a constant.

[0042] (3) Inner loop system: responsible for the attitude stabilization and control of the UAV, directly affecting the dynamic characteristics of the aircraft. By adjusting the speed of the four motors at a high speed, it can quickly respond to disturbances (such as wind disturbances) to the aircraft and maintain the desired pitch, roll and yaw angles.

[0043] (4) Outer loop system: responsible for the position and trajectory tracking control of the UAV. It generates the desired position and velocity commands according to the mission objectives, and calculates the target position and target attitude angle required to achieve the motion and transmits them to the inner loop.

[0044] (5) Leader-follower formation control: Given the position, speed and other information of the leader UAV, the follower UAV can be successfully tracked by the leader UAV by designing appropriate outer and inner loop controllers.

[0045] (6) Backstepping method: also known as the back-induction design method, it is a systematic controller synthesis method for uncertain systems. It is a regression design method that combines the selection of Lyapunov functions with the design of controllers. It starts from the lowest order differential equation of the system, introduces the concept of virtual control, designs virtual controls that meet the requirements step by step, and finally designs the real control law.

[0046] (7) Pulse strength: In random pulse spoofing attacks, sensor data is multiplied by a certain constant, which is usually called pulse strength.

[0047] Example 1

[0048] This disclosure discloses a control method for a quadcopter UAV against random pulse deception attacks. It deeply applies anti-pulse interference control technology to a formation control architecture, significantly improving the controller's flexibility and environmental adaptability. This ensures the reliable completion of leader-follower formation tasks while simultaneously achieving a breakthrough improvement in the quadcopter UAV's anti-jamming performance, optimizing formation information transmission efficiency, and reducing the overall cost of the control system. The method includes the following steps:

[0049] Step 1: Based on the motion characteristics and motion data of the quadcopter UAV, construct the outer loop system dynamic model and the inner loop system dynamic model respectively;

[0050] Step 2: Based on the outer loop system dynamics model and the position information of the leader and followers, construct the outer loop position error equation. Based on the outer loop position error equation and the erroneous data injected by random pulses, establish the outer loop error equation under random pulse deception attack.

[0051] Step 3: Based on the inner loop system dynamics model and the position information of the leader and followers, construct the inner loop position error equation. Based on the inner loop position error equation and the erroneous data injected by random pulses, establish the inner loop error equation under random pulse deception attack.

[0052] Step 4: Construct a continuous outer-loop controller and an inner-loop controller based on the outer-loop error equation and the inner-loop error equation. Design the controller gain according to the strength and frequency of the random pulse spoofing attack. The outer-loop controller performs continuous control on the quadcopter UAV leader-follower task and sends the desired control quantity to the inner-loop controller. The inner-loop controller performs actual control on the quadcopter UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leader-follower task of the quadcopter UAV.

[0053] As one embodiment, the control method for a quadcopter UAV against random pulse deception attacks disclosed herein designs an inner-loop controller and an outer-loop controller, introduces inner-loop control gain and outer-loop control gain, and combines the frequency and intensity of the random deception attack to eventually stabilize the error system, reducing the harm of random pulse deception attacks to leader-follower formation missions, enabling the quadcopter UAV to complete leader-follower formation missions even in the environment of random pulse deception attacks. The specific implementation process is as follows:

[0054] Step 1: Construct a system dynamics model based on the motion characteristics and motion data of the quadcopter UAV;

[0055] Specifically, step 101: Based on the motion environment of the quadcopter UAV, define a world coordinate system and obtain the position information, linear velocity information, and angular velocity information of the individual quadcopter UAV in the world coordinate system. In this embodiment, the position information is the position coordinates.

[0056] like Figure 1 As shown, taking the outer ring positional relationship of a quadcopter drone as an example, the specific process is as follows:

[0057] Based on reasonable assumptions about the physical environment of the quadcopter UAV, a world coordinate system is established. ,in Represents the origin of the world coordinate system. Representing the world coordinate system axis, Representing the world coordinate system axis, Representing the world coordinate system axis.

[0058] Step 102: Construct the dynamic model of the outer loop system.

[0059] Based on the fundamental laws of kinematics and dynamics, and the position and velocity information of the quadrotor UAV, a dynamic model of the outer ring system of the quadrotor UAV is established.

[0060] Based on the relationship between the linear velocity and angular velocity of a single UAV, the dynamic model of the outer-loop system of a single UAV can be obtained in the world coordinate system:

[0061]

[0062] in, This indicates the linear velocity of the drone. Indicates drones and The included angle of the axis, This indicates the angular velocity of the drone.

[0063] Step 103: Construct the dynamic model of the inner loop system.

[0064] Based on the motion environment of the quadrotor UAV, the position, yaw, roll, and pitch angles of the quadrotor UAV are acquired, and an inner-loop dynamic model of the quadrotor UAV is established, such as... Figure 2 As shown.

[0065]

[0066] Step 2: Obtain the error equation based on the outer loop system dynamics model and the position information of the drone leader and followers;

[0067] Specifically, step 201: Based on the coordinates of the leader drone and the follower drone in the world coordinate system and the speed information of the quadcopter drone, establish the error relationship between the two.

[0068] In this embodiment, the following will refer to the first... Take the error equation of a follower drone as an example. The x-axis error of the follower drone and the leader drone is represented by... The vertical coordinate error represents the error of the follower drone and the leader drone, from which the position error representation can be obtained:

[0069]

[0070] Step 202: Based on the position error, velocity error, and the dynamic model of the quadcopter UAV, the outer ring position error can be established.

[0071] The inertial measurement unit (IMU) and compass, among other sensors, within the drone's flight controller are used to perform real-time measurements to obtain the speed information for each drone. The difference between these measurements is then calculated to determine the speed error. Theoretically, the drone's speed can be obtained by differentiating its displacement with respect to time; the speed error can then be calculated by subtracting these values.

[0072] Based on the position error representation, both sides simultaneously adjust the time... Taking the derivative, so the first... The outer ring position error of the follower drone and the leader drone can be established as follows:

[0073]

[0074] Step 203: Based on the outer loop position error and the pulse injection error data, establish the outer loop error equation under the pulse attack environment.

[0075] Considering the pulse attack environment, assume the set of pulse occurrence times is as follows: And the length of the pulse time interval satisfies the parameter as follows Poisson distribution, pulse intensity parameter is Let this pulse time series be denoted as The model for a random pulse spoofing attack is as follows:

[0076]

[0077] The outer-loop error equation under a random pulse deception attack environment can be obtained as follows:

[0078]

[0079] in, This represents the error on the x-axis for leaders and followers. This represents the error on the vertical axis representing leaders and followers. Indicates the leader's linear velocity and The included angle of the axis and the linear velocity of the follower Error in the included angle of the shaft. Indicates the linear velocity of the follower. Indicates the linear velocity of the leader. Indicates the angular velocity of the follower. This represents the leader's angular velocity. This represents the distance parameter of the drone, where and This indicates the control output quantity of the controller.

[0080] Step 3: Based on the inner-loop system dynamics model and the position information of the leader and followers, obtain the error equation;

[0081] Specifically, step 301:

[0082] by Taking the axis as an example, based on the desired motion position coordinates and the current position information of the quadcopter UAV, a position error equation is established between the two:

[0083]

[0084]

[0085] Based on the position error equation and the erroneous data injected by random pulses, the inner-loop error equation under random pulse deception attack is established:

[0086]

[0087] Step 4: Design the outer loop controller for the quadcopter UAV. Based on the outer loop error equation and kinematic model, use a state feedback controller to perform feedback control on the quadcopter UAV. The specific steps are as follows:

[0088] Step 401: Design a state feedback controller to ensure the successful completion of the quadcopter UAV leader-follower formation mission.

[0089] First, based on the linear velocity information of the leader drone, the errors in the horizontal and vertical coordinates of the leader and follower drones, and the errors in linear velocity and axis angle, a controller of the following form is designed:

[0090]

[0091] in, It is the gain of the controller, which ensures the effectiveness of the outer loop control.

[0092] Step 402: Based on the strength and frequency of the random pulse spoofing attack, design the gain of the state feedback controller so that it can resist the random pulse spoofing attack.

[0093] According to the controller gain of the design Based on the information regarding the strength and frequency of the random pulse spoofing attack, the gain can be designed as follows:

[0094]

[0095] This controller not only suppresses the negative effects of random pulse spoofing attacks and exhibits multi-dimensional robustness—that is, it simultaneously resists complex combinations of pulse spoofing attacks related to intensity, frequency, mode, and target—but also the final designed state feedback controller gain… It also has significant advantages in multi-dimensional parameter fusion, constraint optimization, adaptive framework, and cooperative defense, which are mainly reflected in:

[0096] Performance guarantee: Achieve optimal or suboptimal robustness while meeting strict constraints on steady-state accuracy, instantaneous deviation, recovery time, and control energy.

[0097] Adaptive potential: The architecture design paves the way for future dynamic gain adjustment based on real-time attack signature assessment, enhancing the system's survivability in long-term confrontations.

[0098] Synergistic effect: It can be organically combined with other defense layers of the system to form a more powerful overall defense system.

[0099] Quantitatively verifiable: The design process is based on explicit parameters and constraints, and its effectiveness can be rigorously evaluated through theoretical analysis (such as robust stability proof and performance bound calculation) and simulation verification (testing whether performance indicators meet the standards under the set attack scenarios).

[0100] prove:

[0101] make Indicates the initial value of the outer loop error system. The solution, note , Let the Lyapunov function be:

[0102] ,

[0103] but The continuous dynamic derivative of the outer loop system with respect to time is:

[0104] Substituting the outer loop controller into the above equation, we get:

[0105]

[0106] Given the introduction of random impulsive deception attacks, it can be deduced that:

[0107]

[0108] Based on the properties of mathematical expectation, taking the mathematical expectation of both sides simultaneously, we can obtain:

[0109]

[0110] Using Taylor expansion, it can be simplified to:

[0111]

[0112] This means

[0113]

[0114] Where the constants satisfy Therefore, under random impulse spoofing attacks, the outer-loop error system is exponentially stable.

[0115] Step 5: Design the inner-loop controller for the quadcopter UAV. Based on the inner-loop error equation and kinematic model, a state feedback controller is also used to perform feedback control on the quadcopter UAV. The specific steps are as follows:

[0116] Specifically, step 501: Using the Lyapunov backstepping method, design a state feedback controller to make the error between the speed command issued by the quadcopter UAV and the desired speed command approach zero. Based on the continuous dynamic information, introduce a continuous controller with a designable controllable gain.

[0117] by Taking direction as an example, the specific process is as follows:

[0118] First, since the inner-loop dynamics of a quadcopter UAV is an underactuated, strongly coupled system, the system is simplified first. The axis can be simplified to:

[0119]

[0120]

[0121] in, express Desired displacement in the axial direction express The desired velocity along the axis is determined using the Lyapunov backstepping method, based on the desired attitude information and current attitude information provided by the quadrotor UAV. Design a controller in the following form:

[0122]

[0123] in It is the gain of the inner loop controller, which ensures the effectiveness of the inner loop control.

[0124] Secondly, based on the controller gain of the design Based on the information regarding the strength and frequency of the random pulse spoofing attack, the gain can be designed as follows:

[0125]

[0126] This inner-loop controller can effectively suppress the negative impact of random pulse spoofing attacks.

[0127]

[0128] Based on the strength and frequency of random pulse spoofing attacks, the control gain is designed to resist such attacks.

[0129]

[0130] prove:

[0131] make Indicates the initial value of the inner loop error system. The solution. Using the backstepping method, we take the Lyapunov function as:

[0132] ,

[0133] in, but The continuous dynamic derivative of the outer loop system with respect to time is:

[0134]

[0135] Substituting the inner loop controller into the above equation, we get:

[0136]

[0137] Similar to the outer loop system, we can finally obtain the following formula:

[0138]

[0139] This means

[0140]

[0141] Where the constants satisfy as well as Therefore, under random impulse spoofing attacks, the inner-loop error system is exponentially stable.

[0142] Step 502: Design the controller for the remaining attitude quantities.

[0143] and The direction controller is similar, so the remaining attitude controller can be obtained as follows:

[0144]

[0145] Furthermore, the connection between the inner-loop control system and the outer-loop control system is established. Using the aforementioned inner-loop and outer-loop controllers, it can be applied in a real-world random pulse deception attack environment, based on the dynamic equations of a quadcopter UAV:

[0146]

[0147] Therefore, the outer loop controller performs continuous control on the quadcopter UAV’s leader-follower task and sends the desired control quantity to the inner loop controller. The inner loop controller performs actual control on the quadcopter UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner loop controller approaches 0, the control realizes the leader-follower task of the quadcopter UAV.

[0148] That is, when the error between the ideal linear velocity of the outer loop and the actual linear velocity of the inner loop approaches 0, and the error between the ideal yaw rate of the outer loop and the actual yaw rate of the inner loop approaches 0, the outer loop control task can be executed smoothly. Therefore, the task of the inner loop control is to converge the error between the two to 0 as much as possible. Figure 3 As shown.

[0149] As an example, taking the leader drone drawing a circle as an example, assume that the leader drone starts from coordinates... Starting from point A, the follower drone departs from coordinates A. Starting from point A, the positional relationship of their trajectories and the error relationship between them are as follows: Figure 5 As shown in Table 1, the specific data is as follows.

[0150] Table 1. Leader-Follower Formation Status of Quadrotor UAVs under Controller

[0151]

[0152] Example 2

[0153] One embodiment of this disclosure provides a control system for a quadcopter drone against random pulse deception attacks, comprising:

[0154] The dynamics model building module is used to construct the outer loop system dynamics model and the inner loop system dynamics model respectively based on the motion characteristics and motion data of the quadcopter UAV;

[0155] The attack injection error construction module is used to construct the outer loop position error equation based on the outer loop system dynamics model and the position information of the leader and followers. Based on the outer loop position error equation and the error data injected by random pulses, the outer loop error equation under random pulse deception attack is established. Based on the inner loop system dynamics model and the position information of the leader and followers, the inner loop position error equation is constructed. Based on the inner loop position error equation and the error data injected by random pulses, the inner loop error equation under random pulse deception attack is established.

[0156] The inner and outer loop control modules are used to construct continuous outer and inner loop controllers based on the outer loop error equation and the inner loop error equation. The controller gain is designed according to the strength and frequency of the random pulse spoofing attack. The outer loop controller performs continuous control on the quadcopter UAV leader-follower mission and sends the desired control quantity to the inner loop controller. The inner loop controller performs actual control on the quadcopter UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner loop controller approaches 0, the control realizes the leader-follower mission of the quadcopter UAV.

[0157] Example 3

[0158] One embodiment of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the control method for a quadcopter drone against random pulse deception attacks.

[0159] Example 4

[0160] One embodiment of this disclosure provides a non-transitory computer-readable storage medium for storing computer instructions. When these computer instructions are executed by a processor, they implement the control method for a quadcopter drone against random pulse deception attacks.

[0161] Example 5

[0162] One embodiment of this disclosure provides an electronic device, including a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute the control method for a quadcopter drone against random pulse deception attacks.

[0163] Specifically, the electronic equipment comprises a heterogeneous architecture of a Raspberry Pi 4B (host computer) and a Pixhawk 6C mini flight controller (lower-level controller). The system deploys a ROS (Robot Operating System) environment as the core middleware, and through deep configuration, it can achieve the following:

[0164] Full-process task support: covering the entire lifecycle development of quadcopter drones, from virtual simulation Gazebo to physical deployment;

[0165] Anti-pulse spoofing attack formation control: Runs leader-follower formation programs natively at the ROS layer to accurately execute collaborative tasks in random pulse spoofing attack environments;

[0166] Cross-platform communication: Enables efficient command / data interaction between Raspberry Pi (decision layer) and Pixhawk (execution layer) through the MAVROS bridging module.

[0167] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0168] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0169] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A control method for a quadcopter drone against random pulse deception attacks, characterized in that, include: Based on the motion characteristics and motion data of the quadcopter UAV, the outer loop system dynamic model and the inner loop system dynamic model are constructed respectively. Based on the outer loop system dynamics model and the position information of the leader and followers, an outer loop position error equation is constructed. Based on the outer loop position error equation and the erroneous data injected by random pulses, an outer loop error equation under random pulse deception attack is established. Based on the inner loop system dynamics model and the position information of the leader and followers, an inner loop position error equation is constructed. Based on the inner loop position error equation and the erroneous data injected by random pulses, an inner loop error equation under random pulse deception attack is established. A continuous outer-loop controller and an inner-loop controller are constructed based on the outer-loop error equation and the inner-loop error equation. The controller gain is designed according to the strength and frequency of the random pulse spoofing attack. The outer-loop controller performs continuous control on the leader-follower task of the quadcopter UAV and sends the desired control quantity to the inner-loop controller. The inner-loop controller performs actual control on the quadcopter UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leader-follower task of the quadcopter UAV. Based on continuous dynamic information, a continuous outer loop controller and an inner loop controller with designable controllable gains are introduced. The control gains of the two controllers are designed according to the frequency and intensity of random pulse spoofing attacks. The connection between the inner loop system and the outer loop system is established. According to the dynamic equations of the quadcopter UAV, when the error between the ideal linear velocity of the outer loop system and the actual linear velocity of the inner loop system approaches 0, and the error between the ideal yaw rate of the outer loop system and the actual yaw rate of the inner loop system approaches 0, the control task of the outer loop system is successfully executed. Design an outer-loop controller for a quadcopter UAV. Based on the outer-loop error equation and kinematic model, employ a state feedback controller for feedback control of the quadcopter UAV. The specific steps are as follows: Based on the linear velocity information of the leader drone, the errors in the horizontal and vertical coordinates of the leader and follower drones, and the errors in linear velocity and axis angle, design a controller of the following form: in, It is the gain of the controller, which ensures the effectiveness of the outer loop control; This represents the error on the x-axis for leaders and followers. This represents the error on the vertical axis representing leaders and followers. Indicates the leader's linear velocity and The included angle of the axis and the linear velocity of the follower Error in the included angle of the shaft; Indicates the linear velocity of the follower. Indicates the linear velocity of the leader. Indicates the angular velocity of the follower. Indicates the leader's angular velocity; This represents the distance parameter of the drone, where and This indicates the control output quantity of the controller; Based on the strength and frequency of random pulse spoofing attacks, a state feedback controller gain is designed to resist such attacks. Considering the pulse attack environment, it is assumed that the set of pulse occurrence times is... S And the length of the pulse time interval satisfies the parameter as follows Poisson distribution, pulse intensity parameter is ; According to the controller gain of the design Based on the information regarding the strength and frequency of the random pulse spoofing attack, the gain can be designed as follows: Design an inner-loop controller for a quadcopter UAV. Based on the inner-loop error equation and kinematic model, a state feedback controller is also used to perform feedback control on the quadcopter UAV. The specific steps are as follows: Based on the desired attitude information and current attitude information released by the quadcopter UAV, the Lyapunov backstepping method is used. Design a controller in the following form: in It is the gain of the inner loop controller, which ensures the effectiveness of the inner loop control; Secondly, based on the controller gain of the design Based on the information regarding the strength and frequency of the random pulse spoofing attack, the gain can be designed as follows: 。 2. The control method for a quadcopter UAV against random pulse deception attacks as described in claim 1, characterized in that, Based on the motion environment of the quadrotor UAV, the position, velocity, and yaw rate information of the quadrotor UAV are obtained, and an outer-loop system dynamic model of a single quadrotor UAV is established. Based on the motion environment of the quadrotor UAV, the position, yaw rate, roll rate, and pitch rate information of the quadrotor UAV are obtained, and an inner-loop system dynamic model of a single quadrotor UAV is established.

3. The control method for a quadcopter UAV against random pulse deception attacks as described in claim 1, characterized in that, Based on the desired leader coordinates and the position information of the quadcopter drone, the error between the leader and the quadcopter drone is established. Based on the geometric relationship between the leader drone and the follower drone and the outer loop system dynamics model, the outer loop position error equation between the leader and the follower is established. Based on the outer loop position error equation and the erroneous data injected by random pulses, the error equation under random pulse deception attack is established.

4. The control method for a quadcopter UAV against random pulse deception attacks as described in claim 1, characterized in that, Based on the desired motion position coordinates and the current position information of the quadcopter UAV, an inner-loop position error equation is established between the two. Based on the inner-loop position error equation and the erroneous data injected by random pulses, an inner-loop error equation under random pulse deception attack is established.

5. The control method for a quadcopter UAV against random pulse deception attacks as described in claim 1, characterized in that, The process of obtaining erroneous data from random pulse injection includes: considering the pulse attack environment, setting the pulse occurrence time, and ensuring that the length of the pulse time interval satisfies the parameter... Using Poisson distribution, pulse intensity parameters are obtained, and pulse time series and random pulse deception attack models are constructed.

6. A control system for a quadcopter drone against random pulse deception attacks, characterized in that, include: The dynamics model building module is used to construct the outer loop system dynamics model and the inner loop system dynamics model respectively based on the motion characteristics and motion data of the quadcopter UAV; The attack injection error construction module is used to construct the outer loop position error equation based on the outer loop system dynamics model and the position information of the leader and followers. Based on the outer loop position error equation and the error data injected by random pulses, the outer loop error equation under random pulse deception attack is established. Based on the inner loop system dynamics model and the position information of the leader and followers, an inner loop position error equation is constructed. Based on the inner loop position error equation and the erroneous data injected by random pulses, an inner loop error equation under random pulse deception attack is established. The inner and outer loop control modules are used to construct continuous outer loop and inner loop controllers based on the outer loop error equation and the inner loop error equation. The controller gain is designed according to the strength and frequency of the random pulse spoofing attack. The outer loop controller performs continuous control on the quadcopter UAV leader-follower task and sends the desired control quantity to the inner loop controller. The inner loop controller performs actual control on the quadcopter UAV according to the desired control quantity. When the error between the desired control quantity and the actual control quantity of the inner loop controller approaches 0, the control realizes the leader-follower task of the quadcopter UAV. Based on continuous dynamic information, a continuous outer loop controller and an inner loop controller with designable controllable gains are introduced. The control gains of the two controllers are designed according to the frequency and intensity of random pulse spoofing attacks. The connection between the inner loop system and the outer loop system is established. According to the dynamic equations of the quadcopter UAV, when the error between the ideal linear velocity of the outer loop system and the actual linear velocity of the inner loop system approaches 0, and the error between the ideal yaw rate of the outer loop system and the actual yaw rate of the inner loop system approaches 0, the control task of the outer loop system is successfully executed. Design an outer-loop controller for a quadcopter UAV. Based on the outer-loop error equation and kinematic model, employ a state feedback controller for feedback control of the quadcopter UAV. The specific steps are as follows: Based on the linear velocity information of the leader drone, the errors in the horizontal and vertical coordinates of the leader and follower drones, and the errors in linear velocity and axis angle, design a controller of the following form: in, It is the gain of the controller, which ensures the effectiveness of the outer loop control; This represents the error on the x-axis for leaders and followers. This represents the error on the vertical axis representing leaders and followers. Indicates the leader's linear velocity and The included angle of the axis and the linear velocity of the follower and Error in the included angle of the shaft; Indicates the linear velocity of the follower. Indicates the linear velocity of the leader. Indicates the angular velocity of the follower. Indicates the leader's angular velocity; This represents the distance parameter of the drone, where and This indicates the control output quantity of the controller; Based on the strength and frequency of random pulse spoofing attacks, a state feedback controller gain is designed to resist such attacks. Considering the pulse attack environment, it is assumed that the set of pulse occurrence times is... S And the length of the pulse time interval satisfies the parameter as follows Poisson distribution, pulse intensity parameter is ; According to the controller gain of the design Based on the information regarding the strength and frequency of the random pulse spoofing attack, the gain can be designed as follows: Design an inner-loop controller for a quadcopter UAV. Based on the inner-loop error equation and kinematic model, a state feedback controller is also used to perform feedback control on the quadcopter UAV. The specific steps are as follows: Based on the desired attitude information and current attitude information released by the quadcopter UAV, the Lyapunov backstepping method is used. Design a controller in the following form: in It is the gain of the inner loop controller, which ensures the effectiveness of the inner loop control; Secondly, based on the controller gain of the design Based on the information regarding the strength and frequency of the random pulse spoofing attack, the gain can be designed as follows: 。 7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the control method for a quadcopter drone against random pulse deception attacks as described in any one of claims 1-5.

8. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium is used to store computer instructions, which, when executed by a processor, implement the control method for a quadcopter drone against random pulse deception attacks as described in any one of claims 1-5.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to perform the control method for a quadcopter drone against random pulse deception attacks as described in any one of claims 1-5.

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