Multi-unmanned aerial vehicle jitter elimination controller design method based on segmentation coefficient artificial potential field

Abstract

The invention aims to provide a multi-unmanned aerial vehicle jitter elimination controller design method based on a segmentation coefficient artificial potential field. The problem of jitter caused by formation based on a traditional artificial potential field can be solved. Firstly, an artificial potential field of coefficient segmentation is constructed, so that an unmanned aerial vehicle motion model is established, and a shake elimination controller is designed in combination with a backstepping control method. The invention provides a multi-unmanned aerial vehicle jitter elimination controller design method based on a variable coefficient artificial potential field by considering an unmanned aerial vehicle motion model and the artificial potential field.

Description

Technical Field

[0001] The invention belongs to the field of unmanned aerial vehicle system control, and in particular relates to a design method for a multi-unmanned aerial vehicle formation de-jittering controller based on a piecewise coefficient artificial potential field. Background Art

[0002] In recent years, unmanned aerial technology has made rapid progress and has been widely used in military and civilian fields. UAVs can fly quickly and stably even in harsh terrain, and are most suitable for reconnaissance, search, and rescue. However, small UAVs have limited energy, so their flight distance and mission execution time are also limited. Therefore, considering UAV swarm operations is a hot topic at present. Artificial potential fields are a very common control method. Using artificial potential fields can control the shape of the formation and avoid collisions, but relying solely on traditional artificial potential fields will cause the UAV swarm to vibrate violently.

[0003] The traditional artificial potential field method relies solely on the distance between drones to generate force, thereby driving the drone swarm to move. However, when the distance between drones gets closer and closer, due to the relationship between gravity and repulsion, the drones will have to find their own balance positions. As a result, the drone swarm will shake violently. As long as one drone is in motion, the rest of the drones will also shake. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a multi-UAV anti-jitter controller design method based on segmented coefficient artificial potential field, which can solve the jitter problem caused by the formation based on the traditional artificial potential field. First, a coefficient segmented artificial potential field is constructed to establish the UAV motion model, and the anti-jitter controller is designed in combination with the backstepping control method. The present invention considers the UAV motion model and the artificial potential field and proposes a multi-UAV anti-jitter controller design method based on a variable coefficient artificial potential field.

[0005] The objective of the present invention is achieved through the following technical solutions:

[0006] The present invention proposes a multi-UAV anti-jitter controller design method based on a piecewise coefficient artificial potential field, comprising the following steps:

[0007] S1: Establish UAV motion model;

[0008] S2: Construct a multi-UAV formation scenario;

[0009] S3: constructing artificial potential field of piecewise coefficients;

[0010] S4: Design a controller based on piecewise coefficient artificial potential field;

[0011] S5: Select the repulsion coefficient according to the distance between the drones, and continuously adjust the repulsion coefficient to eventually eliminate the jitter of the drone group.

[0012] Furthermore, in S1, a UAV motion model is constructed:

[0013] Model the dynamics of a drone in 2D:

[0014]

[0015] Where x and y represent the position of the drone, u is the speed of the drone, ψ is the heading angle of the drone, and ω is the angular velocity of the drone.

[0016] Furthermore, in S2, a multi-UAV formation scenario is constructed:

[0017] Set a target point for the drone group. This target point has a virtual attraction to all drones. When a drone approaches other drones to a certain distance, a virtual repulsion will be generated between the drones. Therefore, each drone is subject to the attraction of a target point and several repulsions from other drones. The drone will move according to the combined force. After a certain period of time, the drones will slowly shrink to form a cluster.

[0018] Furthermore, in S3, an artificial potential field of segmented coefficients is constructed:

[0019] The gravitational field generated by the target point is defined as follows:

[0020]

[0021] The repulsive field is defined as follows:

[0022]

[0023] Among them, k b ,d ij , d0 are the repulsion coefficient, the distance from drone i to j, and the maximum distance of repulsion, respectively.

[0024] The definition of the segment repulsion coefficient is as follows:

[0025]

[0026] We set a different repulsion coefficient every two meters, and the coefficient decreases as the distance decreases, in order to balance the repulsion force that suddenly increases due to the decrease in distance. The specific values ​​of the repulsion coefficient are as follows:

[0027] Table 1

[0028] d0 / k0b d1 / k1b d2 / k2b d3 / k3b d4 / k4b d5 / k5b d6 / k6b d7 / k7b 0.3 / 0.06 2.3 / 0.10 4.3 / 0.18 6.3 / 0.28 8.3 / 0.45 10.3 / 0.68 12.3 / 0.93 14.3 / 1

[0029] Furthermore, in S4, a controller based on a piecewise coefficient artificial potential field is designed:

[0030] We define:

[0031]

[0032] Where (x0, y0) is the centroid coordinates of all other drones within the repulsive field of drone i.

[0033] The speed controller is:

[0034] u=-k u (x s cosψ+y s sinψ) (7)

[0035] Angle Controller:

[0036]

[0037] Furthermore, in S5, the repulsion coefficient is selected according to the distance between the drones, and the repulsion coefficient is continuously adjusted to eventually eliminate the jitter of the drone group:

[0038] The movement of the drones is controlled according to the designed controller. When the drone group shrinks and the drones get closer, different repulsion coefficients are selected according to the distance. When the distance decreases, the repulsion coefficient also decreases. At this time, there will be no oscillation of the drone group caused by the huge repulsion change caused by the decrease in distance.

[0039] The beneficial effects of the present invention are as follows: The purpose of the present invention is to provide a multi-UAV anti-jitter controller design method based on a segmented coefficient artificial potential field, which can solve the jitter problem caused by the formation based on the traditional artificial potential field. First, a coefficient segmented artificial potential field is constructed to establish a UAV motion model, and the anti-jitter controller is designed in combination with the backstepping control method. The present invention considers the UAV motion model and the artificial potential field and proposes a multi-UAV anti-jitter controller design method based on a variable coefficient artificial potential field. The economy is reflected by the UAV control cost, and the reliability is reflected by the Lyapunov stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0041] Figure 1 It is the overall flow chart;

[0042] Figure 2 This is a schematic diagram of the movement of drone clusters;

[0043] Figure 3 It is a schematic diagram of artificial potential field; DETAILED DESCRIPTION

[0044] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0045] The present invention first constructs a coefficient segmented artificial potential field to establish a UAV motion model, and then designs a de-jitter controller in combination with the backstepping control method. Figure 1 As shown in FIG, the design method of the multi-UAV anti-jitter controller based on the piecewise coefficient artificial potential field specifically includes:

[0046] Step 1: Establish a UAV motion model;

[0047] The initial population of whales is constructed through reverse learning. The detailed steps are as follows: Model the dynamics of the drone in two-dimensional coordinates:

[0048]

[0049] Where x and y represent the position of the drone, u is the speed of the drone, ψ is the heading angle of the drone, and ω is the angular velocity of the drone.

[0050] Step 2: Build a multi-UAV formation scenario;

[0051] Set a target point for the drone group, which has a virtual attraction to all drones, such as Figure 2 As shown in the figure, when a drone approaches other drones to a certain distance, a virtual repulsive force will be generated between the drones. Therefore, each drone is attracted by a target point and several repulsive forces from other drones, and the drone will move according to the combined force. After a certain period of time, the drones will slowly shrink to form a cluster.

[0052] Step 3: Construct an artificial potential field of piecewise coefficients;

[0053] A schematic diagram of repulsion and attraction is shown below Figure 3 As shown, the gravitational field generated by the target point is defined as follows:

[0054]

[0055] Taking the derivative of the gravitational field, we can get the gravitational force as:

[0056]

[0057] Among them, k a is the gravitational coefficient, (x p ,y p ) is the location of the target point.

[0058] The repulsive field is defined as follows:

[0059]

[0060] Similarly, the repulsive force is shown in (5):

[0061]

[0062] Among them, k b ,d ij , d0 are the repulsion coefficient, the distance from drone i to j, and the maximum distance of repulsion, respectively.

[0063] The definition of the segment repulsion coefficient is as follows:

[0064]

[0065] We set a different repulsion coefficient every two meters, and the coefficient decreases as the distance decreases, in order to balance the repulsion force that suddenly increases due to the decrease in distance. The specific values ​​of the repulsion coefficient are shown in Table 1:

[0066] Table 1

[0067] d0 / k0b d1 / k1b d2 / k2b d3 / k3b d4 / k4b d5 / k5b d6 / k6b d7 / k7b 0.3 / 0.06 2.3 / 0.10 4.3 / 0.18 6.3 / 0.28 8.3 / 0.45 10.3 / 0.68 12.3 / 0.93 14.3 / 1

[0068] Step 4: Design a controller based on the piecewise coefficient artificial potential field;

[0069] The distance and angle between the drone and the target point are as follows:

[0070]

[0071] α=atan(y p -y,x p -x) (16)

[0072] Next, we defined an angular error:

[0073] e ψ =α-ψ (17)

[0074] We take the derivative of (7) and substitute (1) into it to obtain:

[0075]

[0076] After rearranging we get:

[0077]

[0078] Next we constructed a Lyapunov function:

[0079]

[0080] Taking the derivative with respect to V, we obtain:

[0081]

[0082] Substituting into (1), we obtain:

[0083]

[0084] Then we define:

[0085]

[0086] Where (x0, y0) is the centroid coordinates of all other drones within the repulsive field of drone i.

[0087] Then simplifying formula (14), we get:

[0088]

[0089] According to Lyapunov's stability principle, if the system is to be stable, it must satisfy: V>0,

[0090] So we take the speed controller as:

[0091] u=-k u (x s cosψ+y s sinψ) (26)

[0092] We define a new angle error: e c =ψ c -ψ,ψ c =atan(y s ,x s ). c After taking the derivative we get:

[0093]

[0094] For the angle error, we construct a Lyapunov function:

[0095] V c =e c 2 (28)

[0096] V c After derivation, we get:

[0097]

[0098] In order to satisfy the stability principle, we set Here, k c is the adjustment coefficient of the angle controller. We will Substitute (17) to obtain the angle controller:

[0099] Step 5: Select the repulsion coefficient according to the distance between drones, and continuously adjust the repulsion coefficient to eventually eliminate the jitter of the drone group.

[0100] The controller designed according to (19) and (22) is used to control the movement of the drones. When the drone group shrinks and the drones get closer, different repulsion coefficients are selected according to the distance. When the distance decreases, the repulsion coefficient also decreases. At this time, there will be no oscillation of the drone group caused by the huge repulsion change caused by the decrease in distance.

[0101] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A multi-UAV anti-jitter controller design method based on piecewise coefficient artificial potential field, characterized by: The method comprises the following steps: S1: Establish UAV motion model; S2: Construct a multi-UAV formation scenario; S3: constructing artificial potential field of piecewise coefficients; S4: Design a controller based on piecewise coefficient artificial potential field; S5: Select the repulsion coefficient according to the distance between the drones, and continuously adjust the repulsion coefficient to eventually eliminate the jitter of the drone group.

2. The method for designing a multi-UAV anti-jitter controller based on a piecewise coefficient artificial potential field according to claim 1 is characterized in that: In S1, the dynamics of the drone in two-dimensional coordinates are modeled: Where x and y represent the position of the drone, u is the speed of the drone, ψ is the heading angle of the drone, and ω is the angular velocity of the drone.

3. The method for designing a multi-UAV anti-jitter controller based on a piecewise coefficient artificial potential field according to claim 1 is characterized in that: In S2: construct a multi-UAV formation scenario; Set a target point for the drone group. This target point has a virtual attraction to all drones. When a drone approaches other drones to a certain distance, a virtual repulsion will be generated between the drones. Therefore, each drone is subject to the attraction of a target point and several repulsions from other drones. The drone will move according to the combined force. After a certain period of time, the drones will slowly shrink to form a cluster.

4. The method for designing a multi-UAV anti-jitter controller based on a piecewise coefficient artificial potential field according to claim 1 is characterized in that: In S3: constructing an artificial potential field of segmented coefficients; The gravitational field generated by the target point is defined as follows: Taking the derivative of the gravitational field, we can get the gravitational force as: Among them, k a is the gravitational coefficient, (x p ,y p ) is the location of the target point. The repulsive field is defined as follows: Similarly, the repulsive force is shown in (5): Among them, k b ,d ij , d0 are the repulsion coefficient, the distance from drone i to j, and the maximum distance of repulsion, respectively. The definition of the segment repulsion coefficient is as follows: We set a different repulsion coefficient every two meters, and the coefficient decreases as the distance decreases, in order to balance the repulsion force that suddenly increases due to the decrease in distance. The specific values ​​of the repulsion coefficient are as follows: Table 1 5. The method for designing a multi-UAV anti-jitter controller based on a piecewise coefficient artificial potential field according to claim 1 is characterized in that: In S4: design a controller based on piecewise coefficient artificial potential field: The distance and angle between the drone and the target point are as follows: atan(and p -y,x p -x) (8) Next, we defined an angular error: e ψ =a-ψ (9) We take the derivative of (7) and substitute (1) into it to obtain: After rearranging we get: Next we constructed a Lyapunov function: Taking the derivative with respect to V, we obtain: Substituting into (1), we obtain: Then we define: Where (x0, y0) is the centroid coordinates of all other drones within the repulsive field of drone i. Then simplifying formula (14), we get: According to Lyapunov's stability principle, if the system is to be stable, it must satisfy: V>0, So we take the speed controller as: u=-k u (x s cosψ+y s sinψ) (18) We define a new angle error: e c =ψ c -ψ,ψ c =atan(y s ,x s ). c After taking the derivative we get: For the angle error, we construct a Lyapunov function: V c =e c 2 (20) V c After derivation, we get: In order to satisfy the stability principle, we set Here, k c is the adjustment coefficient of the angle controller. We will Substitute (17) to obtain the angle controller:

6. The method for designing a multi-UAV anti-jitter controller based on a piecewise coefficient artificial potential field according to claim 1 is characterized in that: In S5: a repulsion coefficient is selected according to the distance between the drones, and the repulsion coefficient is continuously adjusted to eventually eliminate the jitter of the drone group. The controller designed according to (19) and (22) is used to control the movement of the drones. When the drone group shrinks and the drones get closer, different repulsion coefficients are selected according to the distance. When the distance decreases, the repulsion coefficient also decreases. At this time, there will be no oscillation of the drone group caused by the huge repulsion change caused by the decrease in distance.

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