Multi-uav system distributed formation control method, device and storage device

Abstract

The application provides a kind of multi-unmanned aerial vehicle system distributed formation control method, comprising: S1: the dynamics modeling of multi-unmanned aerial vehicle system is carried out, and the dynamics model of multi-unmanned aerial vehicle system is obtained;Desired trajectory of multi-unmanned aerial vehicle system is expressed geometrically, and formation control coordinate condition is set;Control target expression is constructed by dynamics model and formation control coordinate condition;S2: the formation control problem of control target expression is converted into state consistency problem by variable transformation, and improved control target expression is constructed;S3: the distributed formation controller based on smooth control is constructed by improved control target expression, and the motion of multi-unmanned aerial vehicle system is controlled by the distributed formation controller based on smooth control.The application adopts distributed control algorithm, solves the high load problem generally faced in communication and control of centralized control method, and greatly reduces control cost.

Description

Technical Field

[0001] This invention relates to the field of industrial control technology, and in particular to a distributed formation control method, device and storage device for a multi-UAV system. Background Technology

[0002] Unmanned aerial vehicles (UAVs) are a type of reusable, powered, unmanned aircraft. They are widely used due to their low cost, low casualties, and ease of operation. However, as UAV applications become increasingly complex, single-UAV operations are no longer sufficient to meet mission requirements. By combining UAV technology with swarm intelligence, multi-UAV cooperative formation control technology has been developed. Multi-UAV cooperative formation control not only better meets complex mission requirements but also offers advantages such as high efficiency, high flexibility, strong robustness, and low cost. Currently, multi-UAV technology is increasingly used in important fields such as military applications, in addition to information gathering and location tracking. Therefore, research on multi-UAV cooperative control has significant strategic importance.

[0003] While multi-drone technology is widely used today, it still faces several technical challenges. Firstly, in a multi-drone formation involving a leader and followers, the sheer number of individuals makes efficient communication between them problematic, while establishing the desired formation state relies on effective message exchange. Traditional centralized control methods are no longer suitable for such large-scale scenarios. On one hand, centralized control incurs significant communication costs, and the limited bandwidth between drones makes large-scale communication extremely difficult. On the other hand, centralized control lacks robustness; a problem in one component can lead to the collapse of the entire system. These issues require careful consideration in practical engineering applications.

[0004] Secondly, in some important application areas, the formation of a stable formation is often crucial to mission success. Besides an effective control algorithm, a stable control signal input is also essential for stable formation formation. When the input signal jitters, it can cause drastic changes in the formation state, which can lead to instability and collisions between drones, resulting in unnecessary losses. Therefore, research on the cooperative control of multi-UAV system formations has significant engineering implications.

[0005] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a distributed formation control method for multiple unmanned aerial vehicle (UAV) systems, comprising:

[0007] S1: Perform dynamic modeling on the multi-UAV system to obtain the dynamic model of the multi-UAV system; express the desired trajectory of the multi-UAV system geometrically and set the formation control coordinate conditions; construct the control target expression through the dynamic model and the formation control coordinate conditions;

[0008] S2: By using variable transformation, the formation control problem of the control objective expression is transformed into a state consistency problem, and an improved control objective expression is constructed;

[0009] S3: Construct a distributed formation controller based on smooth control through the improved control objective expression, and control the motion of multiple UAV systems through the distributed formation controller based on smooth control.

[0010] Preferably, step S1 specifically includes:

[0011] S11: The multi-drone system includes: one leader drone and multiple follower drones. Construct a dynamic model of the multi-drone system, including: the dynamic model of the followers and the dynamic model of the leader.

[0012] The expression for the dynamic model of the follower is:

[0013]

[0014] The expression for the leader's dynamic model is:

[0015]

[0016] Where i is the drone's number, i = 0 indicates the leader, i > 0 indicates a follower, subscripts m and p represent the drone's planar motion and angular rotational motion respectively, and the superscript · indicates differentiation. X i =[x i ,y i ,z i ] T V is the current position vector of drone i. i =[v i ,w i ,d i ] T Let represent the current velocity vector of drone i. This represents the current angular rotation vector of drone i. F represents the current angular velocity vector of drone i. im F ip G 0m and Y 0p Let F represent the dynamics in the corresponding directions for followers and leaders, respectively, and F... im =T -1G 0m F ip =Y 0p T represents the attitude transformation matrix between the inertial coordinate system and the rigid coordinate system of the multi-UAV system;

[0017] S12: Construct the XOY plane, express the desired trajectory of the multi-UAV system in the XOY plane in geometric form, and set the formation control coordinate conditions. The expression for the formation control coordinate conditions is:

[0018]

[0019] Where n is the total number of drones, (A ix A iy A iz Let A be the desired coordinates of UAV i in the geometric figure. 0x A 0y A 0z Let ) represent the desired coordinates of the leader in the geometric figure, and satisfy A 0x =A 0y =A 0z =0;

[0020] S13: By constructing a control objective expression, UAV i can track the leader's coordinates and form the desired trajectory of the multi-UAV system using only its own state information and the state information of its neighboring UAV j. The specific control objective expression is as follows:

[0021]

[0022]

[0023] Where (x0, y0, z0) represents the current coordinates of the leader, t is the running time of the multi-UAV system, and i and j are the UAV numbers, with i ≠ j. i ,y i ,z i (x) represents the current coordinates of drone i, (x) j ,y j ,z j ) represents the current coordinates of drone j.

[0024] Preferably, step S2 specifically includes:

[0025] S21: Define an auxiliary variable P in the XOY plane. 1i P 2i and P 3i To express the formation state of UAV i, define an auxiliary variable τ. 1i and τ 2iFor the control input of UAV i, the expressions for each auxiliary variable are:

[0026]

[0027]

[0028]

[0029]

[0030] τ 2i =v i -τ 1i ·P 3i (1+α 2 )+α|τ 1i |P 2i .

[0031] Where i is the drone's number, i=0 indicates the leader, i>0 indicates a follower, and the superscript · indicates differentiation. Let x be the angle between the heading of UAV i and the x-axis, (x... i ,y i Let (A) be the current planar coordinates of UAV i. ix A iy Let be the desired planar coordinates of UAV i, and v be the desired plane coordinates of UAV i. i Let α be the flight speed of UAV i, and α be the first control gain parameter;

[0032] S22: Transform the follower's dynamic model using auxiliary variables to obtain the updated dynamic model of the follower, expressed as:

[0033]

[0034] S23: The relationship between the state of each UAV and the formation state is obtained through the follower dynamics update model, expressed as follows:

[0035]

[0036] S24: By re-expressing the control objective through the relationship between the states of individual UAVs and the formation state, an improved control objective expression is obtained, specifically:

[0037]

[0038] Where t is the operating time of the multi-UAV system, (P 1i ,P 2i ,P 2i ,τ 1i Let ) be the improved control objective expression for UAV i, (P 10,P 20 ,P 20 ,τ 10 ) is the leader's improved control objective expression.

[0039] The preferred expression for the distributed formation controller based on smooth control is:

[0040]

[0041] Where, τ 1ir τ is the first-dimensional control input for drone i. 2ir b is the second-dimensional control input for drone i, where i and j are both drone numbers and i ≠ j. i = 0 indicates a leader, and i > 0 indicates a follower. When follower drones and leader drones can directly exchange information, b... i >0, otherwise b i =0, (P 1i ,P 2i ,P 2i ,τ 1i Let ) be the improved control objective expression for UAV i, (P 10 ,P 20 ,P 20 ,τ 10 ) represents the improved control objective expression for the leader, η represents the second control gain parameter, σ represents the third control gain parameter, and a ij b is an element in the Laplace matrix. i For each element in the interaction matrix between leader and follower i, N i Let be the number of neighbors of drone i.

[0042] A storage device that stores instructions and data for implementing the above-described distributed formation control method for a multi-UAV system.

[0043] A distributed formation control device for a multi-UAV system includes: a processor and a storage device; the processor loads and executes instructions and data in the storage device to implement the aforementioned distributed formation control method for a multi-UAV system.

[0044] The present invention has the following beneficial effects:

[0045] 1. The control method of this invention is closer to reality, integrating the smooth distributed consistency control method into the geometric pattern model to achieve three-dimensional formation tracking;

[0046] 2. The control method of the present invention is more engineering-significant, providing a smooth input signal for the UAV control channel and avoiding the chattering effect caused by the traditional sliding mode control protocol;

[0047] 3. By adopting a distributed control algorithm, the high load problem commonly faced by centralized control methods in terms of communication and control is solved, and the control cost is greatly reduced. Attached Figure Description

[0048] Figure 1 This is a flowchart of a method according to an embodiment of the present invention;

[0049] Figure 2 This is a coordinate diagram of the UAV's motion in three-dimensional space.

[0050] Figure 3 The geometry of the desired trajectory for a multi-UAV system;

[0051] Figure 4 A diagram illustrating the consistent tracking performance of a multi-UAV system;

[0052] Figure 5 A tracking effect diagram of the centroid position of a multi-UAV system;

[0053] Figure 6 Control input diagram for a multi-UAV system;

[0054] Figure 7 The image shows the formation effect of a multi-UAV system at nine different moments in the XOY plane.

[0055] Figure 8 The first-angle formation effect of a multi-UAV system at eight moments in a three-dimensional plane;

[0056] Figure 9 The second-angle formation effect of a multi-UAV system at eight moments in a three-dimensional plane;

[0057] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0058] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0059] Reference Figure 1 This invention provides a distributed formation control method for a multi-UAV system, which provides cooperative formation control of a multi-UAV system with a leader and a follower considering the uncertainty of dynamic parameters, and meets the control cost requirements of the multi-UAV system by selecting appropriate control gain parameters.

[0060] Includes the following steps:

[0061] S1: Perform dynamic modeling on the multi-UAV system to obtain the dynamic model of the multi-UAV system; express the desired trajectory of the multi-UAV system geometrically and set the formation control coordinate conditions; construct the control target expression through the dynamic model and the formation control coordinate conditions;

[0062] S2: By using variable transformation, the formation control problem of the control objective expression is transformed into a state consistency problem, and an improved control objective expression is constructed;

[0063] S3: Construct a distributed formation controller based on smooth control through the improved control objective expression, and control the motion of multiple UAV systems through the distributed formation controller based on smooth control.

[0064] In this embodiment, step S1 specifically includes:

[0065] S11: The multi-UAV system includes one leader UAV and multiple follower UAVs. A dynamic model of the multi-UAV system is constructed, including the dynamic models of the followers and the leader. The motion coordinates of the UAVs in three-dimensional space are shown in the figure below. Figure 2 As shown;

[0066] The expression for the dynamic model of the follower is:

[0067]

[0068] The expression for the leader's dynamic model is:

[0069]

[0070] Where i is the drone's number, i = 0 indicates the leader, i > 0 indicates a follower, subscripts m and p represent the drone's planar motion and angular rotational motion respectively, and the superscript · indicates differentiation. X i =[x i ,y i ,z i ] T V is the current position vector of drone i. i =[v i ,w i ,d i ] T Let represent the current velocity vector of drone i. This represents the current angular rotation vector of drone i. F represents the current angular velocity vector of drone i. im F ip G 0m and Y 0p Let F represent the dynamics in the corresponding directions for followers and leaders, respectively, and F... im =T-1 G 0m F ip =Y 0p T represents the attitude transformation matrix between the inertial coordinate system and the rigid coordinate system of the multi-UAV system. The attitude transformation matrix T is a matrix related to the rotation angle.

[0071] S12: The goal of formation control is to design translation and rotation controls so that the multi-UAV system can achieve precise control of the desired formation trajectory; construct the XOY plane, express the desired trajectory of the multi-UAV system in the XOY plane in geometric form, and set the formation control coordinate conditions. The expression for the formation control coordinate conditions is:

[0072]

[0073] Where n is the total number of drones, (A ix A iy A iz Let A be the desired coordinates of UAV i in the geometric figure. 0x A 0y A 0z Let ) represent the desired coordinates of the leader in the geometric figure, and satisfy A 0x =A 0y =A 0z =0;

[0074] S13: Geometry of the desired trajectory for a multi-UAV system as shown in the figure. Figure 3 As shown, by constructing a control objective expression, UAV i can track the leader's coordinates and form the desired trajectory of the multi-UAV system using only its own state information and the state information of its neighboring UAV j. The specific control objective expression is as follows:

[0075]

[0076]

[0077] Where (x0, y0, z0) represents the leader's current coordinates (i.e., the geometric centroid of the desired trajectory geometry), t is the multi-UAV system operating time, and i and j are both UAV numbers where i ≠ j, (x i ,y i ,z i (x) represents the current coordinates of drone i, (x) j ,y j ,z j ) represents the current coordinates of drone j.

[0078] In this embodiment, step S transforms the formation control problem of a multi-UAV system into a state consistency problem by setting auxiliary variables;

[0079] Step S2 is as follows:

[0080] S21: Define an auxiliary variable P in the XOY plane. 1i P 2i and P 3i To express the formation state of UAV i, define an auxiliary variable τ. 1i and τ 2i For the control input of UAV i, the expressions for each auxiliary variable are:

[0081]

[0082]

[0083]

[0084]

[0085] τ 2i =v i -τ 1i ·P 3i (1+α 2 )+α|τ 1i |P 2i .

[0086] Where i is the drone's number, i=0 indicates the leader, i>0 indicates a follower, and the superscript · indicates differentiation. Let x be the angle between the heading of UAV i and the x-axis, (x... i ,y i Let (A) be the current planar coordinates of UAV i. ix A iy Let be the desired planar coordinates of UAV i, and v be the desired plane coordinates of UAV i. i Let α be the flight speed of UAV i, and α be the first control gain parameter;

[0087] S22: Transform the follower's dynamic model using auxiliary variables to obtain the updated dynamic model of the follower, expressed as:

[0088]

[0089] S23: The relationship between the state of each UAV and the formation state is obtained through the follower dynamics update model, expressed as follows:

[0090]

[0091] S24: By re-expressing the control objective through the relationship between the states of individual UAVs and the formation state, an improved control objective expression is obtained, specifically:

[0092]

[0093] Where t is the operating time of the multi-UAV system, (P 1i ,P 2i ,P 2i ,τ 1i Let ) be the improved control objective expression for UAV i, (P 10 ,P 20 ,P 20 ,τ 10 () represents the leader's improved control objective expression;

[0094] Specifically, after transforming the formation control problem of a multi-UAV system into a state consistency problem, the consistency tracking effect of the multi-UAV system is shown in the figure below. Figure 4 As shown in the figure, the tracking effect of the centroid position of the multi-UAV system is as follows: Figure 5 As shown in Figure 4-5, under the designed control algorithm, the multi-UAV system can achieve good trajectory tracking.

[0095] In this embodiment, in reality, the dynamics model of multi-UAV systems generally has uncertain dynamic parameters, which leads to a certain deviation between the actual control input and the expected control input. Therefore, in this invention, a distributed formation controller based on smooth control is reconstructed through an improved control objective expression.

[0096] The expression for a distributed formation controller based on smooth control is:

[0097]

[0098] Where, τ 1ir τ is the first-dimensional control input for drone i. 2ir b is the second-dimensional control input for drone i, where i and j are both drone numbers and i ≠ j. i = 0 indicates a leader, and i > 0 indicates a follower. When follower drones and leader drones can directly exchange information, b... i >0, otherwise b i =0, (P 1i ,P 2i ,P 2i ,τ 1i Let ) be the improved control objective expression for UAV i, (P 10 ,P 20 ,P 20 ,τ 10 ) represents the improved control objective expression for the leader, η represents the second control gain parameter, σ represents the third control gain parameter, and a ijb is an element in the Laplace matrix. i For each element in the interaction matrix between leader and follower i, N i Let be the number of neighbors of drone i.

[0099] Specifically, the stability analysis of the distributed formation controller based on smooth control is as follows:

[0100] L31: Define control error and And satisfy and Based on the newly defined control error, the dynamic model of the follower is rewritten as follows:

[0101]

[0102] Combining the two equations above, we obtain the closed-loop system model:

[0103]

[0104] The above expression can be written in a compact form as follows:

[0105]

[0106] In the above formula, P1 = [P 11 ,P 12 ,…,P 1m ] T P2 = [P 21 ,P 22 ,…,P 2m ] T B = diag(b1, b2, ..., b n ), e1 = [P 11 -P 10 ,P 12 -P 10 ,…,P 1n -P 10 ] T e2 = [P 21 -P 20 ,P 22 -P 20 ,…,P 2n -P 20 ] T ,

[0107] L32: Constructing the V function (Lyapunov function) for the compact form of closed-loop systems:

[0108]

[0109] In the formula, Based on the functional form, we know that the V function is positive definite. Taking the derivative of the above equation, we obtain:

[0110]

[0111] Substituting the closed-loop system expression into the above equation, we get:

[0112]

[0113] Based on the properties of K types of functions, we finally obtain:

[0114]

[0115] Since the V function is positive definite and its first derivative is negative definite, it proves that the distributed formation controller based on smooth control of this invention can guarantee that the state of a multi-UAV system converges to a stable state; similarly, it can be obtained that when At that time, V k (t k ) = 0; therefore, the formation state P 1i and P 2i It can converge to the desired trajectory P in a finite amount of time. 10 and P 20 At the same time, it can track the leader's trajectory, ensuring that the entire multi-drone system can achieve the desired formation state.

[0116] L33: Given control parameters η = 3, σ = 0.64, α = 2; set the initial system state: P 10 = t / 3, P 20 =12α. Furthermore, when there is information exchange between drone i and drone j, a ij =1, otherwise a ij =0; when there is communication between follower drone i and leader drone, b i =1, otherwise b i =0.

[0117] The control input diagram of a multi-UAV system is as follows: Figure 6 As shown, from Figure 6 As can be seen, the multi-UAV system has a relatively smooth input of control signals, which can achieve smooth control of the multi-UAV system;

[0118] Taking a multi-UAV system consisting of six UAVs as an example, the formation effect of the multi-UAV system at nine moments in the XOY plane is as follows: Figure 7 As shown, the formation effect of the multi-UAV system at eight moments in the three-dimensional plane at the first angle is as follows: Figure 8 As shown, the second-angle formation effect of the multi-UAV system at eight moments in the three-dimensional plane is as follows: Figure 9As shown, comparison Figure 3 The geometry of the desired trajectory shows that, under the designed control algorithm, the multi-UAV system can achieve good formation performance.

[0119] This invention provides a storage device that stores instructions and data for implementing the aforementioned distributed formation control method for a multi-UAV system.

[0120] This invention provides a distributed formation control device for a multi-UAV system, comprising: a processor and a storage device; the processor loads and executes instructions and data in the storage device to implement the aforementioned distributed formation control method for a multi-UAV system.

[0121] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0122] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In the unit claims listing several devices, several of these devices may be embodied by the same hardware item. The use of the terms first, second, and third, etc., does not indicate any order and can be interpreted as identifiers.

[0123] The above are merely preferred embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A distributed formation control method for a multi-UAV system, characterized in that, include: S1: Perform dynamic modeling on the multi-UAV system to obtain the dynamic model of the multi-UAV system; express the desired trajectory of the multi-UAV system geometrically and set the formation control coordinate conditions; construct the control target expression through the dynamic model and the formation control coordinate conditions; S2: By using variable transformation, the formation control problem of the control objective expression is transformed into a state consistency problem, and an improved control objective expression is constructed; S3: Construct a distributed formation controller based on smooth control through the improved control objective expression, and control the motion of multiple UAV systems through the distributed formation controller based on smooth control; Step S2 is as follows: S21: Define auxiliary variables in the XOY plane. , and To express the formation state of drone i, define auxiliary variables. and For the control input of UAV i, the expressions for each auxiliary variable are: Where i is the drone's number, i=0 indicates the leader, i>0 indicates a follower, and the superscript · indicates differentiation. Let be the angle between the heading of UAV i and the x-axis. Let i be the current planar coordinates of UAV i. Let i be the desired planar coordinates of UAV i. Let i be the flight speed of the drone. This is the first control gain parameter; S22: Transform the follower's dynamic model using auxiliary variables to obtain the updated dynamic model of the follower, expressed as: S23: The relationship between the state of each UAV and the formation state is obtained through the follower dynamics update model, expressed as follows: S24: By re-expressing the control objective through the relationship between the states of individual UAVs and the formation state, an improved control objective expression is obtained, specifically: Where t represents the operating time of the multi-UAV system. Let be the improved control objective expression for UAV i. The improved control objective expression for the leader; The expression for a distributed formation controller based on smooth control is: in, For the first dimension control input of drone i, The second-dimensional control input for drone i is defined as follows: i and j are both drone IDs, where i ≠ j. i = 0 indicates a leader, and i > 0 indicates a follower. When the follower drone and the leader drone can directly communicate, the input is... ,otherwise , Let be the improved control objective expression for UAV i. The improved control objective expression for the leader. This is the second control gain parameter. This is the third control gain parameter. For each element in the Laplace matrix, For each element in the interaction matrix between leader and follower i, N i Let be the number of neighbors of drone i.

2. The distributed formation control method for multi-UAV systems according to claim 1, characterized in that, Step S1 is as follows: S11: The multi-drone system includes: one leader drone and multiple follower drones. Construct a dynamic model of the multi-drone system, including: the dynamic model of the followers and the dynamic model of the leader. The expression for the dynamic model of the follower is: The expression for the leader's dynamic model is: Where i is the drone's number, i=0 indicates the leader, i>0 indicates a follower, and the subscript... and These represent the drone's planar motion and angular rotational motion, respectively. The superscript · indicates differentiation. It is the current position vector of drone i. Let represent the current velocity vector of drone i. This represents the current angular rotation vector of drone i. This represents the current angular velocity vector of drone i. , , and These represent the dynamics in the corresponding directions for followers and leaders, respectively. , , The attitude transformation matrix represents the relationship between the inertial coordinate system and the rigid coordinate system of a multi-UAV system. S12: Construct the XOY plane, express the desired trajectory of the multi-UAV system in the XOY plane in geometric form, and set the formation control coordinate conditions. The expression for the formation control coordinate conditions is: Where n is the total number of drones, Let i be the desired coordinates of the drone i in the geometric figure. Let the expected coordinates of the leader in the geometric figure be represented, and satisfy the following conditions: ; S13: By constructing a control target expression, the drone... Using only its own state information and neighboring drones Given the state information, it can track the leader's coordinates and simultaneously form the desired trajectory of multiple unmanned aerial vehicle systems. The specific expression for the control target is: in, The current coordinates of the leader are represented by t, the running time of the multi-UAV system is t, and i and j are the UAV numbers where i ≠ j. Represents the current coordinates of drone i. Represents the current coordinates of drone j.

3. A storage device, characterized in that: The storage device stores instructions and data to implement any of the distributed formation control methods for multi-UAV systems as described in claims 1-2.

4. A distributed formation control device for a multi-UAV system, characterized in that: include: A processor and a storage device; the processor loads and executes instructions and data in the storage device to implement any of the distributed formation control methods for multi-UAV systems as described in claims 1-2.

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