CN114115347A - Multi-intelligent-agent distributed phase regulation and control and target tracking method in air under guidance of multiple closed paths - Google Patents
Multi-intelligent-agent distributed phase regulation and control and target tracking method in air under guidance of multiple closed paths Download PDFInfo
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Abstract
The invention discloses an aerial multi-agent distributed phase regulation and control and target tracking method under guidance of multiple closed paths, and relates to the technical field of aircraft guidance control. Firstly, aiming at the requirements of efficient and rapid detection and monitoring of an area/static target under a large-scale space scene, various parameters of an aerial intelligent agent are determined. And then establishing a distributed observer based on information interaction of adjacent aerial agents to realize asymptotic unbiased consistent estimation of the target position. Calculating parameters between various aerial agents and the target position again; a multi-intelligent-agent distributed phase regulation and target tracking method in the air under the guidance of a plurality of closed paths is constructed. And finally, the expected linear speed and the heading angular speed of the aerial multi-agent are derived. The invention constructs a distribution observer only depending on the interaction of adjacent agents, and eliminates the excessive dependence of the whole personnel on the target information broadcast communication; and the defects of insufficient timeliness, poor flexibility and the like of the single circular track surrounding control method facing the large-scale space scene observation task are overcome.
Description
Technical Field
The invention relates to the technical field of aircraft guidance control, in particular to an aerial multi-agent distributed phase regulation and control and target tracking method under guidance of multiple closed paths.
Background
In recent years, the problem of guidance of aerial multi-agent surrounding targets has attracted people's attention, and the main task is that under the drive of a control system, the aerial agents enter a desired track of the target from an arbitrary initial position and periodically and dynamically surround and detect along the track. The system is widely applied to military and civil fields, such as reconnaissance and detection, environment monitoring, information acquisition and the like. For a single airborne agent to be guided around an object, the airborne agent is typically required to surround the object at a prescribed desired radius and angular velocity. The essence of the airborne multi-agent distributed surround tracking control technique is to avoid the use of global information, to design the controller completely from measured initial information so that each airborne agent is kept at a distance from the target, and to be able to maintain the desired formation configuration along a circular track, compared to the single airborne agent case. Therefore, the collaborative surround guidance problem of a plurality of aerial intelligent agents has the advantages of flexibility, wide coverage range, good robustness and the like, and is widely concerned by military researchers and domestic and foreign experts.
In the existing surrounding tracking control technology, it is mostly assumed that each aerial agent can globally observe state information of a target, and due to communication resource constraints and frequent changes of spatial positions of the agents, it is difficult to ensure that all aerial agents can effectively access target information in real time, so how to realize distributed surrounding observation in a true sense on the premise that target information is globally unknown is a problem to be solved urgently in the current multi-agent field. Furthermore, most surround guidance research results achieve dynamic continuous surround observation of targets, primarily by deploying aerial multi-agents to form the desired formation along a common circular track. For the problem of efficient and rapid monitoring and detection of a fixed target in a large-scale and large-airspace task scene, the strategy has the defects of insufficient timeliness, poor flexibility and the like, and how to realize the multi-agent cooperative behavior on a multi-circular track through neighbor interaction and networking energization enhances the flexible observation occupation and efficient information acquisition capability, is an effective way for making up the defect of cooperative observation under guidance of a single circular track, and has great significance for executing efficient and rapid target detection, search, tracking and other tasks under the large-scale environmental characteristics.
Disclosure of Invention
The invention provides an aerial multi-agent distributed phase regulation and target tracking method under the guidance of multiple closed paths, aiming at solving the problems of efficient and rapid monitoring and detection of a fixed target in a large-scale and large-airspace task scene.
The invention is realized by the following technical scheme: a method for controlling and tracking a target by a plurality of aerial multi-agent distributed phases under guidance of closed paths comprises the following steps:
a) aiming at the requirements of efficient and rapid detection and monitoring of an area/static target in a large-scale space scene, the number of aerial intelligent bodies, the expected radius of a multi-circle orbit, the expected surrounding phase angle interval, the expected surrounding angular speed and the master-slave communication topological relation are determined. The method specifically comprises the following steps: determining the number N of aerial agents, the desired radius of the multi-circular orbit
Desired surrounding phase angle spacing
Desired angular velocity of the surround
Directed graph adjacency matrix A ═ a for describing master-slave communication topological relationij]N×NAnd B ═ diag { (B) }i}; wherein, aijIs the weight coefficient of communication between the aerial agents, if aijSay that air agent i can receive information from air agent j, otherwise, aij＝0；biIs the communication weight coefficient between the aerial agent i and the target, if b i1, say that the in-flight agent i can access and obtain the target location, otherwise, bi＝0。
b) Establishing a distributed observer based on information interaction of adjacent aerial intelligent agents based on an information consistency principle according to the communication topological relation obtained in the step a)
To achieve asymptotic unbiased consistent estimation of the target position.
The calculation is as follows:
wherein the content of the first and second substances,
for an aerial agent i to estimate the target location,
estimate of target position, P, for airborne agent js＝[xs,ys]TIs the actual position of the target, g1And g2Is a positive control gain.
c) Combining the results obtained in the steps a) and b), and calculating a line-of-sight angle between the aerial agent and the target position estimation, a unit vector in the direction of a connecting line between the aerial agent and the target position estimation, and a unit vector in the direction orthogonal to the connecting line between the aerial agent and the target position estimation by contrasting the target position estimation and the relative geometry of the aerial agent; by introducing relative distance error feedback in a radial channel and introducing cooperative error based on surrounding phase angle distance in a tangential channel, a method for controlling and tracking the distributed phase of the aerial multi-agent under the guidance of a plurality of closed paths is constructed. The method comprises the following specific steps:
c1) calculating the line-of-sight angle theta of the aerial agent i and the target position estimatei(t)：
Wherein, Pi(t)＝[xi(t),yi(t)]TThe position of an aerial agent i under an inertial system;
next, a unit vector alpha in the direction of the connecting line between the aerial agent i and the target position estimation is calculatedi(t) and unit vector in orthogonal direction βi(t)：
Wherein the content of the first and second substances,
for vectors, matrices, estimated for pointing to a target location by an airborne agent i
c2) Constructing a cooperative error based on the phase angle spacing by combining the communication relation of the adjacent aerial intelligent agents determined in the step a)
c3) By introducing relative distance error feedback into a radial channel and introducing a cooperative error based on a surrounding phase angle distance into a tangential channel, a plurality of closed paths are formed to guide an air intelligent agent i distributed phase regulation and control law with target tracking control:
wherein the content of the first and second substances,
for the distance, k, between the airborne agent i and the target location estimate1For a positive gain in the relative distance error,
for the co-error term with saturation operator, h0Control gain > 0; u. ofi(t)＝[uix(t),uiy(t)]T，uix(t) and uiy(t) are respectively the control laws ui(t) velocity components along the x-axis and y-axis under the inertial system.
d) And c) deriving the expected linear speed and the course angular speed of the aerial multi-agent based on the vector synthesis and the proportional differential control principle according to the result obtained in the step c). The method comprises the following specific steps:
generating linear velocity instruction v of air agent i based on vector synthesis principlei(t) and heading angle command
Then, based on the proportional-derivative control principle, deriving a course angular velocity command omega of the aerial intelligent agent ii(t)：
Wherein k is2And the course angle error gain is more than 0.
Compared with the prior art, the invention has the following beneficial effects: the invention provides a method for controlling the distributed phase and tracking the target of a plurality of aerial multi-agent under the guidance of a plurality of closed paths, (1) different from the prior collaborative surrounding observation scheme, the realization mostly needs to assume that the global target information is known, and the distributed attribute of the whole system is essentially destroyed; (2) according to the invention, a cooperative observation mode that a plurality of intelligent agents regulate and control as required along a plurality of closed paths and surrounding angle intervals is adopted, so that the defects of insufficient timeliness, poor flexibility and the like of a single circular track surrounding control method when a large-scale space scene observation task is oriented are overcome.
Drawings
FIG. 1 is a block diagram of the control architecture of the present invention.
Fig. 2 is a master-slave directed communication topology to which the present invention relates.
Fig. 3 is a schematic diagram of the relative geometry of an airborne multi-agent and target to which the present invention relates.
Fig. 4 illustrates three trajectory profiles of the airborne multi-agent in transient convergence to a predetermined multi-circular orbit, phase adjustment along multiple circular orbits, and formation of a desired phase distribution.
Detailed Description
The invention is further described with reference to the drawings and the specific embodiments.
A method for multi-agent distributed phase regulation and target tracking in the air under guidance of multiple closed paths is disclosed, as shown in FIG. 1, and comprises the following steps:
a) aiming at the requirements of efficient and rapid detection and monitoring of an area/static target in a large-scale space scene, the number of aerial intelligent bodies, the expected radius of a multi-circle orbit, the expected surrounding phase angle interval, the expected surrounding angular speed and the master-slave communication topological relation are determined. The method specifically comprises the following steps: determining the number N of aerial agents and the expected radius rho of the multi-circle orbitdiDesired surrounding phase angle spacing
Desired angular velocity of the surround
Directed graph adjacency matrix A ═ a for describing master-slave communication topological relationij]N×NAnd B ═ diag { (B) }i}; wherein, aijIs the weight coefficient of communication between the aerial agents, if aijSay that air agent i can receive information from air agent j, otherwise, aij＝0；biIs the communication weight coefficient between the aerial agent i and the target, if b i1, say that the in-flight agent i can access and obtain the target location, otherwise, b i0. In the communication topology shown in fig. 2, where 0 represents the target, 1-10 represent the airborne agent, the adjacency matrices a and B may be determined as:
B＝diag{1 0 0 0 0 0 0 0 0 0}
b) establishing a distributed observer based on information interaction of adjacent aerial intelligent agents based on an information consistency principle according to the communication topological relation obtained in the step a)
To achieve asymptotic unbiased consistent estimation of the target position.
The calculation is as follows:
wherein the content of the first and second substances,
for an aerial agent i to estimate the target location,
estimate of target position, P, for airborne agent js＝[xs,ys]TIs the actual position of the target, g1And g2Is a positive control gain.
c) Combining the results obtained in the steps a) and b), and calculating a line-of-sight angle between the aerial agent and the target position estimation, a unit vector in the direction of a connecting line between the aerial agent and the target position estimation, and a unit vector in the direction orthogonal to the connecting line between the aerial agent and the target position estimation by contrasting the target position estimation and the relative geometry of the aerial agent; by introducing relative distance error feedback in a radial channel and introducing cooperative error based on surrounding phase angle distance in a tangential channel, a method for controlling and tracking the distributed phase of the aerial multi-agent under the guidance of a plurality of closed paths is constructed. The method comprises the following specific steps:
c1) Calculate the line-of-sight angle θ between the airborne agent i and the target location estimate as shown in FIG. 3i(t)：
Wherein, Pi(t)＝[xi(t),yi(t)]TThe position of an aerial agent i under an inertial system;
next, a unit vector α in the direction connecting the airborne agent i and the target position estimate as shown in FIG. 3 is calculatedi(t) and unit vector in orthogonal direction βi(t)：
Wherein the content of the first and second substances,
for vectors, matrices, estimated for pointing to a target location by an airborne agent i
c2) Constructing a cooperative error based on the phase angle spacing by combining the communication relation of the adjacent aerial intelligent agents determined in the step a)
c3) By introducing relative distance error feedback into a radial channel and introducing a cooperative error based on a surrounding phase angle distance into a tangential channel, a plurality of closed paths are formed to guide an air intelligent agent i distributed phase regulation and control law with target tracking control:
wherein the content of the first and second substances,
for the distance, k, between the airborne agent i and the target location estimate1For a positive gain in the relative distance error,
for the co-error term with saturation operator, h0Control gain > 0; u. ofi(t)＝[uix(t),uiy(t)]T，uix(t) and uiy(t) are respectively the control laws ui(t) velocity components along the x-axis and y-axis under the inertial system.
d) And c) deriving the expected linear speed and the course angular speed of the aerial multi-agent based on the vector synthesis and the proportional differential control principle according to the result obtained in the step c). The method comprises the following specific steps:
generating linear velocity instruction v of air agent i based on vector synthesis principlei(t) and heading angle command
Then, based on the proportional-derivative control principle, deriving a course angular velocity command omega of the aerial intelligent agent ii(t)：
Wherein k is2And the course angle error gain is more than 0.
e) Simulating the method for controlling the distributed phase and tracking the target of the multi-agent in the air under the guidance of a plurality of closed paths, wherein the number of agents is 10, and the radius of a circular closed orbit corresponding to an agent i in the air is [ 1,2,4,7,8 ] is rhod1And the radius of the circular closed orbit corresponding to the aerial agent i ═ {3,6,9} is rhod2And the radius of the circular closed orbit corresponding to the aerial intelligent agent i ═ {5,10} is rhod3The specific parameters are set as follows:
e1) the task scene parameters for determining the multi-circular orbit observation are shown in table 1.
TABLE 1 mission scene parameters for multi-circular orbit observations
e2) Determining an initial position P of each airborne agent under an inertial systemi(0) Initial heading angle psii(0) As shown in table 2.
TABLE 2 aerial Multi-agent initial parameters
e3) The tuning parameters for the controller were determined as shown in table 3.
TABLE 3 controller parameters
e4) The simulation result is shown in fig. 4, (a) is the situation that the transient state of 10 aerial agents converges to the preset multi-circle orbit; (b) the method is used for the situation that 10 aerial agents are subjected to phase adjustment along a plurality of circular tracks; (c) the case of the desired phase distribution is formed for 10 airborne agents.
The scope of the invention is not limited to the above embodiments, and various modifications and changes may be made by those skilled in the art, and any modifications, improvements and equivalents within the spirit and principle of the invention should be included in the scope of the invention.
Claims (5)
1. A method for controlling and tracking a target by a plurality of aerial multi-agent distributed phases under guidance of closed paths is characterized by comprising the following steps: the method comprises the following steps:
a) aiming at the requirements of efficient and rapid detection and monitoring of an area/static target in a large-scale space scene, determining the number of aerial intelligent bodies, an expected multi-circle track radius, an expected surrounding phase angle interval, an expected surrounding angular velocity and a master-slave communication topological relation;
b) establishing a distributed observer based on adjacent air intelligent agent information interaction according to the communication topological relation obtained in the step a) and based on an information consistency principle so as to realize asymptotic unbiased consistent estimation of a target position;
c) combining the results obtained in the steps a) and b), and calculating a line-of-sight angle between the aerial agent and the target position estimation, a unit vector in the direction of a connecting line between the aerial agent and the target position estimation, and a unit vector in the direction orthogonal to the connecting line between the aerial agent and the target position estimation by contrasting the target position estimation and the relative geometry of the aerial agent; by introducing relative distance error feedback in a radial channel and introducing a cooperative error based on a surrounding phase angle distance in a tangential channel, an aerial multi-agent distributed phase regulation and target tracking method under the guidance of a plurality of closed paths is constructed;
d) and c) deriving the expected linear speed and the course angular speed of the aerial multi-agent based on the vector synthesis and the proportional differential control principle according to the result obtained in the step c).
2. The multi-closed-path-guided airborne multi-agent distributed phase regulation and target tracking method of claim 1, wherein: the step a) is as follows:
determining the number N of aerial intelligent bodies and the expected radius of a multi-circle orbit according to the requirements of efficient and rapid detection and monitoring of regional/static targets in a large-scale space scene
Desired surrounding phase angle spacing
Desired angular velocity of the surround
Directed graph adjacency matrix A ═ a for describing master-slave communication topological relationij]N×NAnd B ═ diag { (B) }i}; wherein, aijIs the weight coefficient of communication between the aerial agents, if aijSay that air agent i can receive information from air agent j, otherwise, aij＝0；biIs the communication weight coefficient between the aerial agent i and the target, if bi1, say that the in-flight agent i can access and obtain the target location, otherwise, bi＝0。
3. The multi-closed-path-guided airborne multi-agent distributed phase regulation and target tracking method of claim 1, wherein: the step b) is as follows:
establishing a distributed observer based on information interaction of adjacent aerial intelligent agents according to the communication topological relation determined in the step a) and based on the principle of information consistency
Wherein the content of the first and second substances,
for an aerial agent i to estimate the target location,
estimate of target position, P, for airborne agent js＝[xs,ys]TIs the actual position of the target, g1And g2Is a positive control gain.
4. The multi-closed-path-guided airborne multi-agent distributed phase regulation and target tracking method of claim 1, wherein: the step c) is as follows:
c1) combining the results obtained in the steps a) and b), and calculating the line-of-sight angle theta between the aerial agent i and the target position estimation by contrasting the target position estimation and the relative geometry of the aerial agenti(t)：
Wherein, Pi(t)＝[xi(t),yi(t)]TThe position of an aerial agent i under an inertial system;
next, a unit vector alpha in the direction of the connecting line between the aerial agent i and the target position estimation is calculatedi(t) and unit vector in orthogonal direction βi(t)：
Wherein the content of the first and second substances,
for vectors, matrices, estimated for pointing to a target location by an airborne agent i
c2) Constructing a cooperative error based on the phase angle spacing by combining the communication relation of the adjacent aerial intelligent agents determined in the step a)
c3) By introducing relative distance error feedback into a radial channel and introducing a cooperative error based on a surrounding phase angle distance into a tangential channel, a plurality of closed paths are formed to guide an air intelligent agent i distributed phase regulation and control law with target tracking control:
wherein the content of the first and second substances,
for the distance, k, between the airborne agent i and the target location estimate1For a positive gain in the relative distance error,
for the co-error term with saturation operator, h0Control gain > 0; u. ofi(t)＝[uix(t),uiy(t)]T，uix(t) and uiy(t) are respectively the control laws ui(t) velocity components along the x-axis and y-axis under the inertial system.
5. The multi-closed-path-guided airborne multi-agent distributed phase regulation and target tracking method of claim 1, wherein: the step d) is as follows:
generating a linear velocity command v of the aerial agent i based on a vector synthesis principle according to the result obtained in the step c)i(t) and heading angle command ψdi(t), and then deriving a course angular velocity command omega of the aerial intelligent agent i based on a proportional-derivative control principlei(t)：
Wherein k is2＞0Is the heading angle error gain.
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