UAV Cooperative Encirclement Control Method under Saturated Attack Mission

Abstract

The present invention discloses a method for cooperative encirclement control of unmanned aerial vehicles (UAVs) under saturation attack tasks. A target defense system model is established in the saturation attack task scenario, and the penetration probability of the UAV swarm is designed to ensure that at least one UAV completes the attack task. Based on the situation of a moving target with unknown target speed, a distributed cooperative encirclement controller for UAVs under saturation attack tasks is designed to enable the UAV swarm to accurately estimate the target speed, prevent collisions, and accurately encircle the target. When receiving an attack instruction, the target is attacked simultaneously along the shortest path. The present invention proposes a saturation attack control method based on the UAV swarm and designs a distributed cooperative encirclement controller. Exclusive command information is generated for different states of each UAV to better complete the encirclement. At the same time, the controller has good versatility and scalability. In terms of control effect, the cooperative encirclement controller has good convergence and anti-interference performance, ensuring that each UAV can quickly and accurately complete the task.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-agent control, and particularly relates to a cooperative pursuit control method for unmanned aerial vehicles (UAVs) under a saturation attack mission. Background Art

[0002] With the improvement of the autonomous capabilities of UAVs, UAVs have been widely used in various tasks. They have the advantages of low cost, high efficiency, good reliability, etc. However, a single UAV has limitations, and some complex tasks require multiple UAVs to cooperate to complete in order to ensure the success rate and efficiency of the tasks. Therefore, the two concepts of multi-UAV systems and UAV swarms have been studied by many scholars. How to control multiple UAVs to cooperate to complete tasks has become the current research topic.

[0003] Then, the task is specified, such as the saturation attack mission of a UAV swarm. First of all, the saturation attack mission refers to a tactical strategy in which a group of low-cost UAVs penetrate the defense system of a target and effectively attack high-value targets. A large-density UAV swarm will overload the air defense system of the target, thereby implementing the attack. However, the defense system of the target is complex and even diversified. How to use the fewest UAVs to complete the saturation attack mission has become the focus of research. Secondly, in terms of control, how to design a controller to effectively pursue a moving target is also a difficult problem. The state information of UAVs is time-varying. If there is information delay or inaccurate commands, it will be difficult to complete the pursuit, and at the same time, it will cause collisions between UAVs; secondly, the target is moving, but the speed is unknown to our UAVs. Without accurate estimation, it is difficult to complete the pursuit, and it is easy to cause the UAVs to not track the target well, reducing the success rate of the mission. Therefore, if a corresponding control target and cooperative pursuit controller are not designed for the saturation attack mission, it will be difficult for UAVs to estimate the target speed in the mission mode and difficult to form a pursuit.

[0004] In summary, in the prior art, there is little research on saturation attack mission strategies and control, and there is a lack of targeted distributed controllers. The pursuit strategy in the formation mode requires more information, increasing the complexity of control and making it difficult to ensure the stability and rapidity of a multi-UAV system. Summary of the Invention

[0005] Based on the saturation attack mission of a UAV swarm, the present invention provides a cooperative pursuit control method, enabling the UAV swarm to effectively estimate the target speed and at the same time prevent collisions to complete cooperative pursuit. When the UAVs receive an attack command, they launch an attack at the shortest distance.

[0006] Based on the above summary of the invention, the following technical solutions are adopted:

[0007] A cooperative pursuit control method for UAVs under a saturation attack mission, comprising the following steps:

[0008] 1) Build a target defense system model in the scenario of saturation attack mission, which includes three modules: early warning system, air defense missile and electronic jamming. Design the penetration probability of the UAV swarm to ensure that at least one UAV completes the attack mission;

[0009] 2) Based on the situation of moving targets with unknown target speeds, for the UAV model with an autopilot, design the UAV encirclement control target and distributed cooperative encirclement controller under the saturation attack mission. Then, drive the UAVs by the command converter to enable the UAV swarm to accurately estimate the target speed, prevent collisions, accurately surround, and finally complete the cooperative encirclement of the target; when receiving the attack command, attack the target simultaneously along the shortest path.

[0010] Furthermore, the cooperative encirclement control method based on the saturation attack mission can be described as:

[0011] (1) At least one UAV breaks through the target defense system and completes the saturation attack mission;

[0012] (2) The target is surrounded by UAVs;

[0013] (3) There are no collisions between UAVs;

[0014] (4) The UAVs can accurately estimate the speed of the target.

[0015] Furthermore, the designed penetration probability of the UAV swarm in step 1) is:

[0016]

[0017] According to the saturation attack mission scenario, it is required that at least one UAV breaks through. Therefore, the minimum number of UAVs dispatched is designed as:

[0018]

[0019] In the formula, n represents the number of target missiles; P f represents the average service probability of air defense weapons; P L represents the detection probability of the early warning system; Q a and Q e respectively represent the penetration probabilities of air defense weapons and electronic jamming; N m represents the minimum number of UAVs that successfully complete the mission; N represents the number of UAVs dispatched.

[0020] Furthermore, the UAV model with an autopilot in step 2) is expressed as

[0021]

[0022] In the formula, xi (t), y i (t), h i (t) is the center of mass position of UAV i at time t; where V i (t), θ i (t) represent the speed, heading angle and climbing angle of UAV i at time t respectively; V ci (t), θ ci (t) represents the corresponding speed command, heading angle command and climb angle command; τ V , τ θ Represents the time constant of each channel respectively.

[0023] Furthermore, in step 2), the control target of the drone capture under the saturation attack task is designed as follows:

[0024]

[0025] The distributed cooperative round-up controller is expressed as:

[0026]

[0027] In the formula, p i , p j , p target Respectively represent the position of UAV i, the position of UAV j and the position of the target; u i =[u xi ,u yi ,u hi ] T represents the acceleration signal of the drone in the forward, lateral and height channels respectively; r represents any point on the encirclement formed by the drone; D represents the distance between the target and the encirclement, if and only if p target ∈co(p), it is determined that the target is surrounded; N represents the number of drones; d ij represents the distance between UAV i and UAV j; d s Indicates the safe distance between drones. The distance between drones cannot be less than the safe distance; V i (t), V target (t) represents the actual speed of UAV i, the estimated speed of the target by UAV i and the actual speed of the target respectively; λ i , α, β, γ and K represent weight coefficients; C i represents the set of neighboring drones of drone i; f i Represents the obstacle avoidance function of UAV i.

[0028] Furthermore, the controller described in step 2) consists of an attack term, a collision avoidance term, and an adaptive estimation term.

[0029] Furthermore, the instruction converter described in step 2) is expressed as:

[0030]

[0031] where u i = [u xi , u yi , u hi T represents the acceleration commands of the UAV in the forward, lateral, and altitude channels respectively; τ V , τ θ represent the time constants of each channel respectively.

[0032] According to the designed saturation attack cooperative encirclement control method and the encirclement controller above, the minimum number of UAVs can be used to cooperatively encircle the target, and at the same time, the speed of the moving target can be estimated. During flight, collisions between UAVs are guaranteed not to occur.

[0033] The beneficial effects of the present invention are:

[0034] The present invention designs a UAV cooperative encirclement control method under saturation attack tasks. Compared with other encirclement methods, the present invention does not require pre-designed formations. The encirclement task can be completed according to the minimum safety distance between UAVs. Due to the real-time and complexity of the task, the method designed by the present invention is difficult to be predicted by the enemy, thereby increasing the success rate of the task. At the same time, the controller has good scalability, can ensure that a large number of UAVs complete the encirclement, and can be achieved with fewer state variables (the positions and speeds of the UAVs and the position of the target). However, traditional formation controllers will affect the formation quality and the success rate of the task due to the increase in the number of UAVs leading to computational complexity and the accuracy problem of formation information. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0036] Figure 1 It is the structure diagram of the distributed cooperative encirclement controller system;

[0037] Figure 2 It is the UAV cluster penetration probability diagram in the embodiment of the present invention;

[0038] Figure 3 This is the three-dimensional UAV cluster flight curve graph in the embodiment of the present invention. Specific implementation manners

[0039] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below in conjunction with specific implementation manners.

[0040] The UAV cooperative hunting control method under the saturation attack mission provided by the embodiment of the present invention mainly includes the defense system model of the target (early warning system, air defense missile system, and electronic jamming system) and the hunting process. Among them, the design structure diagram of the distributed cooperative hunting controller is as Figure 1 shown. The UAV first receives the mission command, the position information of the target, and the status information of other UAVs within the communication radius, and then the controller outputs corresponding control commands to achieve cooperative hunting of the target. Among them, the control commands of each UAV include speed, heading angle, and climb angle commands.

[0041] Specifically, it includes the following steps:

[0042] First, according to the defense system model of the target, calculate the penetration probability of the UAV cluster, and the probability can be expressed as:

[0043]

[0044] In the formula, n represents the number of target missiles; P f represents the average service probability of the air defense weapon; P L represents the detection probability of the early warning system; Q a , Q e respectively represent the penetration probabilities of the air defense weapon and the electronic jamming; N represents the number of UAVs dispatched.

[0045] According to the saturation attack mission scenario, it is required that at least one UAV completes the breakthrough. At the same time, it means that the number of UAVs dispatched is greater than the minimum number of UAVs dispatched, and the mission can be successfully completed. Therefore, the minimum number of UAVs dispatched is designed as:

[0046]

[0047] In the formula, N m represents the minimum number of UAVs that successfully complete the mission; N represents the number of UAVs dispatched.

[0048] Next, according to the above analysis, dispatch the corresponding number of UAVs, and at the same time design a distributed cooperative hunting controller to conduct cooperative hunting on the target. Linearize the nonlinear model of a certain type of fixed-wing UAV by feedback, and at the same time add an autopilot, then the final UAV model with an autopilot can be expressed as:

[0049]

[0050] wherein, x i (t), y i (t), h i (t) is the centroid position of UAV i at time t; where V i (t), θ i (t) respectively represent the speed, heading angle and climb angle of UAV i at time t; V ci (t), θ ci (t) represent the corresponding speed command, heading angle command and climb angle command; τ V , τ θ respectively represent the time constants of each channel.

[0051] Furthermore, based on the situation of a moving target with unknown target speed, for a UAV model with an autopilot, a UAV encirclement control target under a saturation attack mission is designed. The UAV encirclement control target under the saturation attack mission is as follows:

[0052]

[0053] wherein, p target represents the position of the target; λ i represents the weight coefficient; r represents any point on the encirclement formed by the UAVs; D represents the distance between the target and the encirclement. The target is determined to be surrounded if and only if p target ∈co(p); N represents the number of UAVs; d ij represents the distance between UAV i and UAV j; d s represents the safe distance between UAVs. The distance between UAVs cannot be less than the safe distance; V i (t), V target (t) respectively represent the actual speed of UAV i, the estimated speed of UAV i with respect to the target and the actual speed of the target.

[0054] Furthermore, according to the proposed cooperative encirclement control method, a distributed cooperative encirclement controller for a UAV swarm is designed under a saturation attack mission mode to control the UAVs to perform cooperative encirclement of the target while ensuring that there is no collision between UAVs. The distributed cooperative encirclement controller is expressed as:

[0055]

[0056] wherein, p i , p j respectively represent the position of UAV i and the position of UAV j; ui = [u xi , u yi , u hi T represents the acceleration signals of the UAV in the forward, lateral, and altitude channels respectively; α, β, γ, and K represent weight coefficients; C i represents the set of neighboring UAVs of UAV i; f i represents the obstacle avoidance function of UAV i. The controller u i consists of three terms: an attack term, a collision avoidance term, and an adaptive estimation term.

[0057] According to the distributed cooperative encirclement controller designed by the above formula, through command conversion, the actual control input commands required for the UAV model can be obtained. The command converter can be expressed as:

[0058]

[0059] According to the distributed cooperative encirclement controller, when time approaches infinity, the UAVs can encircle the target. At the same time, the speed of the UAVs is equal to the speed of the target, the estimated speed of the UAVs with respect to the target is equal to the speed of the target. And the distance between UAVs is always greater than the safety distance. Therefore, the UAV swarm has completed the cooperative encirclement command. When receiving an attack command, the UAVs will attack the target at the shortest distance, thus completing the saturation attack mission.

[0060] The numerical simulation of this embodiment is verified as follows. According to the defense system of the target, the number of target missiles n = 4, the average service probability P f = 0.7, the detection probability P L = 0.8 of the early warning system, the penetration probabilities Q a = 0.4, Q e = 0.6 of the air defense weapons and electronic jamming. The overall penetration probability simulation diagram is as Figure 2 shown. Based on the penetration probability, four UAVs are dispatched to complete the saturation attack cooperative encirclement mission. Assume the target position is (100, 100, 100) m and the speed is 30 m / s. Set the number of UAVs N = 4, and the initial positions are (-30, 30, 90) m, (0, 160, 110) m, (-10, 100, 120) m, (10, 80, 80) m respectively, and the initial speeds are 25 m / s, 24 m / s, 26 m / s, 25 m / s respectively. The three-dimensional flight trajectories of the UAV swarm are as Figure 3 shown.

[0061] ​Based on the simulation results, it can be seen that the cooperative enclosing control method for the saturation attack mission of the UAV swarm designed by the present invention can well ensure that the minimum number of UAVs complete the mission, reducing the loss of funds and materials. At the same time, according to the simulation position curve, it can be seen that the distributed cooperative enclosing controller designed by the present invention can well help the UAVs accurately estimate the speed of the target, so as to surround the target. During this process, there will be no collision between UAVs. Finally, the actual speed of the UAVs, the estimated speed of the target and the actual speed of the target tend to be consistent. In addition, the command converter can effectively convert the commands of the controller into the speed command V c , track angle command and climb angle command θ c , which also shows that the autopilot can ensure that the UAVs have good tracking performance and ensure the stability of the system.

[0062] The beneficial effects of the present invention are as follows:

[0063] The present invention designs a saturation attack control method based on UAV swarms. At the same time, aiming at the characteristics of UAVs and mission characteristics, a distributed cooperative enclosing controller is designed, and the control algorithm has the characteristics of fast convergence and anti-interference. This algorithm is a distributed algorithm and is less affected by the number of UAVs, so it has good scalability;

[0064] The present invention designs a cooperative enclosing control method under the saturation attack mission mode. Compared with other enclosing methods, the present invention does not need to design the formation in advance. The enclosing mission can be completed according to the minimum safety distance between UAVs. Due to the real-time and complexity of the mission, the method designed by the present invention is difficult to be predicted by the enemy, thus increasing the success rate of the mission. At the same time, the controller has good scalability, can ensure that a large number of UAVs complete the enclosing, and can be realized with fewer state variables (the position and speed of UAVs and the position of the target). The traditional formation controller will affect the formation quality and the success rate of the mission due to the increase in the number of UAVs resulting in the problems of computational complexity and the accuracy of formation information; the controller design is not only applicable to UAVs, but also can use a variety of mobile intelligent agents. It has good adaptability to both linear and non-linear systems.

[0065] In order to better conform to the actual situation, the present invention builds a coupled UAV model, and also has an accurate command converter, and takes into account the constraints of UAVs, such as speed limit, heading angle limit, climb angle limit, etc., to simulate the real saturation attack mission scenario based on UAV swarms.

[0066] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for cooperative encirclement control of unmanned aerial vehicles (UAVs) under a saturation attack mission, characterized in that, it includes the following steps: 1) Build a target defense system model in the saturation attack mission scenario, which includes three modules: an early warning system, air defense missiles, and electronic jamming. Design the penetration probability of the UAV swarm to ensure that at least one UAV completes the attack mission; 2) Based on the situation of a moving target with unknown speed, for the UAV model with an autopilot, design the UAV encirclement control target and the distributed cooperative encirclement controller under the saturation attack mission. Then, drive the UAVs by the command converter to achieve accurate estimation of the target speed by the UAV swarm, prevent collisions, accurately surround, and finally complete the cooperative encirclement of the target; when receiving the attack command, attack the target simultaneously with the shortest path; The design of the penetration probability of the UAV swarm in step 1) is: According to the saturation attack mission scenario, requiring at least one UAV to break through, the minimum number of UAVs dispatched is designed as: where n represents the number of target missiles; P f represents the average service probability of air defense weapons; P L represents the detection probability of the early warning system; Q a and Q e respectively represent the penetration probabilities of air defense weapons and electronic jamming; N m represents the minimum number of UAVs that successfully complete the mission; N represents the number of UAVs dispatched; The UAV model with an autopilot in step 2) is expressed as where x i (t), y i (t), h i (t) are the centroid positions of UAV i at time t; where V i (t), θ i (t) respectively represent the speed, heading angle and climb angle of UAV i at time t; V ci (t), θ ci (t) represent the corresponding speed command, heading angle command and climb angle command; τ V , τ θ respectively represent the time constants of each channel; The design of the UAV encirclement control target under the saturation attack mission in step 2) is: The distributed cooperative encirclement controller is expressed as: In the formula, p i , p j , p target Respectively represent the position of UAV i, the position of UAV j and the position of the target; u i =[u xi ,u yi ,u hi ] T represents the acceleration signal of the drone in the forward, lateral and height channels respectively; r represents any point on the encirclement formed by the drone; D represents the distance between the target and the encirclement, if and only if p target ∈co(p), it is determined that the target is surrounded; N represents the number of drones; d ij represents the distance between UAV i and UAV j; d s Indicates the safe distance between drones. The distance between drones cannot be less than the safe distance; V i (t), V target (t) represents the actual speed of UAV i, the estimated speed of the target by UAV i and the actual speed of the target, respectively; λ i , α, β, γ, and K represent weight coefficients; C i represents the set of neighbor UAVs of UAV i; f i Denote the obstacle avoidance function of UAV i; The controller in step 2) consists of three items: an attack item, a collision avoidance item, and an adaptive estimation item; The command converter in step 2) is expressed as: where u i = [u xi , u yi , u hi T represents the acceleration signals of the UAV on the three channels of forward, lateral and altitude respectively; τ V , τ θ represent the time constants of each channel respectively.​

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