CN-119596969-B - Self-adaptive elastic formation control method for four-rotor unmanned aerial vehicle under DoS attack

CN119596969BCN 119596969 BCN119596969 BCN 119596969BCN-119596969-B

Abstract

The invention provides a self-adaptive elastic formation control method of a four-rotor unmanned aerial vehicle under a DoS attack, which relates to the technical field of unmanned aerial vehicle safety control, and is based on a multi-machine formation system of a leader-follower mode under an undirected network topology graph, a mathematical model is built aiming at the DoS attack blocking a communication channel, and a changed multi-machine system network topology is built according to the DoS attack; the method comprises the steps of constructing a distributed elastic observer to obtain leader information unknown under the DoS attack, constructing tracking formation errors containing time-varying offset signals according to output of the observer, taking a neighborhood where the formation errors can be converged to zero as a control target, and designing a self-adaptive elastic formation controller by using a backstepping method to realize self-adaptive elastic formation control of the four-rotor unmanned aerial vehicle. The control method provided by the invention considers the condition that at least one communication channel is attacked by DoS, and the constructed self-adaptive elastic formation controller can ensure that the tracking formation error of the multi-machine formation system converges to a zero neighborhood under the DoS attack, so that the expected formation is achieved.

Inventors

JIN PENG
ZHU YUTAO
ZHOU GUOPENG
LI YOUNENG

Assignees

武汉纺织大学

Dates

Publication Date: 20260512
Application Date: 20241115

Claims (4)

1. The adaptive elastic formation control method for the four-rotor unmanned aerial vehicle under the DoS attack is characterized in that when a follower is subjected to the DoS attack, unknown leader information is estimated by using a distributed elastic observer (4), an adaptive elastic formation controller and a parameter adaptive update law are designed by using a back-stepping method and a fuzzy logic system, the adaptive elastic formation control of the four-rotor unmanned aerial vehicle is realized, tracking formation errors are converged to a zero neighborhood, and the expected formation is achieved, and the method comprises the following steps: Step1, introducing graph theory, constructing a network topology model of a leader-follower mode based on an undirected graph, and describing a communication relationship among multiple unmanned aerial vehicles; step 2, constructing a dynamics model (1) of a leader and a follower in a four-rotor unmanned aerial vehicle formation system; Step 3, establishing a DoS attack mathematical model and a network topology after the DoS attack, establishing a tracking formation error, and defining a control target; Step 4, constructing a distributed elastic observer (4) so that unknown leader information can be estimated when a follower is attacked by DoS; Step 5, constructing a state error, and designing a self-adaptive elastic formation controller by using a back-stepping method and a fuzzy logic system, so that the system realizes self-adaptive elastic formation control of the four-rotor unmanned aerial vehicle under the DoS attack, and the tracking formation error is converged to a zero neighborhood; Step 6, performing simulation verification on a four-rotor unmanned aerial vehicle self-adaptive elastic formation control method under DoS attack by using MATLAB, and deriving a visual graph of unmanned aerial vehicle state in the system; step 4, constructing a distributed elastic observer (4), wherein the specific method comprises the following steps: When the multi-machine formation system is subjected to DoS attack, at least one communication channel in the system can be blocked, the follower unmanned aerial vehicle can not receive the leader information, the distributed elastic observer (4) is constructed, so that the follower unmanned aerial vehicle affected by the DoS attack can estimate the leader information, and the first design is designed The distributed elastic observer (4) of the individual follower unmanned aerial vehicle is: (4) Wherein the method comprises the steps of And All represent the normal number to be designed; Represent the first The communication channel between the individual drone and the leader is blocked by DoS attacks, otherwise ; Estimated value, state representing leader information For calculating Higher derivatives of (2); Step 1, introducing graph theory, describing information interaction relations among unmanned aerial vehicle individuals in a multi-machine formation system by using a network topology graph, and constructing a network topology model based on a leader-follower mode under undirected graph theory: By using Representing a virtual leader Multiple-machine formation system composed of followers, each unmanned plane in the system is individually called as a node, wherein A set of nodes is represented and, Representing a set of node communication paths The representation can be with the first Neighbor node set for normal communication of individual nodes and adjacent matrix Representing the communication state between neighboring nodes when Represent the first The individual node The individual nodes can communicate normally, otherwise Using an input degree matrix Representing the number of neighbor nodes that each node can communicate with, wherein Represent the first Definition of a leader adjacency matrix When the first When the individual node can receive the leader information And is used in combination To ensure connectivity of the network topology, assume that leader information can be passed to the unmanned individual through at least one continuous channel; step 2, constructing a dynamics model (1) of a leader and a follower in a four-rotor unmanned aerial vehicle formation system, wherein the specific method comprises the following steps: kinetic model of follower (1) th in a multimachine formation system The kinetic model (1) of the individual followers is described as: (1) Wherein the method comprises the steps of Represent the first Positional information of the individual unmanned aerial vehicle; representing the roll angle, pitch angle and yaw angle of the unmanned aerial vehicle; representing the total thrust of the unmanned aerial vehicle; And Respectively representing the mass and the gravitational acceleration of the unmanned aerial vehicle; representing the triaxial moment of inertia of the unmanned aerial vehicle; Representing the air resistance coefficient; Representing the unmanned attitude control torque, since the dynamics model (1) of the follower is strictly fed back, the following variables are defined: , , , The kinetic model (1) of the follower can be rewritten as: (2) Wherein the method comprises the steps of Represent the first Index number of the unmanned aerial vehicle; Respectively represent A position and attitude subsystem; Represent the first A control input of the personal unmanned aerial vehicle; Represent the first Outputting a system of the unmanned aerial vehicle; (2) The leader system is described as: (3) Wherein the method comprises the steps of Representing the status of the leader drone, Representing the system output of the leader drone, 、 Known system matrix and vector, respectively, to achieve the desired multi-machine formation control, time-varying formation offset vectors are defined Each of which is provided with Are continuously conductive.
2. The adaptive elastic formation control method for a quad-rotor unmanned helicopter under DoS attack according to claim 1 is characterized in that step 3, a DoS attack mathematical model and a network topology after DoS attack are established, tracking formation errors are established, and control targets are defined by the specific method: For any arbitrary Definition of Indicating the cut-off of the first Unmanned plane and the first Unmanned aerial vehicle communication channel Duration of a secondary DoS attack, in which And Respectively represent the first Start time and end time of the secondary DoS attack, Represent the first Duration of the secondary DoS attack, definition of the first 、 The time set of unmanned aerial vehicle affected by DoS attack is Establishing a DoS attack time sequence set: Wherein the method comprises the steps of A set of time series representing at least one communication channel within the multi-machine formation system blocked by DoS attacks, Indicating normal time sequence set of multi-machine formation system communication, assuming constant existence for meeting practical condition due to energy support required by DoS attack So that ; When DoS attack occurs, the system network topology changes accordingly, concretely as: defining control targets, establishing tracking formation errors The controller is utilized to enable tracking formation errors of the multi-machine formation system to converge to a zero neighborhood under DoS attack.
3. The adaptive elastic formation control method for a quad-rotor unmanned helicopter under DoS attack according to claim 2 is characterized in that step 5, by combining the distributed elastic observer (4), the adaptive elastic formation controller is designed by constructing a state error and using a backstepping method, and the specific method is as follows: When a multi-aircraft formation system is subjected to DoS attacks, the adjacency matrix coefficients between the affected unmanned aircraft become zero, resulting in conventional distributed formation errors The first term of which is discontinuous, so that the controller cannot be designed using the backstepping method, so that it is calculated from the dynamics model (1) of the follower and by the distributed elastic observer (4) Defining a tracking state error: (5) Wherein the method comprises the steps of Representing a virtual controller; Step1 from equations (1), (4) and (5) The derivative of (2) is: (6) Design of Lyapunov function : (7) Designing virtual controllers : (8) Wherein, the A constant to be designed greater than zero; step2 from equations (1) and (5) The derivative of (2) is: (9) Design of Lyapunov function : (10) Wherein, the Is a constant to be designed that is greater than zero, Representing the error of the estimation, The adaptive parameters are represented by a set of parameters, Representation pair Is used for the estimation of the (c), A weight vector representing a fuzzy logic system; Deriving formula (10): (11) estimating system nonlinear term by introducing fuzzy logic system : (12) Wherein the method comprises the steps of , And is a constant to be designed greater than zero, then equation (11) can be rewritten as: (13) according to the young's inequality, there are: (14) substituting equation (14) into equation (13) to design the controller And adaptive law : (15) (16) According to formulas (15), (16) and young's inequality, there are: (17) Selection of And The method comprises the following steps: (18) From equation (18), by constructing a distributed elastic observer (4), designing a state error (5), designing a controller (15) and an adaptive law (16) by using a back-stepping method and a fuzzy logic system, tracking a formation error The method can converge to the neighborhood of zero, namely the multi-machine formation system can reach the expected formation under the DoS attack, and the control target is realized.
4. The adaptive elastic formation control method of a quad-rotor unmanned helicopter under DoS attack according to claim 3, wherein in step 6, in order to verify the reliability of the control method, a MATLAB is used to perform a simulation experiment, and the specific method is as follows: A multi-machine formation system is formed by using a Leader four-rotor unmanned aerial vehicle and three follower four-rotor unmanned aerial vehicles, wherein the Leader is represented by a Leader, the followers are represented by 1,2 and 3, the expected distance between the followers is time-varying, and the state of each unmanned aerial vehicle in the formation process is visualized by using MATLAB to obtain a visualization state diagram of each unmanned aerial vehicle under the DoS attack of the multi-machine formation system.

Description

Self-adaptive elastic formation control method for four-rotor unmanned aerial vehicle under DoS attack Technical Field The invention relates to the field of unmanned aerial vehicle safety control, in particular to a four-rotor unmanned aerial vehicle self-adaptive elastic formation control method under a DoS attack. Background The four-rotor unmanned aerial vehicle has the characteristics of small volume, light weight, simple structure, low manufacturing cost and the like, and is widely applied to civil fields such as agriculture and forestry plant protection, rescue and relief work, electric power inspection and the like. With the development of control technology, the multi-unmanned aerial vehicle formation control technology can solve the limitations of load and endurance, and meanwhile improves the efficiency of complex task execution, so that the multi-unmanned aerial vehicle formation control technology can efficiently execute military tasks such as battlefield investigation, military combat and the like. Multi-machine formation control has become an important research direction in the field of unmanned aerial vehicles. The core idea of the multi-unmanned aerial vehicle formation control is to update the state of each unmanned aerial vehicle through individual information interaction, so that the multi-unmanned aerial vehicle formation dynamic state in a synchronous system is realized. Because the multi-machine formation is extremely dependent on network topology and network communication channels in the flight process, once the multi-machine formation is attacked by a malicious network, an attacker can easily steal or tamper with the information of the unmanned aerial vehicle, and even takes control rights of the unmanned aerial vehicle. Therefore, unmanned aerial vehicle safety control technology cannot be ignored. The invention mainly researches DoS attack in network attack, which is characterized in that an attacker maliciously occupies communication resources of a target system by sending a large number of requests to cause system network congestion, thereby realizing blocking of a system network communication channel and preventing a follower from acquiring information of a leader and adjacent individuals. Disclosure of Invention Aiming at the safety problem existing in the prior art, the invention aims to provide a self-adaptive elastic formation control method for a four-rotor unmanned aerial vehicle under the DoS attack, and aims to solve the technical problem of ensuring that a four-rotor unmanned aerial vehicle formation system can reach an expected formation under the DoS attack. In order to achieve the purpose, the technical scheme provided by the invention is that the self-adaptive elastic formation control method of the four-rotor unmanned aerial vehicle under the DoS attack comprises the following steps: a self-adaptive elastic formation control method of a four-rotor unmanned aerial vehicle under a DoS attack is characterized in that when the DoS attack occurs, at least one communication channel in a multi-rotor unmanned aerial vehicle formation system is blocked, an unmanned aerial vehicle individual cannot acquire information of a leader and adjacent individuals, a distributed elastic observer is constructed, the multi-rotor unmanned aerial vehicle formation system still can acquire unknown leader information under the DoS attack, a fuzzy logic system is used for estimating a system unknown nonlinear equation, and a self-adaptive elastic formation controller and a parameter self-adaptive update law are designed by combining a backstepping method, so that the self-adaptive elastic formation control of the four-rotor unmanned aerial vehicle is realized, and the method comprises the following steps: Step1, introducing graph theory, constructing a network topology model of a leader-follower mode based on an undirected graph, and describing a communication relationship among multiple unmanned aerial vehicles; step 2, constructing a dynamics model of a leader and a follower in a four-rotor unmanned aerial vehicle formation system; Step 3, establishing a DoS attack mathematical model and a network topology after the DoS attack, establishing a tracking formation error, and defining a control target; step 4, constructing a distributed elastic observer, so that unknown leader information can be estimated when a follower is attacked by DoS; Step 5, constructing a state error, and designing a self-adaptive elastic formation controller by using a back-stepping method and a fuzzy logic system, so that the system realizes self-adaptive elastic formation control of the four-rotor unmanned aerial vehicle under the DoS attack, and the tracking formation error is converged to a zero neighborhood; And 6, performing simulation verification on the proposed control algorithm by using MATLAB, and deriving a visual graph of the unmanned aerial vehicle state in the system. Compared with the existing multi-ma