CN114115334B - Multi-agent formation control method under view angle constraint condition - Google Patents
Multi-agent formation control method under view angle constraint condition Download PDFInfo
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Abstract
The multi-agent formation control method under the view angle constraint condition comprises the steps of establishing an agent system model; constructing an angular velocity controller of the azimuth intelligent agent based on the intelligent agent system model; the angular velocity controller of the azimuth intelligent body is utilized to control the azimuth intelligent body to meet the constraint condition of the view angle; under the condition that the azimuth intelligent body meets the view angle constraint condition, establishing a linear speed control law of the azimuth intelligent body according to the position of the azimuth intelligent body; a distance agent switching function is designed, and a linear speed control law of the distance agent is built according to the switching function and the multi-agent system model; and controlling the formation of multiple intelligent agents under the constraint condition of the view angle according to the linear speed control law of the azimuth intelligent agent and the linear speed control law of the distance intelligent agent. Under the condition that the intelligent agent only has azimuth information and no position information or distance information, the intelligent agent can select relatively fewer paths to move from an unexpected side to a desired side, and finally move to a desired position, so that formation, maintenance and transformation of multi-intelligent agent formation under the view angle constraint condition are realized.
Description
Technical Field
The invention belongs to the technical field of multi-agent control, and particularly relates to a multi-agent formation control method under a view angle constraint condition.
Background
In recent years, due to a great deal of practical application of multi-agent cooperative control in the aspects of search and rescue in complex dangerous environments, cooperative operation in industrial production, entertainment performance of agents and the like, research on multi-agent cooperative control is widely focused in academia and industry. When a search task is executed in a complex environment, the multi-agent formation technology plays an important role in expanding the search range, improving the search efficiency and improving the accuracy of target identification; when the intelligent agent flies at high altitude, the formation flying can not only enhance the stability of the system, but also reduce the overall energy consumption. Thus, there has been a great deal of research on formation formations. However, most of the studies are ideal, and there are few limitations on the measurement range, for example, cameras commonly used for acquiring azimuth information are usually not omni-directional but have a certain viewing angle.
Aiming at the formation control problem under the view angle constraint condition, the following main solutions exist: scheme 1: in reference "Li X,Tan Y,Mareels I,et al.Compatible formation set for uavs with visual sensing constraint[C].In 2018 Annual American Control Conference(ACC),2018:2497–2502.", by introducing the concept of barrier function (barrier function), it is ensured that the neighbor agent is always in the view range during the movement of the agent, but this method assumes that the view angle is 300 ° and the view distance is sufficiently large (i.e. the view distance limitation can be eliminated), so as to ensure that the entire formation topology is fully connected, and it is required that each agent can acquire the relative position information of the neighbor agent. The designed control method realizes formation and maintenance of the formation.
Scheme 2: the literature "Frank D, zelazo D,F.Bearing-only formation control with limited visual sensing:Two agent case[J].IFAC-PapersOnLine,2018,51(23):28–33." And on the basis of azimuth control, under the condition that two intelligent agents are considered, adding orientation angle control to ensure that the other intelligent agent is always at the central position of the view angle, thereby completing the formation task. The designed control method can realize formation and maintenance of the formation.
Scheme 3: in literature "Renaud P,Cervera E,Martiner P.Towards a reliable vision-basedmobile robot formation control[C].In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS),2004:3176–3181.", a reliable visual-based formation control method is proposed under the visual-based condition, and a pilot following control strategy is adopted to realize the in-line formation motion of a plurality of robots.
Disclosure of Invention
The invention overcomes one of the defects of the prior art, provides a multi-agent formation control method under the view angle constraint condition, and can enable an agent to select relatively fewer paths to move from an unexpected side to a desired side under the condition that the agent only has azimuth information and no position information or distance information, finally move to a desired position, thereby realizing formation, maintenance and transformation of the multi-agent formation under the view angle constraint condition.
According to an aspect of the present disclosure, the present invention provides a multi-agent formation control method under a view angle constraint condition, the method including:
Establishing an intelligent system model, wherein the intelligent body comprises a azimuth intelligent body and a distance intelligent body;
constructing an angular velocity controller of the azimuth intelligent agent based on the intelligent agent system model;
Controlling the azimuth intelligent body to meet the view angle constraint condition by utilizing an angular speed controller of the azimuth intelligent body;
under the condition that the azimuth intelligent body meets the view angle constraint condition, establishing a linear speed control law of the azimuth intelligent body according to the position of the azimuth intelligent body;
Designing the switching function of the distance intelligent agent, and establishing a linear speed control law of the distance intelligent agent according to the switching function and the multi-intelligent agent system model;
and controlling the formation of the multiple intelligent agents under the constraint condition of the view angles according to the linear speed control law of the azimuth intelligent agent and the linear speed control law of the distance intelligent agent.
In one possible implementation, the agent system model is:
wherein z i (k+1) and Representing the positions of two adjacent times of the intelligent agent,/>Is the control input of the linear velocity of the intelligent body, T is the time of a material sample,/>The angle of orientation of the agent at two times, u ω (k), is the control input for the agent angular velocity.
In one possible implementation, the building an angular velocity controller of an azimuth agent based on the agent system model includes:
Establishing a perception orientation model of the orientation agent based on the agent system model;
calculating an included angle between the actual orientation and the expected orientation of the azimuth intelligent body according to the perception azimuth model;
and constructing an angular speed controller of the azimuth intelligent body according to the included angle between the actual direction and the expected direction of the azimuth intelligent body.
In one possible implementation, the view angle constraint is the view angle θ f ε (0, pi).
In one possible implementation, the location of the azimuthal agent is divided into a desired side and an undesired side;
The linear speed control law u of the azimuth intelligent agent is as follows:
Wherein g is a discriminant function of the position of the azimuth intelligent agent, and f (k) affects the linear velocity control law of the azimuth intelligent agent when the position of the azimuth intelligent agent is at a desired side; when the position of the position agent is on the undesired side, (1-g) affects the linear velocity control law of the position agent.
In one possible implementation, the f (k) = -k (θ (k) - θ *), where θ (k) is the controlled angle of the azimuthal agent, and θ * (k) represents the desired controlled angle.
In one possible implementation, the distance agent switching functionWhere S is the signed area and S * is the desired signed area.
The multi-agent formation control method under the view angle constraint condition comprises the steps of establishing an agent system model, wherein the agents comprise azimuth agents and distance agents; constructing an angular velocity controller of the azimuth intelligent agent based on the intelligent agent system model; the angular velocity controller of the azimuth intelligent body is utilized to control the azimuth intelligent body to meet the constraint condition of the view angle; under the condition that the azimuth intelligent body meets the view angle constraint condition, establishing a linear speed control law of the azimuth intelligent body according to the position of the azimuth intelligent body; a distance agent switching function is designed, and a linear speed control law of the distance agent is built according to the switching function and the multi-agent system model; and controlling the formation of multiple intelligent agents under the constraint condition of the view angle according to the linear speed control law of the azimuth intelligent agent and the linear speed control law of the distance intelligent agent. Under the condition that the intelligent agent only has azimuth information and no position information or distance information, the intelligent agent can select relatively fewer paths to move from an unexpected side to a desired side, and finally move to a desired position, so that formation, maintenance and transformation of multi-intelligent agent formation under the view angle constraint condition are realized.
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The accompanying drawings are included to provide a further understanding of the technical aspects or prior art of the present application, and are incorporated in and constitute a part of this specification. The drawings, which are used to illustrate the technical scheme of the present application, are not limited to the technical scheme of the present application.
FIG. 1 illustrates a flow chart of a multi-agent formation control method under view angle constraints in accordance with an embodiment of the present disclosure;
FIG. 2 illustrates a schematic diagram of 3 agent formations under view angle constraints in accordance with an embodiment of the present disclosure;
FIG. 3 illustrates a schematic diagram of the motion relationship of 3 agents at any two adjacent moments under view angle constraints in accordance with an embodiment of the present disclosure;
FIG. 4 illustrates a view angle in accordance with an embodiment of the present disclosure Forming a schematic diagram by 3 agent formation under constraint conditions;
FIG. 5 illustrates a view angle in accordance with an embodiment of the present disclosure Forming a process error curve schematic diagram by 3 agent formation under constraint conditions;
FIG. 6 illustrates a view angle in accordance with an embodiment of the present disclosure Forming a schematic diagram by 3 agent formation under constraint conditions;
FIG. 7 illustrates a view angle in accordance with an embodiment of the present disclosure Forming a process error curve schematic diagram by 3 agent formation under constraint conditions;
FIG. 8 illustrates a schematic formation of an initial position of position number 2 agent near distance number 3 agent in accordance with an embodiment of the present disclosure;
FIG. 9 illustrates a schematic diagram of formation errors when an initial position of a position number 2 agent approaches a distance number 3 agent, in accordance with an embodiment of the present disclosure;
FIG. 10 illustrates a schematic formation of an initial position of a position number 2 agent on a desired side in accordance with an embodiment of the present disclosure;
FIG. 11 illustrates a schematic of formation errors for an initial position of position number 2 agent on a desired side in accordance with an embodiment of the present disclosure;
FIG. 12 illustrates a multi-agent formation and transformation process schematic under view angle constraints in accordance with an embodiment of the present disclosure;
fig. 13 illustrates an angular error and side-to-side yearly-conversation schematic during multi-agent formation under view angle constraints in accordance with an embodiment of the present disclosure.
Detailed Description
The following will describe embodiments of the present application in detail with reference to the drawings and examples, thereby solving the technical problems by applying technical means to the present application, and realizing the corresponding technical effects can be fully understood and implemented accordingly. The embodiment of the application and the characteristics in the embodiment can be mutually combined on the premise of no conflict, and the formed technical scheme is within the protection scope of the application.
The multi-agent formation control method under the view angle constraint condition considers the movement of the multi-agent at the same height (two-dimensional plane) and aims at the multi-agent triangular formation control problem under the view angle constraint condition. The method considers the situation that a plurality of intelligent agents can acquire the information of the expected formation specified by the direction and the distance, and adds a view angle constraint condition to the intelligent agents capable of measuring the direction. The angular velocity controller is designed to ensure that the intelligent body can always see the neighbor intelligent body, and on the basis, the intelligent body capable of measuring azimuth information and distance information is respectively designed to control the velocity so that the intelligent body can move to a desired position.
The invention respectively carries out control law design on the intelligent body capable of sensing the azimuth information and the distance information. For the intelligent body for measuring azimuth, the control law design is divided into angular speed control and speed control, wherein the angular speed ensures that the view angle constraint is satisfied, and the speed control ensures that the intelligent body moves to a desired position.
Fig. 1 shows a flow chart of a multi-agent formation control method under view angle constraints in accordance with an embodiment of the present disclosure. The method can be used in a process of forming a team of multiple intelligent agents with azimuth intelligent agents and distance intelligent agents, and the following description will take 1 azimuth intelligent agent and 2 distance intelligent agents as examples. As shown in fig. 1, the method may include:
Step S1: and establishing an intelligent system model, wherein the intelligent body comprises an azimuth intelligent body and a distance intelligent body.
Fig. 2 shows a schematic diagram of 3 agent formations under view angle constraints in accordance with an embodiment of the present disclosure.
As shown in fig. 2, the multiple agents move at the same height (i.e., two-dimensional plane), for convenience of description, 1 azimuth agent is labeled as No. 1, and 2 distance agents are labeled as No. 1 and No. 3, respectively.
In one example, the agent system model is:
wherein z i (k+1) and Representing the positions of two adjacent times of the intelligent agent,/>Is the control input of the linear velocity of the intelligent body, T is the time of a material sample,/>The angle of orientation of the agent at two times, u ω (k), is the control input for the agent angular velocity.
For writing convenience, letzi＝zi(k),ui＝ui(k)，/>U ω＝uω (k). Thus, the intelligent architecture model may be expressed as follows:
step S2: and constructing an angular velocity controller of the azimuth intelligent agent based on the intelligent agent system model.
In an example, this step may specifically include:
Establishing a perception azimuth model of an azimuth intelligent agent based on the intelligent agent system model; calculating an included angle between the true orientation and the expected orientation of the azimuth intelligent agent according to the perception azimuth model; and constructing an angular speed controller of the azimuth intelligent body according to the included angle between the true orientation and the expected orientation of the azimuth intelligent body.
For example, the azimuth-2 agent perception azimuth model shown in fig. 2 is:
Wherein b 2i (k) is the azimuth, i.e. the azimuth No. 2 agent can perceive the azimuth of No. 1 distance agent and No. 3 distance agent as b 21 and b 23, respectively, and the values of b 21 and b 23 can be obtained according to equation 3.
Under such constraint, the neighbor agent (distance 1 intelligent mention and distance 3 agent in fig. 2) is within the field of view of the azimuth agent No.2, and the following formula is required to be satisfied:
Order the Representing the orientation of the head of the intelligent agent,/>Representing the transposition of the positions of agent # 2 and agent # 1,/>Representing the transposition of the positions of agent # 2 and agent # 3, then/>(5), OrderRepresenting a desired orientation corresponding to the agent, corresponding/>Wherein/>For the expected orientation, according to formula (3) and formula (6), can obtain the position that No. 2 intelligent agent can be perceived that No. 1 is apart from intelligent mention and No. 3 is apart from intelligent agent:
the included angle between the actual orientation and the expected orientation of the azimuth intelligent agent can be calculated according to the formula (6) and the formula (7) The method comprises the following steps:
Wherein, The method is as follows:
That is, the angle between the desired direction and the current direction of the azimuthal agent is directional, the direction being the desired direction pointing toward the current direction, and here, the counterclockwise direction is positive and the clockwise direction is negative.
Because of the view angle theta f, ensuring that the azimuth number agent can see the neighbor distance agent is a primary task, the direction angle, i.e. the diagonal speed controller, is controlled first.
U ω is designed as follows: where k w is a positive control gain.
Through the angular velocity controller of design position intelligent object for the position intelligent object satisfies the view angle constraint throughout, and then guarantees that neighbor distance intelligent object remains throughout in the field of view, has guaranteed that azimuth measurement information can not lose.
Step S3: and controlling the azimuth intelligent body to meet the view angle constraint condition by using an angular speed controller of the azimuth intelligent body.
Step S4: under the condition that the azimuth intelligent body meets the view angle constraint condition, establishing a linear speed control law of the azimuth intelligent body according to the position of the azimuth intelligent body;
the position of the azimuth intelligent agent is divided into a desired side and an undesired side, and different control inputs are acted on different sides.
In one example, the linear velocity control law u for the azimuth agent is:
Wherein g is a discriminant function of the position of the azimuth intelligent agent, f (k) affects the linear velocity control law of the azimuth intelligent agent when the position of the azimuth intelligent agent is at the expected side, and finally the azimuth intelligent agent can move to the expected balance point; when the position of the position agent is on the undesired side, (1-g) affects the linear velocity control law of the position agent, which selects the detour mode to move to the desired side.
In one example, the design f (k) = -k (θ (k) - θ *) equation (12), where θ (k) is the controlled angle of the azimuthal agent, and θ * (k) represents the desired controlled angle.
For example, the azimuth angle measured by the azimuth agent is phi j (k) ∈ [0,2 pi)/(U-1), the counterclockwise direction is positive and the clockwise direction is negative from the X-axis direction of the local coordinate system of the azimuth agent, wherein "-1" means that the azimuth agent cannot observe the j-th agent in its field of view.
Introducing the auxiliary angular variable delta (k), then:
Delta (k) =phi 21(k)-φ23 (k) formula (13),
The controlled angle θ (k) is:
the following takes three agents as shown in fig. 2 as an example to design a linear velocity control law, and the controlled angles of the No. 2 azimuth agents can be known by the formula (15):
Introducing the auxiliary variable ψ (k), then ψ (k) =φ 23(k)+γ2θ2 (k) equation (16), where γ 2 is a positive constant coefficient and satisfies 0< γ 2 <1, typically γ 2 is chosen to be 0.5.
Introducing a direction vector b ⊥ (k) perpendicular to the current direction, as shown in FIG. 2, then
Beta 2 (k) to be designed is:
Where h 1 is a function of b (k-1) x b ⊥ (k-1), calculated as follows:
the judgment function g is introduced to judge whether the intelligent agent in the No. 2 azimuth is on the expected side, and the judgment method is as follows:
Here, it is specified that when the azimuth No. 2 agent is judged to be on the undesired side, the initial movement direction is to move toward the azimuth No.1 agent side, as shown by b ⊥ (k) in fig. 2.
Auxiliary variables η (k) and ε (k) are introduced, η (k) being defined as follows:
η (k) =h 2(b(k)×b21 (k)) formula (21),
The calculation method of h 2 is the same as that of h 1, and will not be described here. From equation (21), the auxiliary variable e (k) can be obtained,
A rotation matrix R (k) = e (k) ×r is defined, wherein,Thus, b ⊥ (k) =r (k) ×b (k) formula (23).
Fig. 3 illustrates a schematic diagram of the movement relationship of 3 agents at any two adjacent moments under a view angle constraint according to an embodiment of the present disclosure.
As shown in fig. 3, Δl >0 is the distance between two times at which the No. 2 bearing agent moves, and d 21 and d 23 are the distances at time k+1.
As can be seen from fig. 3, the calculation results from the triangle geometry relation:
wherein alpha 21 is the current moment of the No.2 intelligent agent and the included angle formed by the position of the next moment and the No. 1 intelligent agent, alpha 23 is the current moment of the No.2 intelligent agent and the included angle formed by the position of the next moment and the No. 3 intelligent agent, and the included angle can be obtained by the sine theorem:
Wherein Δl is the distance between the current time of the No.2 agent and the position at the next time, edges D 23 (k+1) and D 21 (k+1) represent the distances between the No.2 agent and the No. 3 and No. 1 agents at the next time, respectively, and their difference Δd is:
Since Δl is greater than zero, it is apparent that the sign of Δd is determined by the latter term. The latter term is defined as Δd, expressed as follows:
The corresponding direction of movement on the nearer side can be selected according to the sign of ad.
The linear speed control law of the intelligent agent in the No. 2 azimuth is as follows:
Where k 2 and k g are both control gains greater than zero, sgn (Δd) is as follows:
When the initial position of the No. 2 azimuth intelligent agent is at the unexpected side, a closer path can be selected to fly to the expected side through the action of the formula (28), and the intelligent agent finally moves to the expected point after arriving at the expected side.
The view angle constraint problem is resolved into an angular velocity control problem and a linear velocity control problem by an agent capable of acquiring an azimuth. The angular velocity controller is designed to ensure that the intelligent body always meets the view angle constraint, so that the neighbor intelligent body always keeps in the view range, and the azimuth measurement information is ensured not to be lost. Under the premise of meeting the view angle constraint, according to different initial positions of the intelligent body, namely the initial position on the expected side and the unexpected side, the speed control is divided into two cases, the control laws are respectively designed, the switching function is designed, and the switching of the two control laws is realized, so that formation and conversion of formation can be realized, and the intelligent body can select a relatively close path to move from the unexpected side to the expected side on the premise of no position and distance information.
Step S5: and designing a distance agent switching function, and establishing a linear speed control law of the distance agent according to the switching function and the multi-agent system model.
For an agent capable of measuring relative distance information, a concept of a signed area is introduced, a discriminant function is designed, movement is started only when the agent measuring the azimuth is on a desired side, and control of the desired distance is finally realized.
Taking the distance 1 agent and the distance 3 agent shown in fig. 2 as an example, in order to ensure that the distance 2 agent can move to a desired side. It is necessary that the No. 1 and No. 3 distance agents are in a stationary state when the No. 2 azimuth agent is on the undesired side, and eventually move to the desired equilibrium point when the No. 2 azimuth agent moves to the desired side.
For this purpose, a signed area S is first introduced, and the signed triangle area calculation method is as follows:
In the method, in the process of the invention, The sign of S is determined by the order of z 1、z2 and z 3. When the sequence is anticlockwise, S is positive, whereas S is negative. A triangle that is unique and whose vertex order is also uniquely determined can be determined by equation (31). The desired signed triangle area S is calculated as follows:
Where a ε {1, -1}, when z 1、z2 and z 3 are arranged counterclockwise, a=1, when arranged clockwise, a= -1,
A distance agent switching function f (S) is defined based on the signed area S and the desired signed area S,
Thus, controllers of intelligent agents No. 1 and No. 3 were obtained in the form as follows:
Where k i >0 is a control gain.
Combining step 1, the total control law of three intelligent agents can be obtained:
Where k i >0 is a constant.
Step S6: and controlling the formation of the multiple intelligent agents under the constraint condition of the view angles according to the linear speed control law of the azimuth intelligent agent and the linear speed control law of the distance intelligent agent.
The multi-agent formation control method is subjected to simulation and physical experiment. Due to the existence of the view angle constraint, let k=0, the parameters at k=0 set as follows:
wherein e >0, and is small enough;
sgn(Δd)＝1。
Three sets of simulation experiments were performed below for the following three cases. The three cases are respectively:
(1) Different viewing angle sizes, i.e. And/>
(2) Different initial positions of the undesired side. Namely, the initial position is close to the No.1 intelligent agent and the initial position is close to the No. 3 intelligent agent respectively;
(3) The initial position is on the desired side and the undesired side.
Simulation one: different viewing angle size constraints
FIGS. 4 and 5 respectively illustrate the angular view in accordance with an embodiment of the present disclosure3 Agents under constraint form a schematic diagram and form an error curve schematic diagram.
At the position ofUnder the condition that the size of the view angle is set as/>Desired angle/>Initial positions of the No. 1, no. 2 and No. 3 agents are/>, respectivelyAnd/>The formation process of agents No. 1, no. 2, and No. 3 shown in fig. 2 is shown in fig. 4, and the error curve of the formation process is shown in fig. 5.
FIGS. 6 and 7 respectively illustrate angles of view in accordance with an embodiment of the present disclosureThe constraint conditions are a formation schematic diagram and a formation process error curve schematic diagram of 3 intelligent agents under the constraint conditions.
At the position ofUnder the condition that the size of the view angle theta f is set to be pi, the expected angle/>Initial positions of the No. 1, no. 2 and No. 3 agents are/>, respectivelyAnd/>The formation process of agents No. 1, no. 2, and No. 3 shown in fig. 2 is shown in fig. 6, and the error curve of the formation process is shown in fig. 5.
Simulation II: different viewing angle size constraints
Fig. 8 and 9 show a schematic formation diagram and a schematic formation process error diagram, respectively, when an initial position of the azimuth No.2 agent is close to the distance No. 3 agent according to an embodiment of the present disclosure.
Wherein, simulation results when the initial position of the No. 2 azimuth intelligent agent is close to the No. 1 distance intelligent agent and the view angle thereofSimulation results under constraint conditions are consistent, and a formation schematic diagram and a formation process error schematic diagram of the initial position of the No.2 azimuth intelligent agent when the initial position is close to the No.1 azimuth intelligent agent are respectively shown in fig. 4 and 5.
At the position ofUnder the condition that the size of the view angle is set as/>Desired angle/>Initial positions of the No. 1, no. 2 and No. 3 agents are/>, respectivelyAnd/>The formation process of agents No. 1, no. 2, and No. 3 shown in fig. 2 is shown in fig. 8, and the error curve of the formation process is shown in fig. 9.
Simulation III: initial position on desired side and undesired side
Fig. 10 and 11 show a schematic formation diagram and a schematic formation process error diagram, respectively, when the initial position of the azimuth No. 2 agent is on the desired side according to an embodiment of the present disclosure.
On the desired side, the view angle is set to beDesired angle/>Initial positions of the No. 1, no. 2 and No. 3 agents are/>, respectivelyAnd/>The formation process of agents No. 1, no.2, and No.3 shown in fig. 2 is shown in fig. 10, and the error curve of the formation process is shown in fig. 11. /(I)
FIG. 12 illustrates a multi-agent formation and transformation process schematic under view angle constraints in accordance with an embodiment of the present disclosure; fig. 13 illustrates a schematic diagram of angle errors and side length transformations during multi-agent formation under view angle constraints in accordance with an embodiment of the present disclosure.
Next, a set of experiments of unmanned aerial vehicle are given, the formation process is shown in fig. 11, and the error and side length change curves are shown in fig. 12.
The multi-agent formation control method under the view angle constraint condition comprises the steps of establishing an agent system model, wherein the agents comprise azimuth agents and distance agents; constructing an angular velocity controller of the azimuth intelligent agent based on the intelligent agent system model; the angular velocity controller of the azimuth intelligent body is utilized to control the azimuth intelligent body to meet the constraint condition of the view angle; under the condition that the azimuth intelligent body meets the view angle constraint condition, establishing a linear speed control law of the azimuth intelligent body according to the position of the azimuth intelligent body; a distance agent switching function is designed, and a linear speed control law of the distance agent is built according to the switching function and the multi-agent system model; and controlling the formation of multiple intelligent agents under the constraint condition of the view angle according to the linear speed control law of the azimuth intelligent agent and the linear speed control law of the distance intelligent agent. Under the condition that the intelligent agent only has azimuth information and no position information or distance information, the intelligent agent can select relatively fewer paths to move from an unexpected side to a desired side, and finally move to a desired position, so that formation, maintenance and transformation of multi-intelligent agent formation under the view angle constraint condition are realized.
Although the embodiments of the present invention are described above, the embodiments are only used for facilitating understanding of the present invention, and are not intended to limit the present invention. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is still subject to the scope of the appended claims.
Claims (4)
1. A multi-agent formation control method under a viewing angle constraint condition, the method comprising:
Establishing an intelligent system model, wherein the intelligent body comprises a azimuth intelligent body and a distance intelligent body;
constructing an angular velocity controller of the azimuth intelligent agent based on the intelligent agent system model;
Controlling the azimuth intelligent body to meet the view angle constraint condition by utilizing an angular speed controller of the azimuth intelligent body;
under the condition that the azimuth intelligent body meets the view angle constraint condition, establishing a linear speed control law of the azimuth intelligent body according to the position of the azimuth intelligent body;
designing a distance agent switching function, and establishing a linear speed control law of the distance agent according to the switching function and the agent system model;
Controlling the formation of multiple intelligent agents under the constraint condition of a view angle according to the linear speed control law of the azimuth intelligent agent and the linear speed control law of the distance intelligent agent;
The intelligent agent system model is as follows:
wherein z i (k+1) and Representing the positions of two adjacent times of the intelligent agent,/>Is the control input of the linear velocity of the intelligent body, T is the sampling time,/>U ω (k) is the control input of the angular velocity of the intelligent agent;
the view angle constraint condition is that the view angle theta f epsilon (0, pi ];
The position of the azimuth intelligent agent is divided into a desired side and an undesired side;
The linear speed control law u of the azimuth intelligent agent is as follows:
wherein g is a discriminant function of the position of the azimuth intelligent agent, and f (k) affects the linear velocity control law of the azimuth intelligent agent when the position of the azimuth intelligent agent is at a desired side; when the position of the azimuth agent is on the undesired side, 1-g represents the linear velocity control law affecting the azimuth agent, v (k) is the agent linear velocity.
2. The multi-agent formation control method according to claim 1, wherein the constructing an angular velocity controller of an azimuth agent based on the agent system model includes:
Establishing a perception orientation model of the orientation agent based on the agent system model;
calculating an included angle between the actual orientation and the expected orientation of the azimuth intelligent body according to the perception azimuth model;
and constructing an angular speed controller of the azimuth intelligent body according to the included angle between the actual direction and the expected direction of the azimuth intelligent body.
3. The multi-agent formation control method according to claim 1, wherein f (k) = -k (θ (k) - θ *), where θ (k) is a controlled angle of the azimuth agent, and θ * (k) represents a desired controlled angle.
4. The multi-agent formation control method according to claim 1, wherein the distance agent switching functionWhere S is the signed area and S * is the desired signed area.
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