CN-121995773-A - Unmanned aerial vehicle fixed time control method and system for cooperatively inhibiting interference and IMU spoofing

CN121995773ACN 121995773 ACN121995773 ACN 121995773ACN-121995773-A

Abstract

The invention discloses a method and a system for controlling fixed time of an unmanned aerial vehicle for cooperatively inhibiting interference and IMU spoofing, wherein the method comprises the steps of constructing a nonlinear attitude dynamics model and a controlled model which explicitly comprise IMU spoofing attack and external lumped disturbance; according to the nonlinear attitude dynamic model, introducing a virtual intermediate variable to obtain a feedforward compensation signal, introducing a piecewise defined auxiliary function, constructing a fixed-time sliding mode function according to a controlled model, constructing a total control law according to an observed value and the fixed-time sliding mode function, ensuring that the attitude tracking error of a closed-loop system converges to a stable state within a preset fixed time, and ensuring that the upper bound of the total convergence time depends on the parameters of a controller. The invention can effectively distinguish and inhibit interference and attack under the strong countermeasure environment of the unmanned aerial vehicle, and realize quick recovery and stable control of the flight attitude, thereby enhancing the adaptability and task execution reliability of the unmanned aerial vehicle under the complex electromagnetic and acoustic interference environment.

Inventors

HE SHUPING
LAN TIAN
REN CHENGCHENG
WANG GUANGYU
CHENG PENG
WANG LONGLONG
JIANG JINHUA
TIAN FENG

Assignees

安徽大学

Dates

Publication Date: 20260508
Application Date: 20260409

Claims (10)

1. A method for controlling a fixed time of an unmanned aerial vehicle for cooperatively suppressing interference and IMU spoofing, the method comprising: Based on the action mechanism of acoustic resonance on the gyroscope, obtaining the frequency characteristic of the IMU affected by resonance, and constructing a nonlinear attitude dynamics model and a controlled model which are explicitly composed of IMU deception attack and external lumped disturbance by combining with the physical structure of the unmanned plane; according to the nonlinear attitude dynamic model, introducing a virtual intermediate variable, and acquiring a feedforward compensation signal, wherein the feedforward compensation signal comprises an observation value and a consistent upper bound of an observation error; Introducing auxiliary functions defined by sections, and constructing a fixed-time sliding mode function according to the controlled model; And constructing a total control law according to the observed value and the fixed time sliding mode function, ensuring that the attitude tracking error of the closed loop system converges to a stable state within a preset fixed time, and the upper bound of the total convergence time depends on the controller parameters.
2. The unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing of claim 1, wherein the step of constructing the nonlinear attitude dynamics model and the controlled model specifically comprises: quantifying an IMU acoustic resonance spoofing attack signal; Constructing a controlled matrix model based on the physical structure of the unmanned aerial vehicle; and constructing the nonlinear attitude dynamics model according to the attack signals and the controlled matrix model.
3. The unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing according to claim 2, wherein the step of quantifying IMU acoustic resonance spoofing attack signals specifically comprises: Acquiring a resonance influence frequency range corresponding to an IMU model of the unmanned aerial vehicle, and determining the action characteristic of acoustic attack on the gyroscope; defining the original noise signal output by the IMU under the attack of acoustic resonance as ; Filtering the original noise signal through a filter of an IMU, filtering high-frequency components, and reserving low-frequency components to form the attack signal: ; Wherein, the Respectively, rolling The original noise components of the pitch theta and yaw phi axes, The low frequency attack components of the drone in three axes respectively.
4. A method of unmanned aerial vehicle fixed time control for co-suppressing interference and IMU spoofing as recited in claim 3, wherein the controlled matrix model is: ; Wherein, the The attitude angle vector is represented as such, , Representing the three-axis angular velocity vector, , 、、 Respectively representing the angular speeds of the unmanned aerial vehicle on three axes; ; 、、 representing the torque of the drone in three axes, The moment of inertia of the motor is represented, The residual motor rotational speed is indicated, , Represents the three-axis aerodynamic drag coefficient, , Representing the three-axis control input vector, Respectively representing control inputs of the drone in three axes, , , The physical disturbance vector is represented by a vector of physical disturbances, Representing the lumped perturbations in the three axes respectively, Unmanned aerial vehicle for representing IMU acquisition angular velocity of the machine three axes.
5. The unmanned aerial vehicle fixed time control method for cooperatively inhibiting interference and IMU spoofing of claim 4, wherein the nonlinear attitude dynamics model is: ; Wherein, the , , , , , , Representing the spoofed IMU measured output.
6. The unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing according to claim 5, wherein said step of obtaining a feedforward compensation signal according to said nonlinear attitude dynamics model and introducing a virtual intermediate variable comprises: According to the nonlinear attitude dynamics model, obtaining an intermediate variable through coordinate transformation: ; obtaining the intermediate variable dynamic equation according to the intermediate variable and the controlled matrix model: ; Designing an intermediate variable observer according to the intermediate variable dynamic equation and the nonlinear attitude dynamic model: ; Constructing an observation error dynamic equation according to the intermediate variable and the intermediate variable observer: ; constructing a first Lyapunov function according to the observation error dynamic equation: ; and performing stability criterion through the first Lyapunov function to obtain a convergence upper bound of the observation error: ; Wherein, the The transform coefficients are represented by a set of coefficients, , , , , Respectively are , , , , Is used for the observation of the (a), Representing a programmable observer gain matrix, , , , , Is a weight coefficient and , Is a positive definite matrix of the matrix and the matrix, Is that Is used to determine the minimum characteristic value of the (c), And Is a convergence coefficient and is composed of And It is determined that the number of the cells, Indicating a consistent upper bound for observed errors.
7. The unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing of claim 6, wherein the step of introducing a piecewise defined auxiliary function and constructing a fixed time sliding mode function according to the controlled model comprises: Defining an error dynamic equation according to the controlled matrix model: ; The design auxiliary function is: ; constructing the fixed time sliding mode function according to the error dynamic equation and the auxiliary function: ; Wherein, the Indicating a desired angular acceleration, the desired angular acceleration, , , Representation adjustment Is set to be a gain factor of an upper bound of (c), , , 。
8. The unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing of claim 7, wherein the step of constructing a total control law according to the observed value and the fixed time sliding mode function ensures that the attitude tracking error of the closed loop system converges to a steady state within a preset fixed time, and the upper bound of the total convergence time depends on the controller parameters, specifically comprises: construction of equivalent control law : ; Constructing a fixed time approach law : ; According to the equivalent control law And the fixed time approach law Constructing an overall control law : ; According to the fixed time sliding mode function, analyzing the time upper bound of the approach section, and designing a second Lyapunov function as The derivative is obtained by: ; According to Deriving the convergence time : ; When the system state reaches the sliding mode surface, the following conditions are satisfied I.e. Designing a third Lyapunov function as Is combined with Deriving and obtaining the upper bound of the stable time as ; Acquiring the total convergence time upper bound of the closed-loop system attitude tracking error: ; Wherein, the , , , Indicating that the control gain is to be applied, Is a design parameter and 。
9. The unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing of claim 8, wherein the control gain Is selected following the following constraints: ; Wherein, the Is that With respect to Li Puxi z continuous constant.
10. The unmanned aerial vehicle fixed time control system for cooperatively inhibiting interference and IMU spoofing is characterized by comprising an instruction end, an algorithm end and an equipment end; The instruction end comprises a ground station and control equipment, wherein the ground station is used for displaying the specific running state of the unmanned aerial vehicle in real time, and the control equipment is used for sending a desired gesture control instruction according to the user demand; The algorithm end is connected with the instruction end and is used for executing the unmanned aerial vehicle fixed time control method for cooperatively inhibiting interference and IMU deception according to any one of claims 1-9 according to the expected gesture control instruction, and outputting an execution control instruction; The equipment end is connected with the algorithm end corresponding to the quad-rotor unmanned aerial vehicle and is used for completing fixed time stabilization in an environment subjected to physical layer disturbance and information layer attack by receiving the execution control instruction, so that cooperative inhibition of IMU spoofing attack and external interference is realized.

Description

Unmanned aerial vehicle fixed time control method and system for cooperatively inhibiting interference and IMU spoofing Technical Field The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle fixed time control method for cooperatively restraining interference and IMU spoofing and an unmanned aerial vehicle fixed time control system for cooperatively restraining interference and IMU spoofing. Background In increasingly complex environments, unmanned aerial vehicles are not only required to cope with strong gust physical disturbances caused by severe weather conditions, but are also exposed to the severe threat of various non-contact "soft-kill" weapons. In particular to an acoustic spoofing attack of a core navigation component, namely an IMU (Inertial Measurement Unit ), false guidance information can be hidden and injected into a gyroscope by utilizing an acoustic resonance principle, so that the unmanned aerial vehicle is unstable in posture, deviated in track and even crashed under control in a non-early-warning state, and the task success rate of the unmanned aerial vehicle is seriously damaged. In the related art, the flight control system is mainly designed for physical wind disturbance resistance under a conventional scene, and is often failed due to lack of an effective situation awareness and cooperative defense mechanism when facing complex working conditions of coexistence of external physical strong disturbance and internal sensor malicious spoofing. Therefore, how to improve the robustness of the unmanned aerial vehicle in the extremely resistant environment and realize the accurate decoupling and the rapid suppression of malicious fraud and environmental interference becomes a key bottleneck for restricting the improvement of the actual combat effectiveness of the unmanned aerial vehicle. At present, unmanned aerial vehicle anti-interference control mainly depends on active disturbance rejection control, sliding mode control and improved methods thereof. Although the extended state observer can enhance the robustness of the system by estimating the lumped disturbance, the essence of the extended state observer is that the external disturbance and the false sensor signal are treated as the same disturbance type, and effective distinguishing and decoupling of the external disturbance and the false sensor signal cannot be realized. Furthermore, the extended state observer generally assumes that the disturbance is smoothly evolving, and in the face of acoustic spoofing signals with fast time varying, bursty characteristics, estimation lags tend to occur, resulting in a lack of pertinence in the compensation strategy. Although the intermediate variable observer theoretically has the capability of distinguishing different types of disturbance, the existing IVO (INTERMEDIATE VARIABLE OBSERVER ) design is mostly aimed at a linear system, and is difficult to be directly applied to a four-rotor unmanned aerial vehicle dynamics model with strong coupling and high nonlinearity. In terms of control strategies, while sliding mode control is widely used for immunity control, the characteristic of exponential convergence results in a slower response speed of the system. When the attitude of the unmanned aerial vehicle instantaneously deviates greatly due to IMU spoofing attack, the convergence time of sliding mode control is obviously prolonged, and the severe safety requirement for quickly recovering the attitude in an emergency scene cannot be met. Disclosure of Invention The present invention aims to solve at least one of the technical problems in the related art to some extent. Therefore, the invention aims to provide a method and a system for controlling the fixed time of the unmanned aerial vehicle, which are used for cooperatively restraining interference and IMU deception, so that the adaptability and the task execution reliability of the unmanned aerial vehicle under complex electromagnetic and acoustic interference environments are enhanced. In order to achieve the above objective, according to a first aspect of the present application, an embodiment of the present application provides an unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing, the unmanned aerial vehicle fixed time control method for cooperatively suppressing interference and IMU spoofing including: Based on the action mechanism of acoustic resonance on the gyroscope, obtaining the frequency characteristic of the IMU affected by resonance, and constructing a nonlinear attitude dynamics model and a controlled model which are explicitly composed of IMU deception attack and external lumped disturbance by combining with the physical structure of the unmanned plane; according to the nonlinear attitude dynamic model, introducing a virtual intermediate variable, and acquiring a feedforward compensation signal, wherein the f