Fault-tolerant formation control method for unmanned aerial vehicle group monitoring

Abstract

The invention relates to the technical field of unmanned aerial vehicles, in particular to a fault-tolerant formation control method for unmanned aerial vehicle group monitoring, and the method comprises the following steps: S1, an operator issues a target monitoring instruction to a leader unmanned aerial vehicle according to a demand; s2, the leader unmanned aerial vehicle performs initialization operation according to the target position and the number of surviving unmanned aerial vehicles, and the leader unmanned aerial vehicle establishes a communication adjacency matrix with the sub unmanned aerial vehicles and distributes positions; s3, the leader unmanned aerial vehicle monitors the system state in real time and keeps the system state; s4, once the sub-unmanned aerial vehicle judges that the communication connection with the leader unmanned aerial vehicle is lost, the sub-unmanned aerial vehicle is lowered until the sub-unmanned aerial vehicle lands; and S5, the leader unmanned aerial vehicle executes the S1 again. When communication between unmanned aerial vehicle formations breaks down, the unmanned aerial vehicle formations need to be changed, it is guaranteed that the unmanned aerial vehicles can monitor targets at all angles, and in the formation changing process, a task allocation algorithm is used, and it is guaranteed that the sum of the motion paths of all the unmanned aerial vehicles is minimum.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and in particular to a fault-tolerant formation control method for monitoring a group of unmanned aerial vehicles. Background Art

[0002] A drone formation refers to a flight configuration in which a group of drones form an orderly formation through coordination and collaboration during flight and jointly perform a specific task. This formation is usually achieved through advanced autonomous flight control systems and communication technologies. The key features of drone formations include: collaborative flight, task division, autonomy, communication technology, etc. Drone formations are widely used in military, civil and scientific research fields, which can improve mission execution efficiency and reduce costs. At the same time, they can also cope with some complex tasks that require large-scale collaborative operations. The existing drone formation tasks are that although real-time detection can be performed, the vacancies caused by faulty drones cannot be replaced, and it is impossible to ensure that the movement path of the drones is minimized when the drone formation changes. Summary of the invention

[0003] The purpose of the present invention is to provide a fault-tolerant formation control method for monitoring a swarm of drones to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A fault-tolerant formation control method for monitoring a swarm of unmanned aerial vehicles comprises the following steps:

[0006] S1. The operator issues target monitoring instructions to the leader UAV according to the needs;

[0007] S2, the leader drone performs initialization operations according to the target location and the number of surviving drones, and the leader drone establishes a communication adjacency matrix with the sub-drones and assigns positions;

[0008] S3, the leading drone monitors the system status in real time and maintains the system status;

[0009] S4. Once the slave drone determines that it has lost communication with the leader drone, it will lower its altitude until it lands;

[0010] S5. Instruct the drone to re-execute S1.

[0011] Preferably, S2 comprises the following specific steps:

[0012] 1) The leader drone uses the task allocation algorithm to assign positions to the sub-drones based on the number of surviving sub-drones;

[0013] 2) The leader UAV establishes a communication adjacency matrix based on the assigned positions of the child UAVs.

[0014] Preferably, the task allocation algorithm includes the following specific steps:

[0015] 1>、Subtract the smallest element from each row of H0

[0016] 2>, H0 minus the smallest element in each column

[0017] 3>, use the smallest horizontal or vertical line to cover all the 0s in H0;

[0018] 4>, if the number of lines is equal to the number of rows of H0 is equal to j, then the optimal allocation is found and the algorithm ends, otherwise go to 5>;

[0019] 5>. Find the smallest element not covered by the line, subtract this element from each row not covered by the line, add this element to each column covered by the line, and return to 3>.

[0020] Preferably, S3 comprises the following specific steps:

[0021] 1) The leading drone monitors the communication connection strength of each drone in real time;

[0022] 2) According to the communication connection strength and feedback information of the sub-UAVs, the position and attitude stability of the entire formation are controlled in real time;

[0023] 3) The leading UAV evaluates the communication connection strength of each sub-UAV in real time. Once the communication strength of a UAV is lower than the expected value, it is judged to be uncontrollable and the communication connection with it is disconnected.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] When communication between drone formations fails, the present invention needs to change the drone formation to ensure that the drones can monitor the target at all angles. During the formation change process, a task allocation algorithm is used to ensure that the sum of the motion paths of all drones is minimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the process of the present invention;

[0027] Figure 2 This is a schematic diagram of the positions of drones in the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0030] In the description of this patent, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, it can be fixedly connected or set, or it can be detachably connected or set, or connected or set in one piece. For ordinary technicians in this field, the specific meanings of the above terms in this patent can be understood according to specific circumstances.

[0031] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "several" is two or more, unless otherwise clearly and specifically defined.

[0032] See also Figure 1 As shown, a technical solution provided by the present invention is:

[0033] A fault-tolerant formation control method for monitoring a swarm of unmanned aerial vehicles comprises the following steps:

[0034] S1. The operator issues target monitoring instructions to the leader UAV according to the needs;

[0035] S2, the leader drone performs initialization operations according to the target location and the number of surviving drones, and the leader drone establishes a communication adjacency matrix with the sub-drones and assigns positions;

[0036] The specific steps include:

[0037] 1) The leader drone uses the task allocation algorithm to assign positions to the sub-drones according to the number of surviving sub-drones; if there are N surviving drones, the interval angle between each drone is θ, the distance is R, the target position is x0, the target speed is v0, and the target height is p0.

[0038] The i-th target position is

[0039] θ=360 / N

[0040] p i =x0+[Rcos(iθ),Rsin(iθ)] T When i=1,2,…,N and the number of drones N=6, the allocation positions are as follows Figure 2 As shown;

[0041] The following is the task allocation algorithm, which generates a cost matrix H0 based on the surviving drones and the target locations:

[0042] H0=(h 0ij ) i×j

[0043] The number of rows i of the matrix H0 is the number of surviving drones, and the number of columns j is the number of allocated target locations. i=j at all times, and each element of the matrix is ​​the cost required for drone i to fly to location j.

[0044] The task allocation algorithm includes the following specific steps:

[0045] 1>, subtract the smallest element from each row of H0;

[0046] 2>, subtract the smallest element from each column of H0;

[0047] 3>, use the smallest horizontal or vertical line to cover all the 0s in H0;

[0048] 4>, if the number of lines is equal to the number of rows of H0 is equal to j, then the optimal allocation is found and the algorithm ends, otherwise go to 5>;

[0049] 5>. Find the smallest element not covered by the line, subtract this element from each row not covered by the line, add this element to each column covered by the line, and return to 3>.

[0050] Finally, we obtain the solution matrix H1 of the algorithm. Each drone sets the element with the smallest value in its row as its target position, and the total cost required for all drones to fly is the lowest.

[0051] 2) The leader UAV establishes a communication adjacency matrix based on the assigned positions of the child UAVs.

[0052] The leader drone establishes the adjacency matrix M according to the network topology between the sub-drones.

[0053] M=(m ij )N×N

[0054]

[0055] Where s ij is the communication frequency between the i-th aircraft and the j-th aircraft, h is the expected communication frequency, m ij is the communication connection strength between the i-th aircraft and the j-th aircraft (0≤m ij ≤1), and because it is an adjacency matrix, when i=j, m ij =0.

[0056] S3, the leading drone monitors the system status in real time and maintains the system status;

[0057] S4. Once the slave drone determines that it has lost communication with the leader drone, it will lower its altitude until it lands;

[0058] The specific steps include:

[0059] 1) The leading drone monitors the communication connection strength of each drone in real time;

[0060] 2) According to the communication connection strength and feedback information of the sub-UAVs, the position and attitude stability of the entire formation are controlled in real time;

[0061] 3) The leading UAV evaluates the communication connection strength of each sub-UAV in real time. Once the communication strength of a UAV is lower than the expected value, it is judged to be uncontrollable and the communication connection with it is disconnected.

[0062] The specific real-time methods of 2) are as follows:

[0063] First, establish the OXY two-dimensional position system model of the UAV

[0064]

[0065] Where: x i 、v i 、u i are the position signal, speed signal, and control input of the i-th UAV respectively.

[0066] Secondly, establish the Z-axis height model of the drone

[0067]

[0068] Where: p i ,q i 、u ziare the height signal, speed signal, and control input of the i-th UAV respectively.

[0069] Define signal strength C:

[0070] C=[c1,c2,c3,c4,c5,c6] T =MD

[0071] D = [1, 1, 1, 1, 1] T

[0072] Define 2D position error variables

[0073] e xi =x i -ρ xi -x0

[0074] e vi =v i -ρ vi -v0

[0075] Where: xi ∈R 2 and ρ vi ∈R 2 Represents the known formation configuration vector

[0076] The control input signals for the two-dimensional position are as follows:

[0077]

[0078] Where: k 0i >0 is the control gain.

[0079] Here, the control signals sent by all drones connected to the sub-drone are controlled by a coefficient, that is, the higher the communication connection strength between the drone and the sub-drone, the higher the weight of the control signal it sends.

[0080] The control input of the Z-axis height model is:

[0081] u zi =-k 1i (p0-p i )

[0082] Where: k 1i >0 is the control gain, p0 is the desired height, p i is the current altitude.

[0083] The specific real-time methods of 3) are as follows:

[0084]

[0085] Where: j iis the communication connection strength of the i-th aircraft, tanh(x) is the activation function, when the value is greater than a certain threshold a, it returns 1, otherwise the returned number decays rapidly as x decreases, so when j i When ≥1, it means that the communication line of the i-th drone is healthy, otherwise the communication is disconnected. The expression of tanh(x) function is as follows:

[0086]

[0087] When a j i When it is less than 1, the landing operation is performed.

[0088] S5. Instruct the drone to re-execute S1.

[0089] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A fault-tolerant formation control method for drone group monitoring, characterized in that: The following steps are involved: S1. The operator issues target monitoring instructions to the leader UAV according to the needs; S2, the leader drone performs initialization operations according to the target location and the number of surviving drones, and the leader drone establishes a communication adjacency matrix with the sub-drones and assigns positions; S3, the leading drone monitors the system status in real time and maintains the system status; S4. Once the slave drone determines that it has lost communication with the leader drone, it will lower its altitude until it lands; S5. Lead the drone to re-execute S1.

2. The fault-tolerant formation control method for monitoring a swarm of drones according to claim 1, characterized in that: The S2 comprises the following specific steps: 1) The leader drone uses the task allocation algorithm to assign positions to the sub-drones based on the number of surviving sub-drones; 2) The leader UAV establishes a communication adjacency matrix based on the assigned positions of the child UAVs.

3. The fault-tolerant formation control method for monitoring a swarm of drones according to claim 2 is characterized in that: The task allocation algorithm includes the following specific steps: 1>, subtract the smallest element from each row of H0; 2>, subtract the smallest element from each column of H0; 3>, use the smallest horizontal or vertical line to cover all the 0s in H0; 4>, if the number of lines is equal to the number of rows of H0 is equal to j, then the optimal allocation is found and the algorithm ends, otherwise go to 5>; 5>. Find the smallest element not covered by the line, subtract this element from each row not covered by the line, add this element to each column covered by the line, and return to 3>.

4. The fault-tolerant formation control method for monitoring a swarm of drones according to claim 1, characterized in that: The S3 includes the following specific steps: 1) The leading drone monitors the communication connection strength of each drone in real time; 2) According to the communication connection strength and feedback information of the sub-UAVs, the position and attitude stability of the entire formation are controlled in real time; 3) The leading UAV evaluates the communication connection strength of each sub-UAV in real time. Once the communication strength of a UAV is lower than the expected value, it is judged to be uncontrollable and the communication connection with it is disconnected.

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