CN105867415A - Cooperative control policy based on secure communication of multiple unmanned aerial vehicles - Google Patents

Abstract

The invention discloses a cooperative control policy based on secure communication of multiple unmanned aerial vehicles. The cooperative control policy comprises a first step of applying an Olfati-saber flocking control algorithm of a variable speed virtual leader to perform preliminary cooperative control over an unmanned aerial vehicle group; a second step of introducing a virtual communication circle to perform on-line communication power setting on each unmanned aerial vehicle, and calculating an expected position of each unmanned aerial vehicle node meeting the secure communication requirements; and a third step of applying an optimized position movement function to make each unmanned aerial vehicle node move to the expected position obtained in the second step securely without collision. According to the cooperative control policy, how communication affects unmanned aerial vehicle group dynamics and communication topology is studied more; through the newly provided virtual communication circle and by combination of an improved target movement function and an existing classic dynamics flocking algorithm, the problem of insecurity of information leakage possibly occurring to a multi-unmanned aerial vehicle system is effectively solved, and the cooperative control policy is a new idea for describing relations of unmanned aerial vehicle dynamics and wireless ad hoc networks.

Description

A kind of coordination control strategy based on multiple no-manned plane secure communication

Technical field

The invention belongs to the communications field of multiple no-manned plane Collaborative Control, be specifically related to a kind of coordination control strategy based on multiple no-manned plane secure communication.

Background technology

Multiple no-manned plane system due to its individuality have autonomous intelligence, at high speed, the feature such as fast-changing topology, internal communication network uses mobile ad-hoc network；The secure communication problem of unmanned plane in prior art, simply by the presence of both sides defect: on the one hand, when unmanned plane transmitting power is the highest, multipling channel can be interfered, the most not only can other unmanned planes of severe jamming, reduce the performance of node, but also the overall transmitted power of unmanned plane group can be increased, easily make information reveal；On the other hand, if the transmitting power of some unmanned plane is not high enough, the signal to noise ratio in link can reduce, and this can affect the connectedness of link, causes some unmanned plane can not proper communication.

At multiple no-manned plane secure communications, main direction of studying concentrates on the aspects such as the optimization to Information Security between node and procotol；Milan Rollo et al. embedded in X-Security layer on the basis of FIPA ACL and processes the secure communication between intelligent body, uses recipient to carry out key encryption and sends the message to ensure the confidentiality of communication data, it is provided that point-to-point secure communication mechanism；The mobile ad-hoc network Routing Optimization Algorithm that Du Jun et al. proposes, the method is by improving ant group algorithm foundation trust statistical model, and the routed path that between discovery node, safety is higher is as data transfer path.

In terms of unmanned plane Collaborative Control, main research concentrates on fixing formation control based on aerodynamic basis and dynamic formation control based on Swarm Intelligence Algorithm.

In nature, a lot of animal populations, such as flock of birds, the shoal of fish, ant colony, bee colony etc., usually can keep the Methodistic group movement that certain formation moves to target location, this group behavior we be referred to as swarming；Proposing from C.Reynolds. intuitively show three criterions that flock of birds is moved with computer after, swarm intelligence theory is developed rapidly, and this is also the heuristic rule of behavior of swarming now, is 1 respectively) each node is close to group center；2) collision of group's interior joint is avoided；3) speed of node reaches unanimity；Vicsek et al. proposes the colony of improvement on the basis of Reynolds model and swarms model, makes all individualities finally move with identical speed and direction by proposing location matches rule；Olfati-Saber will be that the swarm thought of behavior modeling of colony is generalized to the modeling problem in multi-obstacle avoidance space based on dynamic network method, the algorithm of swarming based on virtual leader and α grid proposed not only meets three conditions of swarming, and gives the explanation on strict mathematical model and geometric graphics；Collective control theory being extended to the Collaborative Control field of multiple no-manned plane, a considerable problem is the communication performance between unmanned plane；Because the unmanned plane that autonomous agent based on perception with transmission information controls realizes by communicating.The communication performance of multiple no-manned plane system, need unmanned plane spacing, radio signal power and topological structure consider comprehensively, and swarm in the algorithm research as multiple no-manned plane Collaborative Control basis now, mainly make to be between unmanned plane equidistant formation, the factor such as communication performance, secure communication between unmanned plane is considered less.

Summary of the invention

The present invention is directed to the weak point that prior art exists, it is proposed that a kind of coordination control strategy based on multiple no-manned plane secure communication；Solve Communication Security Problem, reduce the probability of information leakage.

It is an object of the invention to be achieved through the following technical solutions: a kind of coordination control strategy based on multiple no-manned plane secure communication, including following step:

Step 1: use the Olfati-saber of the virtual leader of speed change control algolithm of swarming unmanned plane group carries out preliminary Collaborative Control to make whole multiple no-manned plane group reach equidistant state of swarming；

Step 2: introduce virtual communication annulus, its building method includes finding node layer and arranging communication radius, every frame unmanned plane carrying out online power of communications arrange, calculate each unmanned plane node meets the desired locations that secure communication requires, is allowed to reach secure communication target；

Step 3: use the position move function optimized, makes on the desired locations that each unmanned plane node security moves to draw in step 2 without collision.

Above-mentioned a kind of based on multiple no-manned plane secure communication coordination control strategy, described step 1 also includes:

Step 1.1: arrange parameter, sets unmanned plane number of nodes n, distance d of swarming between unmanned plane, communication spectrum bandwidth W, launches power P_i ^t, maximum iteration time Iter_times.

Step 1.2: initialize unmanned plane, initializing unmanned plane i initial position in theorem in Euclid space is pi, and unmanned plane i initial velocity in theorem in Euclid space is v_i；

Step 1.3: calculate adjacency matrix a_ijP (), multiple no-manned plane topological diagram is weighted graph G, sets up adjacency matrix a according to relationships between nodes_ij(p), as described in formula (1):

a_ij(p)=ρ h (| | p_j-p_i||_σ/r_α)∈[0,1],j≠i (1)

Wherein, p_iRepresent that node i is at the position of theorem in Euclid space, r_α=| | r | |_σ, a_ijP () represents the internodal distance of adjacency matrix two, p_jRepresent the European position of node j in addition to node i, | | r | |_σRefer to the sensing range of intelligent body node by σ-norm conversion, wherein, ρ h (| | p_j-p_i||_σ/r_α) belong to ρ h (z) function；

This piecewise function is the collision function weighing unmanned plane euclidean distance between node pair relation；

Step 1.4: structure collective's potential-energy function V (p), as shown in formula (2):

Wherein, | | p_j-p_i||_σ=d_α,p_jThe European position of expression node j in addition to node i, d_αFor the distance between two nodes in the geometry swarmed,It is paired attraction, repels potential energy, can pass through formula (3) calculating:

Wherein,φ (z) is a uneven s type function,A, b, c are normal integer, and ρ h (z) is collision function, 0 ＜ a≤b,

Step 1.5: add the influence factor of intelligent body group target, namely add the navigation feedback term of group's virtual leader γ intelligent body, tries to achieve every frame unmanned aerial vehicle (UAV) control input ui, as shown in formula (4):

$u_i=\underset{j\∈N_i}{\Σ}{\mathrm{\φ}}_{\mathrm{\α}}\left({||p_j-p_i||}_{\mathrm{\σ}}\right)n_{ij}+\underset{j\∈N_i}{\Σ}{a}_{ij}\left(p\right)(v_j-v_i)+f_i^{\mathrm{\γ}}(p_i,v_i,p_r,v_r)---\left(4\right)$

Wherein,It is p_iAnd p_jVectorial ε ∈ (0,1) in closure is the quantitative parameter in σ-norm；

u_i ^γ=f_i ^γ(p_i,v_i,p_r,v_r)=-c₁(p_i-p_r)-c₂(v_i-v_r),c₁,c₂＞ 0

u_i ^γIt is the control input of each unmanned plane affected with virtual leader, v_iRepresent unmanned plane i speed in theorem in Euclid space, p_iRepresent unmanned plane i position in theorem in Euclid space, p_jIt is the positional information of node j in addition to node i, v_jRepresent except node_iThe velocity information of node j in addition, p_rRepresent the position of virtual leader, v_rRepresent the speed of virtual leader, c₁、c₂It it is all the weighted value regulating virtual leader impact；

Step 1.6: judged result, equidistantly swarming if meeting unmanned plane, forwarding step 1.7 to, otherwise forwards step 1.3 to；

Step 1.7: by unmanned plane kinesiology formulaIt is calculated positional information p in theorem in Euclid space when each unmanned plane is swarmed_i；

Above-mentioned a kind of based on multiple no-manned plane secure communication coordination control strategy, described step 2 also includes:

Step 2.1: input the p after state of swarming_i、a_ij(p), unmanned plane number of nodes n；

Step 2.2: use Kmeans algorithm to each unmanned plane node initial position p of input in step 1_iClassify, find the Centroid position o of unmanned plane group, then find the unmanned plane node from this virtual group Centroid distance is minimum to be designated as min_num；

Step 2.3: initialize in set Level_node and set Compare_node, described set Level_node and set Compare_node and comprise the minimum unmanned plane node min_num in step 2.2；

Step 2.4: unmanned plane node begins stepping through from level_node, it may be judged whether the most traversed, if all having stepped through execution step 2.5, otherwise performs step 2.7；

Step 2.5: by the adjacency matrix a of input in step 1_ijP (), finds in Level_node set the adjacent node of unmanned plane node and is stored in and combines Node_neibor；

Step 2.6: judge whether the unmanned plane node in the Node_neibor generated in step 2.5 set broadly falls into Compare_node set；If being all already belonging to perform step 2.4, otherwise, perform step 2.7；

Step 2.7: update Level_node set, the part being not belonging to Compare_node is stored in new Level_node and Level_node is incorporated to Compare_node；

Step 2.8: judge in Level_node, whether the union of the abutment points of all nodes broadly falls into contrast groups Compare_node, if broadly falling into algorithm to go to step 2.9, otherwise performs step 2.4；

Step 2.9: be calculated virtual communication annulus: the first each node of Level_node in input step 2.7, tries to achieve the communication radius r of each unmanned plane_i(t), as shown in formula (5):

$r_i\left(t\right)=(r_{max}-r_{min}){\mathrm{\η}}^{{\[o_i\left(t\right)-\mathrm{\α}\]}^{+}}+r_{min}---\left(5\right)$

Wherein, r_max,r_minIt is the minimum and maximum communication radius that can distribute of unmanned plane respectively；η=r_e/r_n, for the communication radius of unmanned plane node self and its close on the ratio of minimum communication radius of unmanned plane, o_iT () is the unmanned plane node i distance away from group's Centroid position o, α is the positive integer more than 0, and α illustrates the weight of UAV Communication scoped features；

The radius r of jth layer virtual communication annulus is sought by formula (6)_{level_j}

r_{level_j}=min (r_jk)+r_{level_(j-1)} (6)

Wherein, r_jkRepresent the communication radius of the jth layer interior joint k tried to achieve by formula (5)；

By the method seeking dot product, try to achieve annulus equation, as shown in formula (7) with the polar equation of circle:

ρ²-2ρ(acosθ-bsinθ)+a²+b²-R²=0 (7)

Wherein, ρ is annular radii, (a, b) is respectively the coordinate of center unmanned plane node,

Output annulus equation respectively, level_node gathers, each unmanned plane node location p_iWith group's Centroid position o；Perform step 3；

Above-mentioned a kind of based on multiple no-manned plane secure communication coordination control strategy, described step 3 also includes: step 3.3: the result in input step 2 is as the input parameter in step 3, including described Level_node set, the position p of described each unmanned plane node_i, described min_num center unmanned plane node；

Step: 3.2: unmanned plane node each in Level_node is traveled through, it is judged that whether Level_node set is empty, performs step 3.6 if it is empty, otherwise performs 3.3.

Step 3.3: calculate unmanned plane node and the distance vector p of min_num center unmanned plane node in each Level_node_io；

Step 3.4: try to achieve each node and the angle of X-coordinate in two-dimensional space by formula (8)；

Cos θ ← dot product (p_io,[1,0])/||p_io||² (8)

Step 3.5: try to achieve each unmanned plane node with virtual communication annulus intersection point, as its desired locations DestPos_i, as shown in formula (9):

DestPos_i←r_{level_j}*[cosθ+o(1)；sinθ+o(2)] (9)

Step 3.6: export the DestPos of each node_i, and be input in the move function of target location as parameter, make each unmanned plane move on its desired locations meeting secure communication requirement；

Step 3.7: so far, whole algorithm terminates.

The present invention, is primarily directed to when the increase of multiple no-manned plane group communication range, also can increase the dangerous region that data are stolen, and improves the probability of information leakage.Therefore, what the present invention mainly studied is between communication and multiple no-manned plane group size, formation form and group's kinetics.

Relation, by reaching the purpose of secure communication to the unmanned plane formation i.e. adjustment of communication topology.

The present invention improves the control algolithm basis as multiple no-manned plane coordination control strategy of swarming, and compares the Collaborative Control of fixing formation, improves autonomy and the robustness of multiple no-manned plane system.

The present invention is directed to multiple no-manned plane secure communication problem, use swarm intelligence algorithm research multiple no-manned plane Collaborative Control of swarming to have very important significance.

The present invention is based on the control algolithm of swarming in swarm intelligence theory, introduce virtual communication annulus and control the wireless signal transmission power of unmanned plane, adjust the communication topology of group, in the range of finally making unmanned plane move to secure communication, and reduce the communication range of whole group.

Compared with prior art, it is an advantage of the current invention that more to study communication is how to affect unmanned plane group kinetics and communication topology, by the new virtual communication annulus proposed, target move function and the existing classical dynamics improved is swarmed the combination of algorithm, make each unmanned plane node form fixing formation or unlike the formation form of uniform distances from existing method, the invention enables and between each unmanned plane, meet the requirement meeting secure communication distance, effectively solve the information that multiple no-manned plane system is likely to occur, the dangerous phenomenon of leakage, it is a kind of new approaches describing unmanned plane kinetics and wireless self-organization network relation.

Accompanying drawing explanation

Fig. 1 is the flow chart of a kind of coordination control strategy based on multiple no-manned plane secure communication of the present invention.

Specific embodiment:

Describing the detailed description of the invention of the present invention below in conjunction with the accompanying drawings in detail, the content of detailed description of the invention is not as the restriction to protection scope of the present invention.

A kind of coordination control strategy based on multiple no-manned plane secure communication, including following step:

Step 1: use the Olfati-saber of the virtual leader of speed change control algolithm of swarming unmanned plane group carries out preliminary Collaborative Control to make whole multiple no-manned plane group reach equidistant state of swarming；

Step 1.1: arrange parameter, sets unmanned plane number of nodes n, distance d of swarming between unmanned plane, communication spectrum bandwidth W, launches power P_i ^t, maximum iteration time Iter_times；

Step 1.2: initialize unmanned plane, initializes unmanned plane i initial position p in theorem in Euclid space_i, and unmanned plane i initial velocity v in theorem in Euclid space_i；

Step 1.3: calculate adjacency matrix a_ijP (), multiple no-manned plane topological diagram is weighted graph G, sets up adjacency matrix a according to relationships between nodes_ij(p), as described in formula (1):

a_ij(p)=ρ h (| | p_j-p_i||_σ/r_α)∈[0,1],j≠i (1)

Wherein, p_iRepresent that node i is at the position of theorem in Euclid space, r_α=| | r | |_σ, a_ijP () represents the internodal distance of adjacency matrix two；p_jRepresent the European position of node j in addition to node i, | | r | |_σRefer to the sensing range of intelligent body node by σ-norm conversion, wherein, ρ h (| | p_j-p_i||_σ/r_α) belong to ρ h (z) function；

This piecewise function is the collision function weighing unmanned plane euclidean distance between node pair relation；

Step 1.4: structure collective's potential-energy function V (p), as shown in formula (2):

Wherein, | | p_j-p_i||_σ=d_α,p_jThe European position of expression node j in addition to node i, d_αFor the distance between two nodes in the geometry swarmed,It is paired attraction, repels potential energy, can pass through formula (3) calculating:

Wherein,φ (z) is a uneven s type function,A, b, c are normal integer, and ρ h (z) is collision function, 0 ＜ a≤b,

Step 1.5: add the influence factor of intelligent body group target, namely add the navigation feedback term of group's virtual leader γ intelligent body, tries to achieve every frame unmanned aerial vehicle (UAV) control input ui, as shown in formula (4):

$u_i=\underset{j\∈N_i}{\Σ}{\mathrm{\φ}}_{\mathrm{\α}}\left({||p_j-p_i||}_{\mathrm{\σ}}\right)n_{ij}+\underset{j\∈N_i}{\Σ}{a}_{ij}\left(p\right)(v_j-v_i)+f_r^{\mathrm{\γ}}(p_i,v_i,p_r,v_r)---\left(4\right)$

Wherein,It is p_iAnd p_jVectorial ε ∈ (0,1) in closure is the quantitative parameter in σ-norm,

u_i ^γ=f_i ^γ(p_i,v_i,p_r,v_r)=-c₁(p_i-p_r)-c₂(v_i-v_r),c₁,c₂＞ 0

u_i ^γIt is the control input of each unmanned plane affected with virtual leader, v_iRepresent unmanned plane i initial velocity in theorem in Euclid space, p_iRepresent unmanned plane i initial position in theorem in Euclid space, p_jIt is the positional information of node j in addition to node i, v_jExpression removes_iIn addition_jVelocity information, p_rRepresent the position of virtual leader, v_rRepresent the speed of virtual leader, c₁、c₂It it is all the weighted value regulating virtual leader impact；

Step 1.6: judged result, equidistantly swarming if meeting unmanned plane, forwarding step 1.7 to, otherwise forwards step 1.3 to；

Step 1.7: by unmanned plane kinesiology formulaIt is calculated positional information p in theorem in Euclid space when each unmanned plane is swarmed_i；

Step 2: introduce virtual communication annulus, its building method includes finding node layer and arranging communication radius, every frame unmanned plane carrying out online power of communications arrange, calculate each unmanned plane node meets the desired locations that secure communication requires, is allowed to reach secure communication target；In the case of meeting communication requirement, the communication range of unmanned plane outside group is minimized.

Step 2.1: input the p after state of swarming_i、a_ij(p), unmanned plane number of nodes n；

Step 2.2: use Kmeans algorithm to each unmanned plane node initial position p of input in step 1_iClassify, find the virtual group center of unmanned plane group, then find the unmanned plane node from this virtual group Centroid distance is minimum to be designated as min_num；

Step 2.3: initialize in set Level_node and set Compare_node, described set Level_node and set Compare_node and comprise the minimum unmanned plane node min_num in step 2.2；

Step 2.4: unmanned plane node begins stepping through from level_node, it may be judged whether the most traversed, if all having stepped through execution step 2.5, otherwise performs step 2.7；

Step 2.5: by the adjacency matrix a of input in step 1_ijP (), finds in Level_node set the adjacent node of unmanned plane node and is stored in and combines Node_neibor；

Step 2.6: judge whether the unmanned plane node in the Node_neibor generated in step 2.5 set broadly falls into Compare_node set；If being all already belonging to perform step 2.4, otherwise, perform step 2.7；

Step 2.7: update Level_node set, the part being not belonging to Compare_node is stored in new Level_node and Level_node is incorporated to Compare_node；

Step 2.8: judge in Level_node, whether the union of the abutment points of all nodes broadly falls into contrast groups Compare_node, if broadly falling into algorithm to go to step 2.9, otherwise performs step 2.4；

Step 2.9: be calculated virtual communication annulus: the first each node of Level_node in input step 2.7, tries to achieve the communication radius r of each unmanned plane_i(t), as shown in formula (5):

$r_i\left(t\right)=(r_{max}-r_{min}){\mathrm{\η}}^{{\[o_i\left(t\right)-\mathrm{\α}\]}^{+}}+r_{min}---\left(5\right)$

Wherein, r_max,r_minIt is the minimum and maximum communication radius that can distribute of unmanned plane respectively；η=r_e/r_n, for the communication radius of unmanned plane node self and its close on the ratio of minimum communication radius of unmanned plane, o_iT () is the unmanned plane node i distance away from group's Centroid position o, α is the positive integer more than 0, and α illustrates the weight of UAV Communication scoped features；

The radius r of jth layer virtual communication annulus is sought by formula (6)_{level_j}

r_{level_j}=min (r_jk)+r_{level_(j-1)} (6)

Wherein, r_jkRepresent the communication radius of the jth layer interior joint k tried to achieve by formula (5)；

By the method seeking dot product, try to achieve annulus equation, as shown in formula (7) with the polar equation of circle:

ρ²-2ρ(acosθ-bsinθ)+a²+b²-R²=0 (7)

Wherein, ρ is annular radii, (a, b) is respectively the coordinate of center unmanned plane node,

Output annulus equation respectively, level_node gathers, each unmanned plane node initial position p_iWith group's Centroid position o；Perform step 3；

Step 3: use the position move function optimized, makes on the desired locations that each unmanned plane node security moves to draw in step 2 without collision；

Step 3.1: the result in input step 2 is as the input parameter in step 3, including described Level_node set, the position p of described each unmanned plane node_i, described min_num center unmanned plane node；

Step: 3.2: unmanned plane node each in Level_node is traveled through, it is judged that whether Level_node set is empty, performs step 3.6 if it is empty, otherwise performs 3.3；

Step 3.3: calculate unmanned plane node and min_num center unmanned plane node in each Level_node

Distance vector p_io；

Step 3.4: try to achieve each node and the angle of X-coordinate in two-dimensional space by formula (8)；

Cos θ ← dot product (p_io,[1,0])/||p_io||² (8)

Step 3.5: try to achieve each unmanned plane node with virtual communication annulus intersection point, as its desired locations DestPos_i, as shown in formula (9):

DestPos_i←r_{level_j}*[cosθ+o(1)；sinθ+o(2)] (9)

Step 3.6: export the DestPos of each node_i, and be input in the move function of target location as parameter, finally make smooth the moving to without collision of each unmanned plane node meet the target location that virtual communication annulus limits；

Step 3.7: so far, whole algorithm terminates, and reaches Liao Shi unmanned plane group and meets the formation form of secure communication requirement；

The content of detailed description of the invention, for the ease of skilled artisan understands that and use the present invention to describe, is not intended that the restriction that the present invention protects content.The present invention, after having read present disclosure, can suitably be revised by those skilled in the art.The protection content of the present invention is as the criterion with the content of claim.In the case of without departing from the flesh and blood of claim and protection domain, various amendments that the present invention is carried out, change and replacement etc. is all within protection scope of the present invention.

Claims (4)

1. a coordination control strategy based on multiple no-manned plane secure communication, it is characterised in that: include following step:

Step 1: use the Olfati-saber of the virtual leader of speed change control algolithm of swarming unmanned plane group carries out preliminary Collaborative Control to make whole multiple no-manned plane group reach equidistant state of swarming；

Step 2: introduce virtual communication annulus, its building method includes finding node layer and arranging communication radius, every frame unmanned plane carrying out online power of communications arrange, calculate each unmanned plane node meets the desired locations that secure communication requires, is allowed to reach secure communication target；

Step 3: use the position move function optimized, makes on the desired locations that each unmanned plane node security moves to draw in step 2 without collision.

A kind of coordination control strategy based on multiple no-manned plane secure communication the most according to claim 1, it is characterised in that: described step 1 also includes:

Step 1.1: arrange parameter, sets unmanned plane number of nodes n, distance d of swarming between unmanned plane, communication spectrum bandwidth W, launches powerMaximum iteration time Iter_times；

Step 1.2: initialize unmanned plane, initializing unmanned plane i initial position in theorem in Euclid space is p_i, and unmanned plane i initial velocity in theorem in Euclid space is v_i；

Step 1.3: calculate adjacency matrix a_ijP (), multiple no-manned plane topological diagram is weighted graph G, sets up adjacency matrix a according to relationships between nodes_ij(p), as described in formula (1):

a_ij(p)=ρ h (| | p_j-p_i||_σ/r_α)∈[0,1],j≠i (1)

Wherein, p_iRepresent that node i is at the position of theorem in Euclid space, r_α=| | r | |_σ, p_jRepresent the European position of node j in addition to node i, | | r | |_σRefer to the sensing range of intelligent body node by σ-norm conversion, wherein, ρ h (| | p_j-p_i||_σ/r_α) belong to ρ h (z) function；This piecewise function is the collision function weighing unmanned plane euclidean distance between node pair relation；

Step 1.4: structure collective's potential-energy function V (p), as shown in formula (2):

Wherein, | | p_j-p_i||_σ=d_α,d_αFor distance between two nodes in the geometry of the state of swarming, p_jThe European position of expression node j in addition to node i,It is paired attraction, repels potential energy, can pass through formula (3) shown:

Wherein, φ_α(s) ds=φ_α(z)=ρ h (z/r_a)φ(z-d_α),φ (z) is a uneven s type function,A, b, c are normal integer, and ρ h (z) is collision function,

Step 1.5: add the influence factor of intelligent body group target, namely add the navigation feedback term of group's virtual leader γ intelligent body, tries to achieve every frame unmanned aerial vehicle (UAV) control input ui, as shown in formula (4):

Wherein,It is p_iAnd p_jVectorial ε ∈ (0,1) in closure is the quantitative parameter in σ-norm；

It is the control input of each unmanned plane affected with virtual leader, v_iRepresent unmanned plane i speed in theorem in Euclid space, p_iRepresent unmanned plane i initial position in theorem in Euclid space, p_jIt is the positional information of node j in addition to node i, v_jThe velocity information of expression node j in addition to node i, p_rRepresent the position of virtual leader, v_rRepresent the speed of virtual leader, c₁、c₂It it is all the weighted value regulating virtual leader impact；

Step 1.6: judged result, equidistantly swarming if meeting unmanned plane, forwarding step 1.7 to, otherwise forwards step 1.3 to；

Step 1.7: be calculated positional information p in theorem in Euclid space when each unmanned plane is swarmed by unmanned plane kinesiology formula_i。

A kind of coordination control strategy based on multiple no-manned plane secure communication the most according to claim 1, it is characterised in that: described step 2 also includes:

Step 2.1: input the p after state of swarming_i、a_ij(p), unmanned plane number of nodes n；

Step 2.2: use Kmeans algorithm to each unmanned plane node initial position p of input in step 1_iClassify, find the virtual group center of unmanned plane group, then find the unmanned plane node from this virtual group Centroid distance is minimum to be designated as min_num；

Step 2.3: initialize in set Level_node and set Compare_node, described set Level_node and set Compare_node and comprise the minimum unmanned plane node min_num in step 2.2；

Step 2.4: unmanned plane node begins stepping through from level_node, it may be judged whether the most traversed, if all having stepped through execution step 2.5, otherwise performs step 2.7；

Step 2.5: by the adjacency matrix a of input in step 1_ijP (), finds in Level_node set the adjacent node of unmanned plane node and is stored in and combines Node_neibor；

Step 2.6: judge whether the unmanned plane node in the Node_neibor generated in step 2.5 set broadly falls into Compare_node set；If being all already belonging to perform step 2.4, otherwise, perform step 2.7；

Step 2.7: update Level_node set, the part being not belonging to Compare_node is stored in new Level_node and Level_node is incorporated to Compare_node；

Step 2.8: judge in Level_node, whether the union of the abutment points of all nodes broadly falls into contrast groups Compare_node, if broadly falling into algorithm to go to step 2.9, otherwise performs step 2.4；

Step 2.9: be calculated virtual communication annulus: the first each node of Level_node in input step 2.7, tries to achieve the communication radius r of each unmanned plane_i(t), as shown in formula (5):

Wherein, r_max,r_minIt is the minimum and maximum communication radius that can distribute of unmanned plane respectively；η=r_e/r_n, for the communication radius of unmanned plane node self and its close on the ratio of minimum communication radius of unmanned plane, o_iT () is the unmanned plane node i distance away from group's Centroid position o, α is the positive integer more than 0, and α illustrates the weight of UAV Communication scoped features；

The radius r of jth layer virtual communication annulus is sought by formula (6)_{level_j}

r_{level_j}=min (r_jk)+r_{level_(j-1)} (6)

Wherein, r_jkRepresent the communication radius of the jth layer interior joint k tried to achieve by formula (5)；

By the method seeking dot product, try to achieve annulus equation, as shown in formula (7) with the polar equation of circle:

ρ²-2ρ(acosθ-bsinθ)+a²+b²-R²=0 (7)

Wherein, ρ is annular radii, (a, b) is respectively the coordinate of center unmanned plane node,

Output annulus equation respectively, level_node gathers, each unmanned plane node initial position p_iWith group's Centroid position o；Perform step 3.

A kind of coordination control strategy based on multiple no-manned plane secure communication the most according to claim 1, it is characterised in that: described step 3 also includes:

Step 3.1: the result in input step 2 is as the input parameter in step 3, including described Level_node set, the position p of described each unmanned plane node_i, described min_num center unmanned plane node；

Step: 3.2: unmanned plane node each in Level_node is traveled through, it is judged that whether Level_node set is empty, performs step 3.6 if it is empty, otherwise performs 3.3.

Step 3.3: calculate unmanned plane node and the distance vector p of min_num center unmanned plane node in each Level_node_io；

Step 3.4: try to achieve each node and the angle of X-coordinate in two-dimensional space by formula (8)；

Cos θ ← dot product (p_io,[1,0])/||p_io||² (8)

Step 3.5: try to achieve each unmanned plane node with virtual communication annulus intersection point, as its desired locations DestPos_i, as shown in formula (9):

DestPos_i←r_{level_j}*[cosθ+o(1)；sinθ+o(2)] (9)

Step 3.6: export the DestPos of each node_i, and be input in the move function of target location as parameter, make each unmanned plane move on its desired locations meeting secure communication requirement；

Step 3.7: so far, whole algorithm terminates.