Unmanned aerial vehicle elastic formation control method considering input limitation and speed limitation

Abstract

The invention discloses an unmanned aerial vehicle elastic formation control method considering input limitation and speed limitation, and the method comprises the steps: firstly, considering an elastic constraint relation between unmanned aerial vehicle formations on the basis of a dual-mass spring system, and building an unmanned aerial vehicle elastic formation dynamic model; secondly, considering input and speed limitation conditions, and designing a consistency control method using local speed information and relative speed information; and finally, a leader-following model is introduced, a distributed formation control strategy is adopted, and a leader-following controller under the condition of limited input and speed is designed, so that the follower unmanned aerial vehicle can still rapidly track the flight path of the leader under the condition of limited input and speed, and the position tracking error and the speed tracking error are finally converged to 0 consistently. According to the method, the anti-saturation capability of the unmanned aerial vehicle formation is effectively improved by establishing the dynamic model of the unmanned aerial vehicle elastic formation model influenced by collision between the unmanned aerial vehicles and limited communication data volume and considering the problems of input saturation and limited unmanned aerial vehicle speed into consistency control.

Description

Technical Field

[0001] The invention relates to a method for controlling a flexible formation of unmanned aerial vehicles (UAVs) taking input limitation and speed limitation into consideration, and belongs to the technical field of UAV formation control. Background Art

[0002] In recent years, the cooperative control of multi-UAV systems has been increasingly used in military and civilian fields, attracting great attention. At present, the design of many control algorithms is based on simplified models. In actual engineering, in addition to considering the collision avoidance between UAVs and the limited communication data volume, it is also necessary to consider the input saturation problem caused by the limited driving power of the physical device, the speed constraint problem caused by the fixed-wing UAV hovering and the motor speed limit. In these cases, a consistency controller that considers both speed and input saturation is very necessary. However, few studies have considered this issue.

[0003] At present, most of the control methods for multi-UAV system formations are mainly leader-follower method, virtual structure method and behavior-based method, and only a few studies consider the problem of avoiding collisions between UAVs. Fortunately, the elastic formation model can effectively solve the problem of avoiding collisions between UAVs. However, the unimproved elastic formation model requires a lot of communication resources, and when the number of UAV clusters increases on a large scale, the force relationship of each UAV becomes particularly complex, which may lead to a decrease in the dynamic performance and flexibility of the UAV formation. As for the research on input-constrained and speed-constrained problems, the existing literature has studied the anti-saturation problem of second-order systems more, and there are very few studies on the problem of second-order systems being simultaneously input-constrained and speed-constrained. Therefore, based on the improved elastic formation model, it is very meaningful and valuable to design a control strategy that considers input constraints and speed constraints to ensure the safe and stable operation of the UAV formation system. Summary of the invention

[0004] The technical problem to be solved by the present invention is: to provide a UAV flexible formation control method taking into account input limitation and speed limitation, by establishing a dynamic model problem in which the UAV flexible formation model is affected by inter-machine collision and limited communication data volume, and taking into account the input saturation problem and UAV speed limitation problem in the consistency control method, the anti-saturation capability of the UAV formation is effectively improved.

[0005] The present invention adopts the following technical solutions to solve the above technical problems: A method for controlling a flexible formation of unmanned aerial vehicles (UAVs) considering input constraints and speed constraints comprises the following steps: Step 1: Based on the dual-mass spring system, the elastic constraint relationship between the UAV formations is considered to establish a dynamic model of the UAV elastic formation; Step 2, simplifying the dynamic model of the UAV elastic formation established in step 1 into a second-order system equation; Step 3: For the second-order system equation of the UAV formation, a distributed consistency controller using local speed information and relative speed information is designed to achieve consistency of speed and input constraints; Step 4, introduce a virtual leader UAV, take all the UAVs in the UAV formation as follower UAVs, and design a leader-follower controller under input and speed constraints, so that the follower UAVs can follow the flight path of the given virtual leader UAV under input and speed constraints.

[0006] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects: 1. The UAV elastic formation model established by the present invention defines that there is an elastic constraint between each UAV and its neighboring UAVs. When the distance between the UAVs is too close, the elastic constraint repulsion will be greater, which can effectively avoid the problem of mutual collision between UAVs.

[0007] 2. The present invention uses a directed graph communication topology and a leader-follower system model. It does not require all drones to communicate with each other. Selective communication can be performed according to task requirements, thereby reducing communication burden and resource consumption and optimizing bandwidth usage. In addition, through the directed graph communication structure, task allocation can be achieved more effectively.

[0008] 3. The present invention considers a consistency controller based on input constraint and speed constraint, which does not require global graph information such as the Laplace matrix of a general directed communication graph, thereby improving the robustness of the controller. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a flow chart of a method for controlling a flexible formation of unmanned aerial vehicles taking into account input constraints and speed constraints of the present invention; Figure 2 is a communication topology diagram of the UAV formation system according to an embodiment of the present invention; Figure 3 is a schematic diagram of a three-dimensional flight trajectory of a UAV formation according to an embodiment of the present invention; Figure 4 It is the drone formation follower drone of the embodiment of the present invention Position tracking error curve of the channel; Figure 5 It is the drone formation follower drone of the embodiment of the present invention Position tracking error curve of the channel; Figure 6 It is the drone formation follower drone of the embodiment of the present invention Position tracking error curve of the channel; Figure 7 It is the drone formation follower drone of the embodiment of the present invention The velocity tracking error curve of the channel; Figure 8 It is the drone formation follower drone of the embodiment of the present invention The velocity tracking error curve of the channel; Fig. 9 It is the drone formation follower drone of the embodiment of the present invention The velocity tracking error curve of the channel; Fig.10 It is the drone formation follower drone of the embodiment of the present invention Speed ​​response curves of the three channels; Fig.11 It is the drone formation follower drone of the embodiment of the present invention Control input response curves for the three channels. DETAILED DESCRIPTION

[0010] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0011] like Figure 1 As shown, the present invention proposes a method for controlling a flexible formation of unmanned aerial vehicles taking into account input limitation and speed limitation, comprising the following steps: Step 1: Based on the dual-mass spring system, the elastic constraint relationship between UAV formations is considered and the dynamic model of the UAV elastic formation is established.

[0012] Assume that the research is conducted by The communication network of a multi-UAV system consisting of 100 UAVs is abstracted into a directed graph. To indicate that express A collection of nodes; Representation Node and nodes The set of edges connecting Represents a slave node To Node Figure 1. The adjacency matrix of , , and when When ,but .node The neighbor set of .node The degree is the number of neighbors ,use Represented, the degree matrix is ​​defined as: .

[0013] Considering the elastic constraint relationship between drone formations, the invisible constraint that defines the relative position between two drones in the formation is called a formation elastic constraint, also known as a formation spring. Each end of the drone formation elastic constraint is connected to a drone, and the formation elastic constraint force is related to the relative distance between the two drones. When the distance exceeds the formation, the elastic constraint behaves as an attractive force, and when the distance is less than the formation, the elastic constraint behaves as a repulsive force. Represents the stiffness of the UAV formation spring, in units of , which is also expressed as the strength of the elastic constraint of the UAV. The dynamic model of the elastic formation of UAVs is established: , in, Indicates The quality of the drone, Indicates The location information of the drone, , Indicates The stiffness matrix of the elastic constraint of the UAV, and They represent the adjacency matrix and degree matrix of the UAV formation communication network respectively, is the expected formation distance between UAVs, For control input.

[0014] Step 2: Based on step 1, the dynamic model of the UAV elastic formation is further simplified into the form of a second-order system equation.

[0015] Based on step 1, the dynamic model of the UAV elastic formation and Combining the items gives: , in, Indicates The drone is relatively The formation position error of the UAVs.

[0016] Further simplifying the dynamic model of the UAV elastic formation, we get the following model: , Based on step 1 and the above description, the dynamic model of each UAV in the UAV elastic formation is decomposed into a second-order system equation: , in, Indicates The speed information of the drone.

[0017] Step 3: Considering the input-constrained and speed-constrained cases, design a consistent control method using local speed information and relative speed information.

[0018] For the second-order system equation of the UAV formation described in step 2, a distributed consistency controller using local velocity information and relative velocity information is proposed to achieve consistency of velocity and input constraints. Assign a constant formation vector ,make Indicates drone and drones The desired relative position in the formation. , When satisfied, formation control is achieved.

[0019] The original control input for designing the UAV formation system is: , in, , , , , , is a symbolic function, so we can get .

[0020] Based on step 1 and the above description, the control input can be rewritten as: , in, .

[0021] In order to limit the range of control input, the elastic force in step 1 is limited, and the second-order system equation is rewritten as: , Let the elastic coefficient matrix , then the actual control input of the UAV is: , in, .

[0022] Step 4: Introduce the leader-follower model and design a leader-follower controller under input and speed constraints, so that the follower UAV can still follow the flight path of the given leader UAV under input and speed constraints, and the position tracking error and speed tracking error eventually converge to 0.

[0023] For the second-order system equation of the UAV formation in step 3, the position and speed of the UAV cannot be directly controlled, so a leader UAV needs to be introduced to guide the UAV to the desired trajectory. The leader UAV only needs to exchange information with a limited number of UAVs in the communication network. Definition: UAVs other than the leader are called followers, and the leader UAV is represented as node 0.

[0024] The leader also needs to satisfy the speed constraint and input constraint. The leader dynamics model is defined as follows: , in, , Can be freely designed to specify the desired trajectory. and It can be seen that both the speed constraint and the input constraint of the leader can be satisfied.

[0025] According to the leader dynamics model and the second-order system equation of the UAV formation in step 2, the leader-follower controller is designed as follows: , in, , .

[0026] In practical applications, discontinuous terms This will cause chattering. To reduce the chattering of the control input, the sign function in the leader-follower controller can be replaced by the following continuous saturation function : , in, .

[0027] In order to test the collaborative control performance of the flexible formation of unmanned aerial vehicles designed in the present invention, a simulation experiment was designed according to the model and controller algorithm of the present invention. A simulation environment was built on MATLAB R2023a / Simulink on a computer with CPU: Intel(R) Core(TM) i5 10500 and 16GB of RAM for simulation.

[0028] The leader-follower model consists of 1 leader drone and 5 follower drones. 0 is the leader, 1, 2, 3, 4, 5 are followers, leader 0 only communicates with follower 1, and assuming that the connectivity graph is directed, the communication topology of the drone elastic formation system is as follows: Figure 2 As shown, according to Figure 2 From this information, we can get some related matrices: Adjacency Matrix , the degree matrix , the Laplacian matrix ; The position of the follower relative to the leader is set to , , , , , the leader’s desired trajectory is set as: The parameter selection of the UAV elastic formation model is shown in Table 1, and the simulation parameters of the controller are shown in Table 2.

[0029] Table 1 UAV formation model parameters

[0030] Table 2 Controller parameters

[0031] The present invention provides a flexible formation control method for unmanned aerial vehicles taking into account input limitation and speed limitation. Figure 3 This is a rendering of the three-dimensional flight trajectory of a UAV formation. It can be seen that the flight trajectory of the control method proposed in the present invention can converge quickly and has high tracking accuracy. Figures 4 to 6 The drone formation follower drone of the present invention The trajectory tracking error curves of the three channels show The channel trajectory tracking error converged to within 0.2 at 5.27s. The channel trajectory tracking error converged to within 0.2 at 8.45s. The trajectory tracking error of the channel converged to within 0.2 at 0.91s. Figures 7 to 9 The drone formation follower drone of the present invention The speed tracking error curves of the three channels show The velocity tracking error of the channel converged to within 0.2 at 6.30s. The velocity tracking error of the channel converged to within 0.2 at 9.40s. The velocity tracking error of the channel converged to within 0.2 at 0.58s. Fig.10 The drone formation follower drone of the present invention The speed response curves of the three channels show that the speed of the follower drone is within the constraint range allowed by the amplitude. Fig.11 The drone formation follower drone of the present invention The control input response curves of the three channels show that the amplitude of the control input signal is within the allowable constraint range.

[0032] Based on the same inventive concept, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the aforementioned method for controlling a flexible formation of unmanned aerial vehicles taking into account input constraints and speed constraints are implemented.

[0033] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the aforementioned method for controlling a flexible formation of unmanned aerial vehicles taking into account input constraints and speed constraints.

[0034] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0035] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. 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.

[0036] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0037] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0038] The above embodiments are only for illustrating the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for controlling a flexible formation of unmanned aerial vehicles considering input constraints and speed constraints, characterized in that: The steps include: Step 1: Based on the dual-mass spring system, the elastic constraint relationship between the UAV formations is considered to establish a dynamic model of the UAV elastic formation; Step 2, simplifying the dynamic model of the UAV elastic formation established in step 1 into a second-order system equation; Step 3: For the second-order system equation of the UAV formation, a distributed consistency controller using local speed information and relative speed information is designed to achieve consistency of speed and input constraints; Step 4, introduce a virtual leader UAV, take all the UAVs in the UAV formation as follower UAVs, and design a leader-follower controller under input and speed constraints, so that the follower UAVs can follow the flight path of the given virtual leader UAV under input and speed constraints.

2. The method for controlling a flexible formation of unmanned aerial vehicles considering input limitation and speed limitation according to claim 1, characterized in that: The specific process of step 1 is as follows: Setting up a drone formation includes drone, using a directed graph represents the communication network of the UAV formation, where express A collection of nodes, Representation Node and nodes The set of edges connecting ; The adjacency matrix of , , and when When ,but ,side Represents a slave node To Node Information flow of The degree matrix of , , Representation Node degree; Considering the elastic constraint relationship between the UAV formations, the elastic constraint force of the formation is related to the relative distance between the two UAVs. When the distance exceeds the formation, the elastic constraint behaves as gravity, and when the distance is less than the formation, the elastic constraint behaves as repulsion. The dynamic model of the UAV elastic formation is established as follows: ， in, Indicates The quality of the drone, is the identity matrix, Indicates The location information of the drone, , Indicates The stiffness matrix of the elastic constraint of the UAV, and They represent the adjacency matrix and degree matrix of the UAV formation communication network respectively, is the expected formation distance between UAVs, , Respectively Frame and The expected position information of the drone, is the control input, .

3. The method for controlling a flexible formation of unmanned aerial vehicles considering input limitation and speed limitation according to claim 2, characterized in that: The specific process of step 2 is as follows: The dynamic model of the UAV elastic formation and Combining the items yields: ， in, Indicates The drone is relatively The formation position error of the UAVs, , Indicates The location information of the drone; The combined model is simplified to obtain the dynamic model of each drone in the UAV elastic formation: ， The dynamic model of each drone in the UAV elastic formation is decomposed into a second-order system equation: ， in, Indicates The speed information of the drone.

4. The method for controlling a flexible formation of unmanned aerial vehicles considering input limitation and speed limitation according to claim 3, characterized in that: In step 3, the distributed consistency controller formula using local speed information and relative speed information is as follows: ， in, , , , , , , are the minimum and maximum speed of the drone, respectively. are all constants greater than 0. are all constants greater than 0. Indicates The speed information of the drone, Indicates A distributed consensus controller for drones.

5. The method for controlling a flexible formation of unmanned aerial vehicles considering input limitation and speed limitation according to claim 4, characterized in that: In step 4, the leader-follower controller formula under input and speed constraints is as follows: ， in, Indicates The leader-follower controller of the UAV, subscript 0 represents the virtual leader UAV; make ,have ,in, is the saturation function, , sgn is the sign function.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the method for controlling a flexible formation of unmanned aerial vehicles taking into account input constraints and speed constraints as described in any one of claims 1 to 5 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for controlling a flexible formation of unmanned aerial vehicles taking into account input constraints and speed constraints as described in any one of claims 1 to 5 are implemented.

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