Method and system for controlling quad-rotor unmanned aerial vehicle aiming at random pulse spoofing attack

Abstract

The invention provides a control method and system for a quad-rotor unmanned aerial vehicle for random pulse spoofing attacks, and relates to the technical field of unmanned aerial vehicle control. Establishing inner and outer ring error equations under the random pulse spoofing attack based on the inner and outer ring system dynamics models and random pulse injection error data; a continuous outer ring controller and a continuous inner ring controller are constructed, controller gains are designed according to the intensity and frequency of random pulse spoofing attacks, the outer ring controller performs continuous control on a leading-following task of the quad-rotor unmanned aerial vehicle, and an expected control quantity is issued to the inner ring controller; and the inner ring controller performs actual control on the quadrotor unmanned aerial vehicle according to the expected control quantity, and when the error between the expected control quantity and the actual control quantity of the inner ring controller tends to 0, the leader-following task of the quadrotor unmanned aerial vehicle is controlled to be realized. According to the invention, the quad-rotor unmanned aerial vehicle can resist the random pulse spoofing attack when carrying out the leader-following task.

Description

Technical Field

[0001] The present disclosure relates to the field of drone control technology, and in particular to a control method and system for a quadrotor drone against random pulse deception attacks. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] In recent years, with the rapid development of unmanned systems technology, quadcopter drones (UAVs), with their significant advantages such as light weight, compact structure, low loss, and easy control, have been widely used in a variety of fields, including express delivery, power inspection, and pesticide spraying. Technological upgrades have not only enabled them to perform highly complex and challenging tasks, but have also led to their gradual replacement for some traditional jobs. However, due to limitations in endurance and payload capacity, individual UAVs are unable to meet the demands of specific operational scenarios. Therefore, coordinated formation operations of multiple UAVs have become a key solution. Through formation swarming, UAV systems can transcend the limitations of individual units and adapt to a wider range of application scenarios, with far-reaching application value. Given these practical needs, achieving precise trajectory tracking control for individual UAVs, based on in-depth research into the characteristics of quadcopter system models, is crucial. Furthermore, achieving formation tracking control of multiple UAVs along pre-defined trajectories is even more crucial.

[0004] As a type of cyber-physical system, quadcopters are vulnerable to malicious external attacks during formation control. Specifically, a deception attack is a typical external attack in which the attacker sends false information to trick sensors or users into believing erroneous data, thereby prompting them to take incorrect actions. Unlike traditional deception attacks, pulse deception attacks are discontinuous. This discrete deception attack can be viewed as a pulsed interference attack, meaning that erroneous data is injected into the controller at a certain moment, resulting in a pulsed instantaneous jump in the system state data, causing the quadcopter to make incorrect flight gestures or flight plans. In addition, the timing of pulsed deception is usually random, and the attacker can send pulsed deception signals at any time, making the attack more covert and lethal.

[0005] However, existing technical solutions and theoretical systems have obvious shortcomings in dealing with pulse spoofing attacks, specifically the following problems: 1) Most research focuses on continuous spoofing attacks or denial-of-service (DoS) attacks, while little research is conducted on effective control strategies for pulse spoofing attacks. This directly leads to severe performance degradation and even mission failure in existing control frameworks when UAV formations are attacked by pulse spoofing.

[0006] 2) Faced with complex and highly harmful pulse deception attack environments, existing solutions are unable to suppress the negative impact of random pulse deception attacks. UAVs are unable to make timely attitude adjustments and lack robustness. Summary of the Invention

[0007] To solve the above problems, the present disclosure proposes a control method and system for a quadrotor drone against random pulse deception attacks. An inner-loop controller and an outer-loop controller are designed respectively, and inner-loop control gains and outer-loop control gains are introduced. Combined with the frequency and intensity of random deception attacks, the error system is ultimately stabilized, allowing the quadrotor drone to complete the leader-follower mission and reducing the harm of random pulse deception attacks to the leader-follower formation mission.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions: The control method of the quadrotor drone against random pulse deception attack includes: According to the motion characteristics and motion data of the quadrotor drone, the outer loop system dynamics model and the inner loop system dynamics model are constructed respectively; Based on the outer loop system dynamics model, the position information of the leader and follower, the outer loop position error equation is constructed. According to 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 follower, the inner loop position error equation is constructed. According to 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. Based on the outer-loop error equation and the inner-loop error equation, a continuous outer-loop controller and inner-loop controller are constructed, and the controller gain is designed according to the intensity and frequency of the random pulse deception attack. The outer-loop controller performs continuous control on the leading-following task of the quadrotor UAV and sends the expected control quantity to the inner-loop controller. The inner-loop controller actually controls the quadrotor UAV according to the expected control quantity. When the error between the expected control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leading-following task of the quadrotor UAV.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions: The control system of the quadrotor drone against random pulse deception attacks includes: The dynamic model construction module is used to construct the outer loop system dynamic model and the inner loop system dynamic model according to the motion characteristics and motion data of the quadrotor drone; An attack injection error construction module is used to construct an outer loop position error equation based on the outer loop system dynamics model and the position information of the leader and follower. The outer loop error equation under a random pulse deception attack is established based on the outer loop position error equation and the error data injected by the random pulse. The inner loop position error equation is constructed based on the inner loop system dynamics model and the position information of the leader and follower. The inner loop error equation under a random pulse deception attack is established based on the inner loop position error equation and the error data injected by the random pulse. The inner and outer loop control modules are used to construct a continuous outer loop controller and an inner loop controller based on the outer loop error equation and the inner loop error equation, and design the controller gain according to the intensity and frequency of the random pulse deception attack. The outer loop controller continuously controls the leading-following task of the quadrotor UAV and sends the expected control amount to the inner loop controller. The inner loop controller actually controls the quadrotor UAV according to the expected control amount. When the error between the expected control amount and the actual control amount of the inner loop controller approaches 0, the control realizes the leading-following task of the quadrotor UAV.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions: A computer program product includes a computer program, which, when executed by a processor, implements the control method for a quadrotor drone against random pulse deception attacks.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions: A non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the control method of the quadrotor drone against random pulse deception attacks is implemented.

[0012] According to some embodiments, the present disclosure adopts the following technical solutions: An electronic device includes: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. 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 of a quadrotor drone against random pulse deception attacks.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The control method of the quadrotor drone against random pulse deception attacks disclosed in the present invention applies continuous inner-loop control and outer-loop control to the leader-follower formation control of the quadrotor drone. Traditional control means cannot enable the quadrotor drone to resist random pulse deception attacks when performing leader-follow tasks. The present invention introduces inner-loop control gain and outer-loop control gain, designs inner-loop controller and outer-loop controller, and combines the frequency and intensity of random deception attacks to ultimately stabilize the error system, reduce the harm of random pulse deception attacks to the leader-follower formation task, effectively adjust the control gain, ensure the completion of the leader-follower task of the quadrotor drone, and effectively improve the flexibility and adaptability of the controller design, saving about 20% of network computing resources.

[0014] The control method of the quadcopter drone against random pulse deception attack disclosed in the present invention designs the dynamic models of the inner and outer loop systems of the quadcopter drone and establishes a connection. The desired speed of the follower is calculated through the outer loop error, and the position and speed information of the follower expected by the outer loop is transmitted to the inner loop attitude control loop through the established relationship, so that the inner loop attitude can be adjusted in time. In addition, for a random deception network attack, the pulse attack environment is considered, the pulse generation time is set, and the length of the pulse time interval satisfies the parameter Poisson distribution is used to obtain pulse intensity parameters, construct pulse time series and random pulse deception attack models, improve the theoretical model accuracy of quadrotor drones, and make the theoretical control accuracy reach more than 95%, greatly improving the flight accuracy of quadrotor drones while resisting the negative impact of random pulse deception attacks.

[0015] The disclosed control method for a quadrotor drone against random pulse deception attacks, while ensuring the reliable completion of the leader-follower formation mission, simultaneously achieves a breakthrough improvement in the quadrotor drone's anti-interference performance, optimizes the formation information transmission efficiency, and reduces the overall cost of the control system. It is also scalable and is not only suitable for pulse deception attack environments, but also for certain scenarios such as data transmission packet loss and sensor failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which constitute a part of the present disclosure, are used to provide a further understanding of the present disclosure. The exemplary embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation to the present disclosure.

[0017] Figure 1 Schematic diagram of the outer loop system control model of the quadrotor drone according to an embodiment of the present disclosure; Figure 2 Schematic diagram of the inner loop system control model of the quadrotor drone according to an embodiment of the present disclosure; Figure 3Schematic diagram of the relationship between the inner and outer ring systems of the quadrotor drone according to an embodiment of the present disclosure; Figure 4 Schematic diagram of a quadrotor drone subjected to a random pulse spoofing attack according to an embodiment of the present disclosure; Figure 5 : is a position phase diagram in the leader-follower task of an embodiment of the present disclosure, that is, the trajectory of the x-direction position and the y-direction position over time. DETAILED DESCRIPTION

[0018] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0019] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present disclosure belongs.

[0020] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0021] Explanation of terms (1) Quadcopter: An 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 control. It is mainly used in aerial photography, disaster relief, and other fields. As early as 1907, the Breguet-Richet N.1, jointly produced by the Breguet brothers in France, was the first recorded and successfully tested quadcopter in history.

[0022] (2) Pulse spoofing attack: A pulse spoofing attack is a discontinuous spoofing attack that tampered with the data transmission process from the sensor to the controller at certain moments, causing the controller to obtain incorrect data and thus destroying the original control function. Typical data tampering methods include multiplying the sensor data by a certain constant.

[0023] (3) Inner loop system: This is responsible for the attitude stability and control of the drone, and directly affects the dynamic characteristics of the aircraft. By adjusting the speed of the four motors at a high rate, it quickly responds to disturbances (such as wind disturbance) on the aircraft and maintains the desired pitch, roll, and yaw angles.

[0024] (4) Outer loop system: responsible for the position and trajectory tracking control of the UAV. It generates the desired position and velocity instructions based on the mission objectives, and calculates the target position and target attitude angle required to achieve the movement and transmits them to the inner loop.

[0025] (5) Leader-follower formation control: When the position, speed and other information of the leader UAV are known, the follower UAV is made to successfully track the leader UAV in terms of position by designing appropriate outer-loop controller and inner-loop controller.

[0026] (6) Backstepping: Also known as the backstepping 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 controller design. It starts from the lowest-order differential equation of the system, introduces the concept of virtual control, and gradually designs virtual controls that meet the requirements, ultimately designing the true control law.

[0027] (7) Pulse strength: In a random pulse spoofing attack, the sensor data is multiplied by a constant, which is usually called the pulse strength.

[0028] Example 1 This disclosure describes a control method for quadrotor drones that are resistant to random pulse deception attacks. This method deeply applies pulse interference-resistant control technology to the formation control architecture, significantly improving the controller's flexibility and environmental adaptability. While ensuring the reliable completion of leader-follower formation missions, it also achieves a breakthrough improvement in the quadrotor's anti-interference performance, optimizes formation information transmission efficiency, and reduces the overall cost of the control system. The method includes the following steps: Step 1: Based on the motion characteristics and motion data of the quadrotor drone, construct the outer loop system dynamics model and the inner loop system dynamics model respectively; Step 2: Based on the outer loop system dynamics model and the position information of the leader and follower, the outer loop position error equation is constructed. Based on the outer loop position error equation and the erroneous data injected by random pulses, the outer loop error equation under the random pulse spoofing attack is established. Step 3: Based on the inner loop system dynamics model and the position information of the leader and follower, the inner loop position error equation is constructed. Based on the inner loop position error equation and the erroneous data injected by random pulses, the inner loop error equation under the random pulse spoofing attack is established. Step 4: Based on the outer-loop error equation and the inner-loop error equation, a continuous outer-loop controller and an inner-loop controller are constructed, and the controller gain is designed according to the intensity and frequency of the random pulse deception attack. The outer-loop controller continuously controls the leading-following task of the quadrotor drone and sends the expected control quantity to the inner-loop controller. The inner-loop controller actually controls the quadrotor drone based on the expected control quantity. When the error between the expected control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leading-following task of the quadrotor drone.

[0029] As an embodiment, the disclosed control method for a quadrotor drone against random pulse deception attacks designs an inner-loop controller and an outer-loop controller, introduces inner-loop control gains and outer-loop control gains, and combines the frequency and intensity of random deception attacks to ultimately stabilize the error system, reducing the harm of random pulse deception attacks to the leader-follower formation mission, allowing the quadrotor drone to complete the leader-follower formation mission under random pulse deception attacks. The specific implementation process is as follows: Step 1: Construct a system dynamics model based on the motion characteristics and motion data of the quadrotor drone; Specifically, step 101: define a world coordinate system based on the motion environment of the quadrotor drone, and obtain the position information, linear velocity information, and angular velocity information of the single quadrotor drone in the world coordinate system. In this embodiment, the position information is the position coordinates.

[0030] like Figure 1 As shown, taking the position relationship of the outer ring of a quadcopter as an example, the specific process is as follows: Establish a world coordinate system based on reasonable assumptions about the physical environment of the quadcopter ,in represents the origin of the world coordinate system, Represents the world coordinate system axis, Represents the world coordinate system axis, Represents the world coordinate system axis.

[0031] Step 102: Construct an outer loop system dynamics model.

[0032] According to the basic laws of kinematics and dynamics, the position information and velocity information of the quadrotor UAV, the outer loop system dynamics model of the quadrotor UAV is established.

[0033] According to the relationship between the linear velocity and angular velocity of a single UAV, the outer loop system dynamics model of the single UAV can be obtained in the world coordinate system:

[0034] in, represents the linear velocity of the drone, Indicates that drones and The angle of the axis, Indicates the angular velocity of the drone.

[0035] Step 103: Construct an inner loop system dynamics model.

[0036] According to the motion environment of the quadrotor drone, the position information, yaw angle information, roll angle information, and pitch angle information of the quadrotor drone are obtained, and the inner loop dynamics model of the quadrotor drone is established, such as Figure 2 shown.

[0037]

[0038] Step 2: Obtain the error equation based on the outer loop system dynamics model and the position information of the leader and follower drones; Specifically, step 201: establishing an error relationship between the leader UAV and the follower UAV based on the coordinates of the leader UAV and the follower UAV in the world coordinate system and the speed information of the quadrotor UAV.

[0039] In this embodiment, the following Take the error equation of a follower drone as an example. represents the horizontal coordinate error between the follower UAV and the leader UAV, Represents the ordinate error between the follower UAV and the leader UAV, from which the position error representation can be obtained:

[0040] Step 202: Based on the position error, the velocity error, and the dynamic model of the quadrotor drone, an outer loop position error may be established.

[0041] Using sensors such as the inertial measurement unit (IMU) and compass in the drone's flight controller, real-time measurements are performed to obtain the velocity information of each drone. This information is then subtracted to obtain the velocity error. In theory, the velocity of a drone can be derived by taking the time derivative of its displacement, and then subtracting this velocity to obtain the velocity error.

[0042] Based on the position error representation, both sides simultaneously Take the derivative, so the The outer ring position error of the follower drone and the leader drone can be established as:

[0043] Step 203: Establish an outer loop error equation under a pulse attack environment based on the outer loop position error and the pulse injected error data.

[0044] Considering the pulse attack environment, it is assumed that the set of pulse occurrence times is , and the length of the pulse time interval satisfies the parameter Poisson distribution, the pulse intensity parameter is , this pulse time series is recorded as The model of random pulse deception attack is:

[0045] The outer loop error equation under the random pulse deception attack environment can be obtained:

[0046] in, represents the error between the leader and follower's horizontal coordinates, represents the error between the leader and follower ordinates, represents the leader line speed and Axis angle and follower linear velocity and Error in axis angle. represents the linear velocity of the follower, represents the linear velocity of the leader, represents the angular velocity of the follower, represents the angular velocity of the leader. represents the UAV distance parameter, where and Indicates the control output of the controller.

[0047] Step 3: Based on the inner loop system dynamics model and the position information of the leader and follower, obtain the error equation; Specifically, step 301: by Taking the axis as an example, based on the position coordinates of the desired movement and the current position information of the quadrotor, the position error equation between the two is established:

[0048]

[0049] According to the position error equation and the erroneous data injected by random pulses, the inner loop error equation under random pulse deception attack is established:

[0050] Step 4: Design the outer loop controller of the quadrotor drone. Based on the outer loop error equation and kinematic model, use a state feedback controller to perform feedback control on the quadrotor drone. The specific steps are as follows: Step 401: Design a state feedback controller to enable the quadrotor drone to successfully complete the leader-follower formation mission.

[0051] First, based on the leader UAV's linear velocity information, the error in the horizontal coordinates of the leader UAV and the error in the vertical coordinates, and the error information of the linear velocity and axis angle of the leader UAV and the follower UAV, a controller of the following form is designed:

[0052] in, is the gain of the controller, which can ensure the effectiveness of the outer loop control.

[0053] Step 402: Design the state feedback controller gain according to the intensity and frequency of the random pulse deception attack so as to enable it to resist the random pulse deception attack.

[0054] According to the designed controller gain Based on the information of the strength and frequency of the random pulse deception attack, the gain can be designed as follows:

[0055] The controller can not only suppress the negative impact of random pulse deception attacks, but also has multi-dimensional robustness, that is, it can simultaneously resist the combination of complex pulse deception attacks related to intensity, frequency, pattern, and target. Moreover, the state feedback controller gain of the final design is It also has significant advantages in multi-dimensional parameter fusion, constraint optimization, adaptive framework and collaborative defense, which are mainly manifested in: Performance guarantee: Achieve optimal or suboptimal robustness while meeting strict constraints on steady-state accuracy, transient deviation, recovery time, and control energy.

[0056] Adaptive potential: The architectural design paves the way for future dynamic gain adjustment based on real-time attack signature evaluation, enhancing the system's survivability in long-term confrontations.

[0057] Synergy: Organically combine with other defense layers of the system to form a more powerful overall defense system.

[0058] Quantitative Verifiability: The design process is based on clear 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 set attack scenarios).

[0059] prove: make Indicates that the outer loop error system has exceeded the initial value Solution, remember , . Take the Lyapunov function as: , but The derivative of the system along the outer loop in continuous dynamics with respect to time is: Substituting the outer loop controller into the above equation yields:

[0060] Given the introduction of random impulse deception attack, it can be deduced that:

[0061] According to the properties of mathematical expectation, taking the mathematical expectation on both sides, we can get:

[0062] Using Taylor expansion, it can be simplified to:

[0063] This means

[0064] Among them, the constant satisfies Therefore, under random pulse spoofing attacks, the outer loop error system is exponentially stable.

[0065] Step 5: Design the inner loop controller of the quadrotor drone. Based on the inner loop error equation and kinematic model, a state feedback controller is also used to perform feedback control on the quadrotor drone. The specific steps are as follows: Specifically, step 501: using the Lyapunov backstepping method, a state feedback controller is designed to make the error between the speed command issued by the quadrotor drone and the desired speed command approach 0. Based on the continuous dynamic information, a continuous controller with designable control gains is introduced.

[0066] by Taking direction as an example, the specific process is as follows: First, since the inner loop dynamics of the quadrotor drone is an underactuated and strongly coupled system, the system is simplified. The axis can be simplified to:

[0067]

[0068] in, express The desired displacement in the axial direction, express The expected speed in the axis direction is calculated based on the expected attitude information and current attitude information released by the quadrotor drone using the Lyapunov backstepping method. Design a controller as follows:

[0069] in is the gain of the inner loop controller, which can ensure the effectiveness of the inner loop control.

[0070] Secondly, according to the designed controller gain Based on the information of the strength and frequency of the random pulse deception attack, the gain can be designed as follows:

[0071] The inner loop controller can effectively suppress the negative impact of random pulse deception attacks.

[0072]

[0073] According to the intensity and frequency of random pulse deception attacks, the control gain is designed to be able to resist random pulse deception attacks:

[0074] prove: make Indicates that the inner loop error system has exceeded the initial value The solution of . Using the backstepping method, the Lyapunov function is: , in, but The derivative of the system along the outer loop in continuous dynamics with respect to time is:

[0075] Substituting the inner loop controller into the above formula, we can get:

[0076] Similar to the outer ring system, we can finally get the following formula:

[0077] This means

[0078] Among them, the constant satisfies as well as Therefore, the inner-loop error system is exponentially stable under random pulse spoofing attacks.

[0079] Step 502: Design a controller for the remaining gesture quantities.

[0080] and The direction controller is similar, and the remaining posture controller can be obtained as:

[0081] Furthermore, the connection between the inner loop control system and the outer loop control system is established. The above inner loop controller and outer loop controller can be applied in the actual random pulse deception attack environment. According to the dynamic equation of the quadcopter drone:

[0082] Therefore, the outer-loop controller performs continuous control on the leading-following task of the quadrotor UAV and sends the expected control quantity to the inner-loop controller. The inner-loop controller actually controls the quadrotor UAV according to the expected control quantity. When the error between the expected control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leading-following task of the quadrotor UAV.

[0083] That is, when the error between the outer loop's ideal linear velocity and the inner loop's actual linear velocity approaches 0, and the error between the outer loop's ideal yaw rate and the inner loop's actual yaw rate approaches 0, the outer loop control task can be performed smoothly. Therefore, the inner loop control task is to converge the error between the two to 0 as much as possible, such as Figure 3 shown.

[0084] As an example, take the leader drone drawing a circle as an example. Assume that the leader drone starts from the coordinate Starting from the coordinates Starting from the position of the motion trajectory, the error relationship between the two is as follows: Figure 5 The specific data are shown in Table 1.

[0085] Table 1 Leader-follower formation status of the quadrotor drone under the controller

[0086] Example 2 In one embodiment of the present disclosure, a control system for a quadrotor drone is provided to protect against random pulse spoofing attacks, including: The dynamic model construction module is used to construct the outer loop system dynamic model and the inner loop system dynamic model according to the motion characteristics and motion data of the quadrotor drone; An attack injection error construction module is used to construct an outer loop position error equation based on the outer loop system dynamics model and the position information of the leader and follower. The outer loop error equation under a random pulse deception attack is established based on the outer loop position error equation and the error data injected by the random pulse. The inner loop position error equation is constructed based on the inner loop system dynamics model and the position information of the leader and follower. The inner loop error equation under a random pulse deception attack is established based on the inner loop position error equation and the error data injected by the random pulse. The inner and outer loop control modules are used to construct a continuous outer loop controller and an inner loop controller based on the outer loop error equation and the inner loop error equation, and design the controller gain according to the intensity and frequency of the random pulse deception attack. The outer loop controller continuously controls the leading-following task of the quadrotor UAV and sends the expected control amount to the inner loop controller. The inner loop controller actually controls the quadrotor UAV according to the expected control amount. When the error between the expected control amount and the actual control amount of the inner loop controller approaches 0, the control realizes the leading-following task of the quadrotor UAV.

[0087] Example 3 In one embodiment of the present disclosure, a computer program product is provided, including a computer program, which, when executed by a processor, implements the control method of a quadrotor drone against random pulse deception attacks.

[0088] Example 4 In one embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, which is used to store computer instructions. When the computer instructions are executed by a processor, the control method of the quadrotor drone against random pulse deception attacks is implemented.

[0089] Example 5 In one embodiment of the present disclosure, an electronic device is provided, comprising: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes the control method of the quadrotor drone against random pulse deception attacks.

[0090] Specifically, the electronic equipment includes a heterogeneous architecture consisting of a Raspberry 4B (host computer) and a Pixhawk 6C mini flight controller (lower-level controller). The system deploys the ROS (Robot Operating System) environment as the core middleware, and after in-depth configuration, it can achieve: Full-process mission support: covering the full development cycle of quadrotor drones from virtual simulation Gazebo to physical deployment; Anti-pulse deception attack formation control: Natively run the leader-follower formation program in the ROS layer to accurately execute collaborative tasks under random pulse deception attack environments; Cross-platform communication: The MAVROS bridge module enables efficient command / data interaction between the Raspberry Pi (decision layer) and the Pixhawk (execution layer).

[0091] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0092] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0093] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Those skilled in the art should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A control method for a quadrotor drone against random pulse deception attacks, characterized in that: include: According to the motion characteristics and motion data of the quadrotor drone, the outer loop system dynamics model and the inner loop system dynamics model are constructed respectively; Based on the outer loop system dynamics model, the position information of the leader and follower, the outer loop position error equation is constructed. According to 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 follower, the inner loop position error equation is constructed. According to 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. Based on the outer-loop error equation and the inner-loop error equation, a continuous outer-loop controller and inner-loop controller are constructed, and the controller gain is designed according to the intensity and frequency of the random pulse deception attack. The outer-loop controller performs continuous control on the leading-following task of the quadrotor UAV and sends the expected control quantity to the inner-loop controller. The inner-loop controller actually controls the quadrotor UAV according to the expected control quantity. When the error between the expected control quantity and the actual control quantity of the inner-loop controller approaches 0, the control realizes the leading-following task of the quadrotor UAV.

2. The control method for a quadrotor drone against random pulse deception attacks according to claim 1, wherein: According to the motion environment of the quadrotor UAV, the position information, speed information and yaw angular velocity information of the quadrotor UAV are obtained, and the outer loop system dynamics model of the single quadrotor UAV is established; according to the motion environment of the quadrotor UAV, the position information, yaw angle information, roll angle information and pitch angle information of the quadrotor UAV are obtained, and the inner loop system dynamics model of the single quadrotor UAV is established.

3. The control method for a quadrotor drone against random pulse deception attacks according to claim 1, wherein: Based on the leader coordinates of the expected motion and the position information of the quadrotor drone, the error between the leader and the quadrotor 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 of the leader and 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 quadrotor drone against random pulse deception attacks according to claim 1, wherein: According to the position coordinates of the desired motion and the current position information of the quadrotor drone, 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 quadrotor drone against random pulse deception attacks according to claim 1, wherein: Based on the continuous dynamic information, a continuous outer-loop controller and an inner-loop controller with designable control gains are introduced. According to the frequency and intensity of the random pulse deception attack, the control gains of the two controllers are designed, and the connection between the inner-loop system and the outer-loop system is established. According to the dynamic equation of the quadrotor drone, when the error between the ideal linear velocity of the outer-loop system and the actual linear velocity of the inner-loop system tends to 0, and the error between the ideal yaw angular velocity of the outer-loop system and the actual yaw angular velocity of the inner-loop system tends to 0, the control task of the outer-loop system is smoothly executed.

6. The control method for a quadrotor drone against random pulse deception attacks according to claim 1, wherein: The acquisition process of the error data injected by random pulses includes: considering the pulse attack environment, setting the pulse generation time, and the length of the pulse time interval meets the parameter Poisson distribution, obtain pulse intensity parameters, build pulse time series and random pulse deception attack model.

7. A control system for a quadrotor drone against random pulse deception attacks, characterized in that: include: The dynamic model construction module is used to construct the outer loop system dynamic model and the inner loop system dynamic model according to the motion characteristics and motion data of the quadrotor drone; An attack injection error construction module is used to construct an outer loop position error equation based on the outer loop system dynamics model and the position information of the leader and follower. Based on the outer loop position error equation and the error data injected by random pulses, the outer loop error equation under the random pulse deception attack is established; Based on the inner loop system dynamics model and the position information of the leader and follower, the inner loop position error equation is constructed. According to 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. The inner and outer loop control modules are used to construct a continuous outer loop controller and an inner loop controller based on the outer loop error equation and the inner loop error equation, and design the controller gain according to the intensity and frequency of the random pulse deception attack. The outer loop controller continuously controls the leading-following task of the quadrotor UAV and sends the expected control amount to the inner loop controller. The inner loop controller actually controls the quadrotor UAV according to the expected control amount. When the error between the expected control amount and the actual control amount of the inner loop controller approaches 0, the control realizes the leading-following task of the quadrotor UAV.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the control method of the quadrotor drone against random pulse deception attacks described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the control method of the quadrotor drone against random pulse deception attacks as described in any one of claims 1 to 6 is implemented.

10. An electronic device, characterized in that: include: 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 of a quadrotor drone against random pulse deception attacks as described in any one of claims 1 to 6.

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