A method and system for autonomous formation control based on a bounded bifurcation potential field

Abstract

This invention discloses a formation autonomous control method and system based on a bounded forked bifurcation potential energy field, belonging to the field of unmanned swarm formation flight control. First, an artificial potential energy field control function for the relative motion velocity of the unmanned swarm is established. Then, the real-time relative positions of swarm nodes to the swarm formation configuration reference point, and the relative positions of swarm nodes to other swarm nodes are input into the artificial potential energy field control function to obtain the relative motion velocity commands of each swarm node. Subsequently, a tracking control law is adopted to determine the relative motion velocity control input of each swarm node, ensuring that the actual relative motion velocity of the swarm nodes tracks the relative motion velocity commands of the upper nodes without error, thus realizing the swarm configuration. This invention does not require planning the motion path of each member; by introducing an artificial potential energy field, the swarm nodes move to the desired position under the guidance of the negative gradient of the potential energy field.

Description

Technical Field

[0001] This invention relates to the field of unmanned swarm formation flight control, and in particular to a method and system for autonomous formation control based on a bounded forked bifurcation potential energy field. Background Technology

[0002] Unmanned swarm formation flight is a common application scenario for swarms. Conventional swarm formation configuration control methods are centralized control rather than member-independent autonomous control. This means that the motion control of swarm members requires receiving external commands or information to maintain the configuration or achieve reconfiguration. When the swarm formation configuration changes, the motion path of each member needs to be planned. As the number of members increases, the system maintenance cost increases significantly; due to the large number of members, the planning and control algorithms become extremely complex, the computational load increases dramatically, and they may even become impossible to implement. Summary of the Invention

[0003] The purpose of this invention is to provide a formation autonomous control method and system based on a bounded fork-shaped bifurcation potential energy field. By introducing an artificial potential energy field, cluster nodes can move to the desired position under the guidance of the negative gradient of the potential energy field.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] An autonomous formation control method based on a bounded bifurcation potential field includes:

[0006] An artificial potential energy field control function is established for the relative motion velocity of the unmanned swarm; the artificial potential energy field control function includes the gradient function of the attractive potential energy field function and the gradient function of the repulsive potential energy field function;

[0007] Construct the gradient function of the attraction potential energy field function; the attraction potential energy field function and the gradient function of the attraction potential energy field function have a forked bifurcation characteristic;

[0008] The gradient function of the attraction potential energy field function is substituted into the artificial potential energy field control function to obtain the cluster node relative motion speed command function; the cluster node relative motion speed command determined by the cluster node relative motion speed command function is bounded.

[0009] Real-time acquisition of the relative position of each cluster node in the cluster system with respect to the cluster formation reference point, its relative position with respect to other cluster nodes, and its movement speed in the relative position coordinate system;

[0010] Based on the relative positions of each cluster node and the cluster formation configuration reference point, the relative positions of each cluster node and other cluster nodes, and the formation plane configuration to be switched, the relative motion speed command of each cluster node is obtained using the cluster node relative motion speed command function.

[0011] Based on the relative motion speed commands and motion speeds of each cluster node, the relative motion speed control input of each cluster node is determined using a tracking control law.

[0012] The cluster nodes are controlled according to the relative motion speed control input, so that the actual relative motion speed of the cluster nodes tracks the relative motion speed command of the upper node without error, thus realizing the cluster configuration.

[0013] Optionally, the artificial potential field control function for establishing the relative motion velocity of the unmanned swarm specifically includes:

[0014] Establish the artificial potential field function as U i =U G (r i )+U R (r ij In the formula, U i U is the artificial potential field function. G U is the attraction potential energy function. R Let r be the repulsive potential energy field function. i Let r be the relative position vector between cluster node i and the cluster formation reference point. ij Let be the relative position vector between cluster node i and cluster node j;

[0015] Based on the aforementioned artificial potential field function, the artificial potential field control function for the relative motion velocity of the cluster is determined as follows: In the formula, v di The relative motion speed command for cluster node i. Let be the gradient function of the attraction potential energy field function of cluster node i. Let be the gradient function of the repulsive potential energy field function of cluster node i.

[0016] Optionally, the attractive potential energy field function is: In the formula, C1 and C2 are the first and second amplitude scale parameters, respectively, C3 is the length scale function, r is the reference distance parameter, and μ is the formation configuration control switching parameter;

[0017] The gradient function of the attraction potential energy field function is:

[0018] Optionally, the relative motion speed command function of the cluster nodes is:

[0019]

[0020] Optionally, the attraction potential energy field function and its gradient function have a forked bifurcation characteristic:

[0021] Given the first amplitude scale parameter C1, the second amplitude scale parameter C2, the length scale parameter C3, and the reference distance parameter r: if the formation switching parameter μ is less than the critical value and the reference distance parameter r is greater than zero, then only one cluster node position value is possible. At this point, the formation planar configuration is a circle; if the formation configuration switching parameter μ is greater than the critical value, then there exist two different cluster node position values ​​such that... At this point, the formation planar configuration is a concentric ring; if the formation configuration switching parameter μ is less than the critical value and the reference distance parameter r is equal to zero, then the formation planar configuration is a disk;

[0022] When given the formation configuration switching parameter μ, the formation configuration can be enlarged or reduced by adjusting the first amplitude scale parameter C1, the second amplitude scale parameter C2, the length scale parameter C3, and the reference distance parameter r.

[0023] Optionally, the boundedness of the relative motion speed command of the cluster nodes is as follows:

[0024] Given the first amplitude scale parameter C1, the second amplitude scale parameter C2, the length scale parameter C3, and the reference distance parameter r, the relative motion velocity command of the cluster nodes has a finite magnitude, regardless of how the relative position vector values ​​of the cluster nodes and the cluster formation configuration reference points change.

[0025] Optionally, the tracking control law is as follows:

[0026]

[0027]

[0028] S = v di -v i

[0029] In the formula, u is the relative motion speed control input of the cluster nodes, C(r,v) is the relative motion dynamics function of the cluster nodes, S is the relative motion speed tracking error of the cluster nodes, sof(S,φ) is the softening function, ε is the softening coefficient, and k, γ, and φ are the first, second, and third control parameters, respectively. For intermediate functions, It is the first derivative of the intermediate function.

[0030] Optionally, it also includes:

[0031] When a cluster node in the cluster system fails and cannot perform motion control, the relative position vector related to the failed cluster node is deleted from the repulsive potential energy field function of the artificial potential energy field control function, thereby realizing the control update of the cluster system.

[0032] An autonomous formation control system based on a bounded bifurcation potential field includes:

[0033] An artificial potential energy field control function establishment module is used to establish an artificial potential energy field control function for the relative motion velocity of an unmanned swarm; the artificial potential energy field control function includes the gradient function of the attractive potential energy field function and the gradient function of the repulsive potential energy field function;

[0034] The gradient function construction module is used to construct the gradient function of the attractive potential energy field function; the attractive potential energy field function and the gradient function of the attractive potential energy field function have a forked bifurcation characteristic;

[0035] The velocity command function acquisition module is used to input the gradient function of the attraction potential energy field function into the artificial potential energy field control function to obtain the relative motion velocity command function of the cluster nodes; the relative motion velocity command of the cluster nodes determined by the relative motion velocity command function of the cluster nodes is bounded.

[0036] The real-time module is used to obtain the relative position of each cluster node in the cluster system with respect to the cluster formation reference point, the relative position with respect to other cluster nodes, and the movement speed in real time in the relative position coordinate system.

[0037] The speed command acquisition module is used to obtain the relative motion speed command of each cluster node based on the relative position of each cluster node to the cluster formation configuration reference point, the relative position of each cluster node to other cluster nodes, and the formation plane configuration to be switched, using the cluster node relative motion speed command function.

[0038] The speed control input determination module is used to determine the relative motion speed control input of each cluster node based on the relative motion speed command and the motion speed of each cluster node, using a tracking control law.

[0039] The control module is used to control each cluster node according to the relative motion speed control input, so that the actual relative motion speed of the cluster nodes tracks the relative motion speed command of the upper node without error, thereby realizing the cluster configuration.

[0040] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0041] This invention discloses a formation autonomous control method and system based on a bounded fork-shaped bifurcation potential energy field. First, an artificial potential energy field control function is established for the relative motion velocity of the unmanned swarm. Then, the real-time relative positions of swarm nodes to the swarm formation configuration reference point, and the relative positions of swarm nodes to other swarm nodes, are input into the artificial potential energy field control function to obtain the relative motion velocity commands for each swarm node. Subsequently, a tracking control law is adopted to determine the relative motion velocity control input for each swarm node, ensuring that the actual relative motion velocity of the swarm node tracks the relative motion velocity commands of the preceding nodes without error, thus achieving the swarm configuration. This invention eliminates the need to plan the motion path of each member; by introducing an artificial potential energy field, the swarm nodes move to the desired position under the guidance of the negative gradient of the potential energy field. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart illustrating an autonomous formation control method based on a bounded fork-shaped bifurcation potential field, provided as an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram illustrating the equilibrium state change of the gradient function of the attraction potential energy field of a bounded fork-shaped bifurcation, provided in an embodiment of the present invention.

[0045] Figure 3 A three-dimensional schematic diagram of the gravitational potential energy field provided for an embodiment of the present invention when C1=C2=C3=1, r=3, μ<critical value;

[0046] Figure 4 This is a schematic diagram of the planar change of the gravitational potential energy field when C1=C2=C3=1, r=3, μ<critical value, provided for an embodiment of the present invention.

[0047] Figure 5 A schematic diagram illustrating the gradient function change of the gravitational potential energy field when C1=C2=C3=1, r=3, μ<critical value, provided for an embodiment of the present invention;

[0048] Figure 6 A three-dimensional schematic diagram of the gravitational potential energy field provided for an embodiment of the present invention when C1=C2=C3=1, r=3, μ>critical value;

[0049] Figure 7 This is a schematic diagram of the planar change of the gravitational potential energy field when C1=C2=C3=1, r=3, μ>critical value, provided for an embodiment of the present invention.

[0050] Figure 8 This is a schematic diagram showing the gradient function change of the gravitational potential energy field when C1=C2=C3=1, r=3, μ>critical value, provided for an embodiment of the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] The purpose of this invention is to provide a formation autonomous control method and system based on a bounded fork-shaped bifurcation potential energy field. By introducing an artificial potential energy field, cluster nodes can move to the desired position under the guidance of the negative gradient of the potential energy field.

[0053] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] For a system without external forces defined in a potential energy field, the system will move along the negative gradient direction of the potential energy field. This invention provides an autonomous formation control method based on a bounded fork-shaped bifurcation potential energy field, such as... Figure 1 As shown, it includes:

[0055] Step S1: Establish an artificial potential energy field control function for the relative motion velocity of the unmanned swarm; the artificial potential energy field control function includes the gradient function of the attractive potential energy field function and the gradient function of the repulsive potential energy field function.

[0056] Under the guidance of a virtual artificial potential field, the desired motion dynamics of the cluster nodes (the desired relative motion velocity of the cluster nodes) can be described as follows:

[0057]

[0058] r i It is the relative position vector of the nodes, v di It is the desired movement speed of the node (that is, the node movement speed command). This is the gradient of the artificial potential field function to be designed. The desired velocity guides the nodes towards a stable formation position. When the desired velocity of a node is zero (v... di =0), the node position no longer changes ( r i(Maintaining constant values), nodes reach their stable positions, forming a cluster formation. When the actual movement speed of a node can track its expected speed without error, the node can reach its stable position and form a formation configuration.

[0059] The artificial potential field function is a scalar function of the cluster node position vectors, designed as two parts:

[0060] U i =U G (r i )+U R (r ij )

[0061] function The repulsive potential energy field function represents the avoidance behavior. A standard Morse potential function is sufficient. When the distance between nodes is less than the safe distance, the repulsive repulsion velocity increases, preventing collisions during node movement and ensuring uniform distribution of cluster nodes within the formation. When the distance between nodes is larger... Approaching zero. Function U i G Let U be the attraction potential energy field function, which determines the aggregation behavior of the cluster nodes, driving each node to move towards the desired location and form a formation configuration. G The shape of the cluster formation is determined, which forms the core function to be designed.

[0062] The cluster nodes move in the desired velocity field determined by the negative gradient of the artificial potential field function. The desired motion dynamics of the cluster nodes can be described as follows:

[0063]

[0064] The gradient function represents the attractive potential energy field function. This represents the gradient function of the repulsive potential energy field function. Since the nodes separate from each other when the cluster forms a stable configuration, both the repulsive potential energy field function and its gradient are close to zero. Therefore, the cluster configuration depends on the attractive potential energy field function.

[0065] Step S2: Construct the gradient function of the attraction potential energy field function; the attraction potential energy field function and the gradient function of the attraction potential energy field function have a forked bifurcation characteristic.

[0066] Design of the attraction potential field function and its gradient for bounded bifurcation

[0067]

[0068] Where C1 and C2 are the attraction potential energy field amplitude scale parameters, C3 is the length scale function, r is the reference distance parameter, and μ is the formation configuration control switching parameter.

[0069] The gradient function of the attractive potential energy field function is as follows:

[0070]

[0071] The proposed potential energy field function and its gradient function exhibit a forked bifurcation characteristic: given amplitude scale parameters, length scale parameters, and a reference distance parameter, when the formation switching parameter μ is less than a critical value and the reference distance parameter is greater than zero, there is only one unique node position r. i The value makes At this point, the formation planar configuration is a circle. When the formation configuration switching parameter μ is greater than the critical value, there are two distinct node positions r. i The value makes At this point, the formation planar configuration is a concentric ring. When the formation configuration switching parameter is less than the critical value and the reference distance parameter is equal to zero, the formation planar configuration becomes a disk.

[0072] Given a fixed amplitude scale parameter, length scale parameter, and reference distance parameter, switching the formation configuration can be achieved simply by adjusting the configuration switching parameter μ. Conversely, given the configuration switching parameter μ, adjusting the amplitude scale parameter, length scale parameter, and reference distance parameter can enlarge or reduce the formation configuration.

[0073] The equilibrium state change of the gradient function of the attraction potential energy field of a bounded fork-shaped bifurcation is as follows: Figure 2 As shown, r eq The node's equilibrium position.

[0074] When C1=C2=C3=1, r=3, and μ<critical value, the three-dimensional gravitational potential energy field is as follows: Figure 3 As shown, the gravitational potential energy field of the plane changes as follows: Figure 4 As shown, the gradient function of the gravitational potential energy field changes as follows: Figure 5 As shown. Figure 3 In this context, "One Stable State" represents a stable state.

[0075] When C1=C2=C3=1, r=3, and μ>critical value, the three-dimensional gravitational potential energy field is as follows: Figure 6 As shown, the gravitational potential energy field of the plane changes as follows: Figure 7 As shown, the gradient function of the gravitational potential energy field changes as follows: Figure 8 As shown. Figure 6 In this context, "Two Stable States" represents two stable states, and "One Unstable State" represents one unstable state. Figure 4 , Figure 5 , Figure 7 and Figure 8 x-coordinate |ri | represents the relative position scalar of cluster node i and the cluster formation configuration reference point.

[0076] Step S3: Substitute the gradient function of the attraction potential energy field function into the artificial potential energy field control function to obtain the cluster node relative motion speed command function; the cluster node relative motion speed command determined by the cluster node relative motion speed command function is bounded.

[0077] The relative motion velocity command of the cluster nodes (i.e., the desired motion dynamics of the cluster nodes) is taken as the negative value of the potential energy field gradient:

[0078]

[0079] Boundedness of the relative motion speed command of the cluster (i.e., the potential energy field function and its gradient function): The potential energy field function and its gradient function proposed in this invention, given the amplitude scale parameter, length scale parameter and reference distance parameter, have a finite size regardless of how the relative position vector of the cluster nodes changes. That is, the expected motion speed of the cluster nodes has a finite size, which is convenient for the control and implementation of the actual physical system.

[0080] Step S4: In real time, obtain the relative position of each cluster node in the cluster system with respect to the cluster formation reference point, the relative position with respect to other cluster nodes, and the movement speed in the relative position coordinate system.

[0081] Step S5: Based on the relative position of each cluster node to the cluster formation configuration reference point, the relative position of each cluster node to other cluster nodes, and the formation plane configuration to be switched, the relative motion speed command of each cluster node is obtained using the cluster node relative motion speed command function.

[0082] Step S6: Based on the relative motion speed command and motion speed of each cluster node, the relative motion speed control input of each cluster node is determined using the tracking control law.

[0083] For the relative motion speed command of the cluster nodes given in S5, the following tracking control law is used to track and control the actual relative motion speed of the cluster nodes to achieve error-free tracking of the expected motion speed command (relative motion speed command of the cluster nodes).

[0084]

[0085]

[0086] S = v di -v i

[0087] Where C(r,v) is the relative motion dynamics function of the cluster nodes (e.g., for a spacecraft constellation cluster, the simplified relative motion dynamics function is...). w n S is the orbital angular velocity of the reference star, S is the tracking error of the relative motion velocity of the cluster nodes, sof(S,φ) is the softening function, ε is the softening coefficient, k, γ and φ are control parameters, and u is the control input of the relative motion velocity of the cluster nodes.

[0088] Using the above tracking control rules, the actual relative motion speed of the cluster nodes can be accurately tracked by the expected relative motion speed command of the upper node, thereby realizing the cluster configuration.

[0089] Step S7: Control each cluster node according to the relative motion speed control input, so that the actual relative motion speed of the cluster node tracks the relative motion speed command of the upper node without error, and realize the cluster configuration.

[0090] When a cluster node malfunctions and cannot perform motion control, the node detaches from the cluster due to its inability to move normally, resulting in a change in the number of cluster members. The repulsive potential energy field function of the artificial potential energy field control function in S3... Cluster control updates can be achieved by deleting the relative position vector information associated with it.

[0091] This invention introduces an artificial potential energy field U for control of a cluster system composed of homogeneous nodes. Under the guidance of the negative gradient of the potential energy field, the cluster nodes move to the desired position.

[0092] This invention also provides an autonomous formation control system based on a bounded fork-shaped bifurcation potential field, comprising:

[0093] An artificial potential energy field control function establishment module is used to establish an artificial potential energy field control function for the relative motion velocity of an unmanned swarm; the artificial potential energy field control function includes the gradient function of the attractive potential energy field function and the gradient function of the repulsive potential energy field function;

[0094] The gradient function construction module is used to construct the gradient function of the attractive potential energy field function; the attractive potential energy field function and the gradient function of the attractive potential energy field function have a forked bifurcation characteristic;

[0095] The velocity command function acquisition module is used to input the gradient function of the attraction potential energy field function into the artificial potential energy field control function to obtain the relative motion velocity command function of the cluster nodes; the relative motion velocity command of the cluster nodes determined by the relative motion velocity command function of the cluster nodes is bounded.

[0096] The real-time module is used to obtain the relative position of each cluster node in the cluster system with respect to the cluster formation reference point, the relative position with respect to other cluster nodes, and the movement speed in real time in the relative position coordinate system.

[0097] The speed command acquisition module is used to obtain the relative motion speed command of each cluster node based on the relative position of each cluster node to the cluster formation configuration reference point, the relative position of each cluster node to other cluster nodes, and the formation plane configuration to be switched, using the cluster node relative motion speed command function.

[0098] The speed control input determination module is used to determine the relative motion speed control input of each cluster node based on the relative motion speed command and the motion speed of each cluster node, using a tracking control law.

[0099] The control module is used to control each cluster node according to the relative motion speed control input, so that the actual relative motion speed of the cluster nodes tracks the relative motion speed command of the upper node without error, thereby realizing the cluster configuration.

[0100] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0101] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A formation autonomous control method based on a bounded fork-shaped bifurcation potential field, characterized in that, include: Establish the artificial potential field control function for the relative motion velocity of the unmanned swarm: In the formula, v di The relative motion speed command for cluster node i. Let be the gradient function of the attraction potential energy field function of cluster node i. Let r be the gradient function of the repulsive potential energy field function of cluster node i; i Let r be the relative position vector between cluster node i and the cluster formation reference point. ij U is the relative position vector between cluster node i and cluster node j. G U is the attraction potential energy function. R The potential energy field function of the repulsive force; Construct the gradient function of the attractive potential energy field function; the attractive potential energy field function and its gradient function have a forked bifurcation characteristic; the attractive potential energy field function is... In the formula, C1 and C2 are the first and second amplitude scale parameters, respectively; C3 is the length scale function; r is the reference distance parameter; and μ is the formation configuration control switching parameter. Given the amplitude scale parameter, length scale parameter, and reference distance parameter, adjusting the configuration switching parameter μ achieves the switching of the cluster formation configuration. Given the configuration switching parameter μ, adjusting the amplitude scale parameter, length scale parameter, and reference distance parameter achieves the scaling up or down of the formation configuration. The gradient function of the attraction potential energy field function is... The gradient function of the attraction potential energy field function is substituted into the artificial potential energy field control function to obtain the cluster node relative motion speed command function; the cluster node relative motion speed command determined by the cluster node relative motion speed command function is bounded. Real-time acquisition of the relative position of each cluster node in the cluster system with respect to the cluster formation reference point, its relative position with respect to other cluster nodes, and its movement speed in the relative position coordinate system; Based on the relative positions of each cluster node and the cluster formation configuration reference point, the relative positions of each cluster node and other cluster nodes, and the formation plane configuration to be switched, the relative motion speed command of each cluster node is obtained using the cluster node relative motion speed command function. Based on the relative motion speed commands and motion speeds of each cluster node, the relative motion speed control input of each cluster node is determined using a tracking control law. The cluster nodes are controlled according to the relative motion speed control input, so that the actual relative motion speed of the cluster nodes tracks the relative motion speed command of the upper node without error, thus realizing the cluster configuration.

2. The formation autonomous control method based on a bounded fork-shaped bifurcation potential field according to claim 1, characterized in that, The artificial potential energy field control function for establishing the relative motion velocity of the unmanned swarm specifically includes: Establish the artificial potential field function as U i =U G (r i )+U R (r ij In the formula, U i Here is the artificial potential field function; Based on the artificial potential field function, the artificial potential field control function for the relative motion velocity of the cluster is determined.

3. The formation autonomous control method based on a bounded fork-shaped bifurcation potential field according to claim 2, characterized in that, The relative motion speed command function of the cluster nodes is:

4. The formation autonomous control method based on a bounded fork-shaped bifurcation potential field according to claim 2, characterized in that, The attraction potential energy field function and its gradient function have the following bifurcation characteristics: Given the first amplitude scale parameter C1, the second amplitude scale parameter C2, the length scale parameter C3, and the reference distance parameter r: if the formation switching parameter μ is less than the critical value and the reference distance parameter r is greater than zero, then only one cluster node position value is possible. At this point, the formation planar configuration is a circle; if the formation configuration switching parameter μ is greater than the critical value, then there exist two different cluster node position values ​​such that... At this point, the formation planar configuration is a concentric ring; if the formation configuration switching parameter μ is less than the critical value and the reference distance parameter r is equal to zero, then the formation planar configuration is a disk; When given the formation configuration switching parameter μ, the formation configuration can be enlarged or reduced by adjusting the first amplitude scale parameter C1, the second amplitude scale parameter C2, the length scale parameter C3, and the reference distance parameter r.

5. The formation autonomous control method based on a bounded fork-shaped bifurcation potential field according to claim 2, characterized in that, The boundedness of the relative motion speed command of the cluster nodes is as follows: Given the first amplitude scale parameter C1, the second amplitude scale parameter C2, the length scale parameter C3, and the reference distance parameter r, the relative motion velocity command of the cluster nodes has a finite magnitude, regardless of how the relative position vector values ​​of the cluster nodes and the cluster formation configuration reference points change.

6. The formation autonomous control method based on a bounded fork-shaped bifurcation potential field according to claim 3, characterized in that, The tracking control law is as follows: S=v di -v i In the formula, u is the relative motion speed control input of the cluster nodes, C(r,v) is the relative motion dynamics function of the cluster nodes, S is the relative motion speed tracking error of the cluster nodes, sof(S,φ) is the softening function, ε is the softening coefficient, and k, γ, and φ are the first, second, and third control parameters, respectively. For intermediate functions, It is the first derivative of the intermediate function.

7. The formation autonomous control method based on a bounded fork-shaped bifurcation potential field according to claim 1, characterized in that, Also includes: When a cluster node in the cluster system fails and cannot perform motion control, the relative position vector related to the failed cluster node is deleted from the repulsive potential energy field function of the artificial potential energy field control function, thereby realizing the control update of the cluster system.

8. A formation autonomous control system based on a bounded fork-shaped bifurcation potential field, characterized in that, include: The module for establishing the artificial potential energy field control function is used to establish the artificial potential energy field control function for the relative motion velocity of the unmanned swarm. In the formula, v di The relative motion speed command for cluster node i. Let be the gradient function of the attraction potential energy field function of cluster node i. Let r be the gradient function of the repulsive potential energy field function of cluster node i; i Let r be the relative position vector between cluster node i and the cluster formation reference point. ij U is the relative position vector between cluster node i and cluster node j. G U is the attraction potential energy function. R The potential energy field function of the repulsive force; A gradient function construction module is used to construct the gradient function of the attractive potential energy field function; the attractive potential energy field function and its gradient function exhibit a forked bifurcation characteristic; the attractive potential energy field function is... In the formula, C1 and C2 are the first and second amplitude scale parameters, respectively; C3 is the length scale function; r is the reference distance parameter; and μ is the formation configuration control switching parameter. Given the amplitude scale parameter, length scale parameter, and reference distance parameter, adjusting the configuration switching parameter μ achieves the switching of the cluster formation configuration. Given the configuration switching parameter μ, adjusting the amplitude scale parameter, length scale parameter, and reference distance parameter achieves the scaling up or down of the formation configuration. The gradient function of the attraction potential energy field function is... The velocity command function acquisition module is used to input the gradient function of the attraction potential energy field function into the artificial potential energy field control function to obtain the relative motion velocity command function of the cluster nodes; the relative motion velocity command of the cluster nodes determined by the relative motion velocity command function of the cluster nodes is bounded. The real-time module is used to obtain the relative position of each cluster node in the cluster system with respect to the cluster formation reference point, the relative position with respect to other cluster nodes, and the movement speed in real time in the relative position coordinate system. The speed command acquisition module is used to obtain the relative motion speed command of each cluster node based on the relative position of each cluster node to the cluster formation configuration reference point, the relative position of each cluster node to other cluster nodes, and the formation plane configuration to be switched, using the cluster node relative motion speed command function. The speed control input determination module is used to determine the relative motion speed control input of each cluster node based on the relative motion speed command and the motion speed of each cluster node, using a tracking control law. The control module is used to control each cluster node according to the relative motion speed control input, so that the actual relative motion speed of the cluster nodes tracks the relative motion speed command of the upper node without error, thereby realizing the cluster configuration.

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