CN115016526B - Cluster self-organizing control method for double-layer defense - Google Patents
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Abstract
The invention relates to a self-organizing control method of a double-layer defending cluster, wherein the defending cluster and the intrusion cluster respectively have different individual attributes and interaction strategies, and a defending potential field force is formed by constructing a defending potential field to realize a double-layer defending effect for the defending cluster, and in addition, a position cooperative item, a speed cooperative item, a self-driving item, an anti-intrusion item and a random noise item are also provided, so that the intrusion of an intruder can be dealt with by setting different weight coefficients; for an intrusion cluster, a certain difference exists between a cooperative rule and a defense cluster, and main cooperative items comprise: the method comprises the steps of setting a cooperative item weight coefficient to complete an intrusion task. And (3) making a rule on the cooperative rules and the interaction strategies of the two-party clusters, further determining the defending cluster parameters according to the defending effect, and finally realizing successful cluster defending.
Description
Technical Field
The invention relates to the technical field of cluster intelligence, in particular to a self-organizing control method for carrying out cluster defense countermeasure by utilizing a double-layer defense potential field.
Background
The phenomenon of colony movement is widely found in nature, and is suggested from vortex of fish to migration of bird colony, from cooperation of ant colony to formation of bacterial colony. The individuals composing the group have limited ability and do not have complex intelligent thinking, and the group formed by the individuals can show complex ordered and various intelligent clustering phenomenon, which is also called clustering self-organization emerging behavior. The core of the cluster motion is the basic rule followed by individuals in the cluster, and the rule is followed by the individuals to finally emerge rich phenomena at the group level. By referencing the natural cluster rules, people construct various artificial cluster systems, which are embodied in military use and civil use. For example, the method is applied to unmanned aerial vehicle groups, and can be used for completing complex environment exploration, forest fire prevention and control, personnel search and rescue under disasters, and even realizing cross-domain cooperation through a cluster technology. Meanwhile, various cluster models, such as a social force model, a Vicsek model, a Couzin model and the like, are also put forward on a theoretical level through realizing actual manual clustering.
In terms of defending against intrusion challenge problems, the most basic model is called: target-intruder-defender challenge model (target-attacker-DEFENDER GAME, TAD game). This basic challenge model contains three participants, the target, intruder and defender, respectively. An intruder aims to capture the target while avoiding attack by an defender. Defenders attempt to protect the target while also capturing the intruder as much as possible. The target has no defensive ability to the invader and can only avoid the attack of the invader by escaping. Solutions to TAD models are mainly divided into two categories: and selecting an optimal strategy according to the initial position division dominant region, and constructing a differential equation to dynamically update the state. The TAD problem aims at the defending invasion problem of a single individual, when defending invasion among a plurality of individuals (groups), the method is generally adopted to match a target between an defender and an invader through an allocation algorithm, and the traditional TAD solution method is adopted after one-to-one matching is completed. Namely, the current thought for defending the intrusion problem among groups is to decompose the defending among groups into two steps: individual matching and individual defense. The method simply regards the population as the accumulated sum of a plurality of individuals, changes the population defense into a plurality of individual defenses which are performed simultaneously, and does not fully highlight the population advantage.
So how to motivate population advantage is a core problem for current population defense. Defensive intrusion countermeasures using a clustered self-organizing approach are one option, where how to design clustered individual rules such that defensive behavior emerges is a matter of intense investigation.
Disclosure of Invention
Technical problem to be solved
In order to avoid the defects of the prior art, the invention provides a self-organizing control method for cluster defense, which updates the motion state of individuals by combining a social force model through the design of individual interaction mechanisms in a cluster and among the clusters, and finally realizes the self-organizing control of the cluster defense.
Technical proposal
A cluster self-organizing control method of double-layer defense is characterized in that: setting a cooperative rule of an individual in a defending cluster and an individual in an intrusion cluster;
1) The cooperative rule of the individual in the defense cluster is expressed as follows:
Wherein, Is a self-driven item,/>For location collaborative item,/>Is a velocity synergistic term,/>As a potential field protection term,As an anti-intrusion term, ηζ i is random noise;
the self-driving item
Wherein, alpha represents the maximum value of the defending cluster speed, and v i (t) represents the defending cluster speed;
The position cooperative item
Representing the balance position adjustment parameter of attraction force and repulsion force, wherein the repulsion force is represented when the individual interval is smaller than the value, and the attraction force is represented when the individual interval is larger than the value; /(I)Representing the subgroup spacing, the repulsive force between subgroups reaching a maximum when the individual spacing is equal to the value; /(I)A unit vector representing the location vector of neighbor individuals to individuals D i;
n i is a set of perceivable neighbors:
Ni＝{k|dik＜Rsen,k∈{1,...,ND},k≠i}
Wherein d ik represents the distance between individuals in the defensive cluster, and R sen > 0 is the perceived radius of the defensive cluster;
The speed cooperative item
Representing the speed of the neighbor individual with the largest angle change in the neighbors;
The potential field protection item
Wherein d ip represents the distance from the defending individual to the protected object,A unit vector representing a position vector of the individual D i to the protection object; /(I)Respectively corresponding to the boundary distances of potential fields surrounding the protection object;
the anti-intrusion item
T i is a set of perceivable intruders:
Ti＝{k|dik＜Rsen,k∈{1,...,NI}}
Wherein d ik represents the distance of the defending individual to the intruder T i within the perception domain, where A unit vector representing a location vector of the individual D i to the intruder T i within the perception domain;
the random noise eta xi i represents random noise with the intensity eta > 0, and the random noise eta xi i is expressed as Is a random vector satisfying uniform distribution at [ -0.5,0.5] 2;
2) The cooperative rule of the individuals in the intrusion cluster is expressed as follows:
wherein, self-driving force The random noise eta zeta j is consistent with the expression of the defender, and only the parameter of the self-driving force of the invading individual, namely the maximum value beta of the speed is different from the self-driving force parameter alpha of the defending individual, wherein beta is more than alpha; the remaining items include location synergy items/>Individual intrusion item/>Anti-flooding item by item/>The specific expression is as follows:
The self-driving force
Wherein, beta represents the maximum value of the intrusion cluster speed, and beta is more than alpha, v j (t) is the intrusion cluster speed;
The position cooperative item
Wherein,A unit vector representing a neighbor individual to individual I j's location vector;
N j is a set of perceivable neighbors:
Nj＝{k|djk＜rsen,k∈{1,...,NI},k≠j}
Wherein d jk represents the inter-individual distance within the intrusion cluster, and r sen > 0 is the perceived radius of the intrusion cluster;
The individual intrusion item
A unit vector representing a position vector of the individual I j to the protected object;
the said anti-flooding item by item
T j is a set of perceivable defenders:
Tj＝{k|djk＜rsen,k∈{1,...,ND}}
N D represents a defensive cluster;
The random noise eta xi j represents random noise with the intensity eta > 0, and the random noise eta xi j is expressed as Is a random vector satisfying a uniform distribution at [ -0.5,0.5] 2.
A computer system, comprising: one or more processors, a computer-readable storage medium storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the methods described above.
A computer readable storage medium, characterized by storing computer executable instructions that when executed are configured to implement the method described above.
A computer program comprising computer executable instructions which when executed are adapted to implement the method described above.
Advantageous effects
The invention provides a cluster self-organizing control method for double-layer defense, which solves the problem of defending intrusion and countermeasure by using the cluster self-organizing control method. By means of the design of individual interaction mechanisms in the group and among the groups and the combination of a social force model, the motion state of the individual is updated, and finally self-organizing control of cluster defense is achieved. The defending clusters and the intrusion clusters respectively have different individual attributes and interaction strategies, wherein a defending potential field force is formed by constructing a defending potential field to realize a double-layer defending effect for the defending clusters, and a position cooperative item, a speed cooperative item, a self-driving item, a counter-intrusion item and a random noise item are also provided for the defending clusters, so that the invaders can be prevented from being intruded by setting different weight coefficients; for an intrusion cluster, a certain difference exists between a cooperative rule and a defense cluster, and main cooperative items comprise: the method comprises the steps of setting a cooperative item weight coefficient to complete an intrusion task. And (3) making a rule on the cooperative rules and the interaction strategies of the two-party clusters, further determining the defending cluster parameters according to the defending effect, and finally realizing successful cluster defending.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, like reference numerals being used to refer to like parts throughout the several views.
Figure 1 is a schematic diagram of a dual layer defensive loop potential field design.
FIG. 2 is a diagram of a simulation interface in the method of the present invention.
Figure 3 is a simulated view of a defensive sub-population forming a double layer defensive loop in the method of the invention.
Fig. 4 is a simulated view of the capture radius of an intruder into an defender in the method of the present invention.
Figure 5 is a simulated view of an intruder surrounded by inner and outer defensive subgroups in the method of the present invention.
Figure 6 is a simulation diagram of the successful defense of a defense cluster in the method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
The invention provides a cluster defense model capable of realizing defense intrusion countermeasure between two clusters, which ensures that the clusters can emerge cooperative defense behavior in the movement process and finally realizes effective self-organizing defense effect. The cluster defense system has the following characteristics:
1. Individuals in the group are isomorphic and have consistent rules. That is, the individual attributes in the same camping group are consistent, and the individual behavior rules are also the same. Where individual attributes include kinematic characteristics (maximum speed, maximum acceleration, etc.), perceptibility, capturing ability, etc.
2. Individual heterogeneous among groups and different rules. The individual attributes of different camps are different, such as the maximum speed and the maximum acceleration of the defender and the invader are different, and the perception level is also different, and specific parameters are shown in the table one.
3. All intra-group individuals are externally identical. That is, the identity of the individual cannot be identified through the external or signal, all the individuals are consistent in the cluster, and no specificity exists.
4. The individuals decide autonomously, and there is no centralized distribution. All individuals in the group are autonomously aware and autonomously update the individual states according to the cluster rule to make autonomous decisions, and no upper and lower levels or follow-up dependence exists among the individuals.
5. The antagonism between clusters is embodied in a captured form. The defender intercepts the invader to catch the invader until the invader enters the capturing radius of the defender, and the defender are simultaneously 'all-in-one' to represent the fight of the defender to the invader, and the invader escapes from the defender opposite to the defender to catch the protected object until the protected object enters the capturing radius of the invader, so that the fight of the invader is successful.
The defending cluster and the intrusion cluster are constructed according to the five-point characteristics, wherein the defending cluster is named as D and comprises N D individuals; the intrusion cluster is designated as I, which contains N I individuals; the protected object is named P. Wherein the position vector of the individual D i(i＝1,...,ND),Ij(j＝1,...,NI) isVelocity vector is/>Irrespective of the individual profile, the individual mass is assumed to be m=1. The individual satisfies newton's law of mechanics, where individual synergy is divided into intra-group and inter-group synergy. The defensive individual position speed update formula is as follows:
Where u i (t) represents the resultant force of the defending individual D i, where the resultant force and the acceleration are equivalent in magnitude because of the mass of 1, where u i (t) represents the acceleration of the defending individual D i. The invading individual position and speed updating formula is the same as the defending cluster updating formula, and the cooperative terms of the individuals in the two clusters are different, and the following description is given:
first, defend against the collaborative rules of individuals within a cluster, as follows:
Defensive clustering individual cooperative items include self-driven items Location synergy item/>Velocity synergistic term/>Potential field protection term/>Anti-intrusion item/>And random noise ηζ i. The specific rule settings are as follows:
(1) Self-driving item
Where α represents the maximum value of the velocity, |v i (t) | represents the velocity magnitude.
(2) Sports coordination item
Individual interactions are based on the motion state of a neighbor partner, assuming that an individual can perceive in real time the motion state information (location and speed) of a neighbor within a certain neighborhood. Wherein the perceived radius of the defending cluster is R sen > 0, the set of perceivable neighbors is:
Ni＝{k|dik＜Rsen,k∈{1,...,ND},k≠i} (4)
where d ik represents the distance between individuals within the defensive cluster.
The sports coordination items include location coordination itemsSum velocity synergistic term/>
Wherein the positional synergy term formula is as above, and the model is short-distance rejection-long-distance attraction-medium-distance rejection.Representing the balance position adjustment parameter of attraction force and repulsion force, wherein the repulsion force is represented when the individual interval is smaller than the value, and the attraction force is represented when the individual interval is larger than the value; representing the sub-group spacing, the repulsive force between sub-groups reaches a maximum when the individual spacing is equal to this value. /(I) A unit vector representing the location vector of neighbor individuals to individuals D i.
The speed cooperative term adopts an uneven rule, and neighbor individuals with the largest angle change are selected from the neighborsAnd references its velocity orientation.
(3) Potential field protection item
The double-layer defending potential field is constructed by combining with the artificial potential field theory, as shown in figure 1. The defenses are shown below:
wherein the defending individual perceives the protected object globally, d ip represents the distance of the defending individual to the protected object, A unit vector representing the position vector of the individual D i to the protected object. When defending individuals exist in different potential fields and are subjected to potential field forces in different directions, the positive and negative of the potential field protection force also correspond to two behaviors of approaching and separating from the protection object. Wherein the method comprises the steps ofRespectively, corresponds to the potential field boundary distance around the protection object as shown in fig. 1. The defending clusters thus eventually form a double-layered defending ring around the protected object.
(4) Anti-intrusion item
This is an inter-group interaction term, i.e., defending individuals interacting with invading individuals. The defending individual locally perceives the invading individual, the perceiving radius of the invading individual is R sen & gt 0, and the perceivable invader set is as follows:
Ti＝{k|dik＜Rsen,k∈{1,...,NI}} (8)
The anti-intrusion force is the resultant force direction of each intruder in the approaching perception range, and the distance from the intruder to the defender influences the corresponding weight, and the specific form is as follows:
Where d ik represents the distance of the defending individual to the intruder T i within the perception domain, where A unit vector representing the location vector of the individual D i to the intruder T i within the perception domain.
(5) Random noise
Eta xi i represents random noise with strength eta > 0, and makesIs a random vector satisfying a uniform distribution at [ -0.5,0.5] 2.
Then, the cooperative rule of the individuals in the intrusion cluster is expressed as follows:
Wherein the self-driving force The random noise eta zeta j is consistent with the expression of the defender, but the parameter of the self-driving force of the invading individual, namely the maximum value beta of the speed is different from the self-driving force parameter alpha of the defending individual, and the beta is generally larger than the alpha. The other items comprise position cooperative itemsIndividual intrusion item/>Anti-flooding item by item/>The specific expression is as follows:
(1) Location collaborative item
The intruder also has local perception, wherein the perceived radius of the intrusion cluster is r sen > 0, and the set of perceivable neighbors is:
Nj＝{k|djk＜rsen,k∈{1,...,NI},k≠j} (11)
The cooperation of the positions of the invading individuals and the neighbors in the perception domain thereof follows the principle of 'only exclusion', namely, the individuals are only collided, and no aggregation exists, and the specific expression is as follows:
(2) Individual intrusion item
The invading individual has an invasion trend to the protected object, and has an individual invasion force, which is specifically expressed as follows:
(3) Anti-flooding item-by-item
The method is an inter-group interaction item of an invading individual, namely the invading individual interacts with a defending individual. The invasion individuals are locally perceived by the defending individuals, the perception radius of the defending individuals is r sen & gt 0, and the perceivable defending person set is as follows:
Tj＝{k|djk＜rsen,k∈{1,...,ND}} (14)
The counter-driving progressive force is the resultant force direction away from each defender in the perception range, and meanwhile, the distance from the defender to the invader influences the corresponding weight, and the concrete form is as follows:
Simulation results
The algorithm is simulated, the simulation object consists of a defending cluster, an intrusion cluster and a protection object, and the simulation interface is shown in figure 2. According to the collaborative rule, the individual in the cluster updates the speed and the position information in real time, and the simulation result finally shows that in the cluster defense countermeasure, the defense cluster can spontaneously develop various defense behaviors, such as a defense subgroup forms a double-layer defense ring, an inner ring defense subgroup surrounds an attack invader, an outer ring directly strikes and captures the invader, the self-organizing defense of the cluster is finally successfully realized, and the specific effect is as shown in fig. 3-6, and the double-layer defense ring is formed again to cope with the next intrusion after the defense of the defense cluster is successful.
Table-cluster parameters
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made without departing from the spirit and scope of the invention.
Claims (4)
1. A cluster self-organizing control method of double-layer defense is characterized in that: setting a cooperative rule of an individual in a defending cluster and an individual in an intrusion cluster;
1) The cooperative rule of the individual in the defense cluster is expressed as follows:
Wherein, Is a self-driven item,/>For location collaborative item,/>Is a velocity synergistic term,/>Is a potential field protection term,/>As an anti-intrusion term, ηζ i is random noise;
the self-driving item
Wherein, alpha represents the maximum value of the defending cluster speed, and v i (t) represents the defending cluster speed;
The position cooperative item
Representing the balance position adjustment parameter of attraction force and repulsion force, wherein the repulsion force is represented when the individual interval is smaller than the value, and the attraction force is represented when the individual interval is larger than the value; /(I)Representing the subgroup spacing, the repulsive force between subgroups reaching a maximum when the individual spacing is equal to the value; /(I)A unit vector representing the location vector of neighbor individuals to individuals D i;
n i is a set of perceivable neighbors:
Ni＝{k|dik＜Rsen,k∈{1,...,ND},k≠i}
Wherein d ik represents the distance between individuals in the defensive cluster, and R sen > 0 is the perceived radius of the defensive cluster;
The speed cooperative item
Representing the speed of the neighbor individual with the largest angle change in the neighbors;
The potential field protection item
Wherein d ip represents the distance from the defending individual to the protected object,A unit vector representing a position vector of the individual D i to the protection object; /(I)Respectively corresponding to the boundary distances of potential fields surrounding the protection object;
the anti-intrusion item
T i is a set of perceivable intruders:
Ti＝{k|dik＜Rsen,k∈{1,...,NI}}
Wherein d ik represents the distance of the defending individual to the intruder T i within the perception domain, where A unit vector representing a location vector of the individual D i to the intruder T i within the perception domain;
the random noise eta xi i represents random noise with the intensity eta > 0, and the random noise eta xi i is expressed as Is a random vector satisfying uniform distribution at [ -0.5,0.5] 2;
2) The cooperative rule of the individuals in the intrusion cluster is expressed as follows:
wherein, self-driving force The random noise eta zeta j is consistent with the expression of the defender, and only the parameter of the self-driving force of the invading individual, namely the maximum value beta of the speed is different from the self-driving force parameter alpha of the defending individual, wherein beta is more than alpha; the remaining items include location synergy items/>Individual intrusion item/>Anti-flooding item by item/>The specific expression is as follows:
The self-driving force
Wherein, beta represents the maximum value of the intrusion cluster speed, and beta is more than alpha, v j (t) is the intrusion cluster speed;
The position cooperative item
Wherein,A unit vector representing a neighbor individual to individual I j's location vector;
N j is a set of perceivable neighbors:
Nj＝{k|djk＜rsen,k∈{1,...,NI},k≠j}
Wherein d jk represents the inter-individual distance within the intrusion cluster, and r sen > 0 is the perceived radius of the intrusion cluster;
The individual intrusion item
A unit vector representing a position vector of the individual I j to the protected object;
the said anti-flooding item by item
T j is a set of perceivable defenders:
Tj＝{k|djk＜rsen,k∈{1,...,ND}}
N D represents a defensive cluster;
The random noise eta xi j represents random noise with the intensity eta > 0, and the random noise eta xi j is expressed as Is a random vector satisfying a uniform distribution at [ -0.5,0.5] 2.
2. A computer system, comprising: one or more processors, a computer-readable storage medium storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of claim 1.
3. A computer readable storage medium, characterized by storing computer executable instructions that, when executed, are adapted to implement the method of claim 1.
4. A computer program comprising computer executable instructions which, when executed, are adapted to implement the method of claim 1.
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