CN118192273A - A hierarchical agile collaborative control method for AUV swarms for ocean exploration scenarios - Google Patents

Abstract

The embodiment of the disclosure relates to an AUV cluster layered agile cooperative control method for ocean exploration scenes. Aiming at the characteristics of ocean detection scenes and task demands, the embodiment of the disclosure analyzes the group performance of AUV clusters and provides an AUV cluster layered cooperative control architecture; furthermore, a layered cluster agile cooperative network model is established according to network characteristics such as high dynamic topology, high burstiness detection data and the like of the offshore area detection seal control facing the layered cooperative control architecture; and finally, analyzing a control target and a control requirement of the cooperative control architecture by combining an AUV cluster layered cooperative control architecture and a layered cluster agile cooperative network model and an information fusion result to provide a corresponding formation control method.

Description

A hierarchical agile collaborative control method for AUV swarms for ocean exploration scenarios

Technical Field

The disclosed embodiments relate to the technical field of underwater robots, and in particular to a hierarchical agile collaborative control method for AUV clusters for ocean exploration scenarios.

Background Art

As the largest strategic geographical unit on Earth, the ocean occupies rich resources on Earth and plays a vital role in human society. With the continuous development of autonomous underwater vehicle (AUV) technology, human underwater activities in the three-dimensional ocean space are gradually increasing. The ocean hydrological environment is harsh, complex and changeable. Single AUV ocean detection technology has the disadvantages of limited detection area, insufficient endurance, and low information processing efficiency, which can no longer meet the needs of current complex engineering applications.

The multi-AUV system has its own distribution characteristics in space, time and function, which fully overcomes the shortcomings of single AUV such as low detection range and low detection capability. Multi-AUV ocean detection has broad application prospects in the fields of hydrological information collection, underwater emergency target search, and large-scale sea area detection. However, the ocean detection scenes facing the multi-AUV system are usually located in the deep ocean, with limited light, large water depth, extreme environmental conditions, and large target areas. Therefore, the number of cluster formation platforms required is large, the detection data is huge, the reliability is insufficient, and there are a lot of time lag problems. AUVs are complex and diverse, the number is huge, and the detection capabilities of individual units vary greatly. The ocean information obtained by detection is incomplete and uncertain, which restricts the detection efficiency of the system. In addition, the network structure of the detection system is complex, and the transmission of detection, control and other information has defects such as high delay, high packet loss rate, and low efficiency, which restricts the overall performance of the system.

Summary of the invention

In order to avoid the shortcomings of the prior art, the present invention provides an AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios, which is used to solve the problems in the prior art that a multi-AUV system requires a large number of cluster formation platforms, huge detection data, insufficient reliability, and a large number of time lags; and the transmission of detection, control and other information has defects such as high delay, high packet loss rate, and low efficiency.

According to an embodiment of the present disclosure, a hierarchical agile collaborative control method for an AUV cluster for an ocean exploration scenario is provided, the method comprising:

Based on the ocean exploration scenario and the characteristics of each AUV, a hierarchical collaborative control architecture of an AUV cluster is established; wherein an AUV cluster includes several AUV subclusters, and an AUV subcluster includes a leading AUV and several follower AUVs;

Based on the AUV cluster hierarchical collaborative control architecture and detection tasks, several detection formations are established; one detection formation corresponds to one AUV sub-cluster;

For a detection formation, an AUV kinematic model is constructed, and the position error and angle error between the actual position and the ideal position of each following AUV in the carrier coordinate system are calculated;

The error between the actual position and the ideal position of the following AUV in the carrier coordinate system is input into the formation controller to calculate the expected angular velocity and the expected speed. The formation controller controls each following AUV according to the expected angular velocity and the expected speed, so that each following AUV and the leading AUV can reach asymptotic stability.

Furthermore, the method further comprises:

According to the network characteristics of ocean exploration scenarios, a hierarchical cluster agile collaborative network model is established, and a communication protocol based on an acoustic modem is adopted. The leader AUV and each follower AUV, each leader AUV, and the AUV cluster and collaborative nodes all communicate using the hierarchical cluster agile collaborative network model and a communication protocol based on an acoustic modem.

Furthermore, the communication protocol based on the underwater acoustic modem includes a header, a source address, a source role, a source level, a task status, a communication status, a posture information, collaborative data and a tail in sequence.

Furthermore, the structure of the AUV cluster hierarchical collaborative control architecture is a hierarchical structure. In the hierarchical structure, the leading AUV is the hierarchical control center of the following AUVs. The leading AUV communicates with each following AUV, and each following AUV communicates with each other. The control architecture of the AUV cluster hierarchical collaborative control architecture includes an information network layer, a data support layer, and a control planning layer.

Furthermore, the steps of constructing the AUV kinematic model and calculating the error between the actual position and the ideal position of each follower AUV in the carrier coordinate system include:

For a detection formation, the AUV kinematic model is constructed based on the position and attitude information of the leading AUV and each following AUV in the AUV cluster in the north-east coordinate system, and the velocity information and angular velocity information of the leading AUV and each following AUV in the carrier coordinate system;

Based on the AUV kinematic model, the ideal distance and angle between the leader AUV and the virtual leader AUV are set, and the position and attitude information of the virtual leader AUV in the north-east coordinate system is calculated;

According to the position and attitude information of the virtual leader AUV in the north-east coordinate system and the position and attitude information of the follower AUV in the north-east coordinate system, the position error and angle error of the virtual leader AUV and the follower AUV in the north-east coordinate system are obtained;

The carrier coordinate system is established with the position of the virtual leader AUV as the coordinate origin;

According to the position error and angle error of the virtual leader AUV and the follower AUV in the north-east coordinate system, the position error and angle error between the actual position and the ideal position of the follower AUV in the carrier coordinate system are obtained.

Furthermore, the expression of the AUV kinematic model is:

(1)

In the formula, is the position and attitude information of the i- th AUV in the north-east coordinate system, for The differential of is the x- axis coordinate of the ith AUV in the north-east coordinate system, is the y- axis coordinate of the i -th AUV in the north-east coordinate system, is the yaw angle of the i- th AUV in the north-east coordinate system, is the velocity information and angular velocity information of the i - th AUV in the carrier coordinate system, For the The x- axis speed of an AUV in the carrier coordinate system, is the y- axis speed of the i - th AUV in the carrier coordinate system, is the yaw angular velocity of the i - th AUV in the carrier coordinate system, is the transformation matrix from the north-east coordinate system to the carrier coordinate system, where

(2)

In the formula, It is the angle between the carrier coordinate system rotated around the axis and the north-east coordinate system;

The virtual leaders are:

(3)

In the formula, is the x- axis coordinate of the virtual leader AUV in the north-east coordinate system, is the y- axis coordinate of the virtual leader AUV in the north-east coordinate system, is the yaw angle of the virtual leader AUV in the north-east coordinate system, is the x- axis coordinate of the leading AUV in the north-east coordinate system, is the y- axis coordinate of the leading AUV in the north-east coordinate system, is the yaw angle of the leading AUV in the north-east coordinate system, The ideal distance between the leader AUV and the virtual leader AUV, The ideal angle for leading AUV and virtual leading AUV;

use It represents the error between the actual position of the following AUV and the virtual leading AUV. In the north-east coordinate system, the AUV error model is:

(4)

In the formula, is the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the north-east coordinate system, is the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the north-east coordinate system, is the yaw angle error between the actual position of the following AUV and the position of the virtual leader AUV in the north-east coordinate system, is the x- axis coordinate of the AUV in the north-east coordinate system, is the y- axis coordinate of the AUV in the north-east coordinate system, is the yaw angle of the following AUV in the north-east coordinate system;

use The error between the ideal position and the actual position of the following AUV in the carrier coordinate system is:

(5)

In the formula, is the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the yaw angle error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, It is the angle between the AUV carrier coordinate system rotating around the axis and the north-east coordinate system;

Differentiating with respect to time gives:

(6)

In the formula, is the differential of the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the differential of the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the differential of the yaw angle error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, To follow the x-axis speed of the AUV in the carrier coordinate system, To follow the yaw angle of the AUV in the carrier coordinate system, is the x-axis speed of the AUV in the carrier coordinate system, is the yaw angle of the leader AUV in the carrier coordinate system.

Furthermore, the design steps of the formation controller include:

Make the virtual leader AUV and the follower AUV consistent, that is:

(7)

Then

(8)

In the formula, is the first parameter, is the second parameter, is the third parameter, is the fourth parameter, is a dummy control variable;

Differentiate formula (8) and substitute it into formula (6) to obtain:

(9)

In the formula, is the differential of the first parameter, is the differential of the second parameter, is the differential of the third parameter, is the differential of the fourth parameter, is the differential of the yaw angle of the following AUV in the carrier coordinate system, is the differential of the dummy control variable;

make , then convert formula (9) into:

(10)

In the formula, are the derivatives of the first parameter, the second parameter, and the third parameter with respect to time, Controller parameters;

The formation controller is designed using the backstepping method, that is, first , the designed control law is as follows:

(11)

In the formula, is the first normal number, is the second normal number, is the third normal constant;

The Lyapunov function is selected as follows:

(12)

Taking the derivative of the Lyapunov function, we have:

when , and There is one that does not hour, ;

Based on formula (10), the following control law is selected:

In the formula, is the fourth normal constant;

The Lyapunov function is selected as follows:

(13)

Taking the derivative of the Lyapunov function, we have:

when There is one that does not hour, ;

In summary, the formation controller is designed as follows:

(14)

In the formula, For controller parameters.

Furthermore, the method further comprises:

If a suspicious target is found, the position and heading angle of the suspicious target are obtained according to the measurement information, and the relative distance and heading angle difference between the detection formation and the suspicious target are calculated according to the PP guidance method;

According to the relative distance and the difference in the yaw angle between the detection formation and the suspicious target, the ideal yaw and ideal position of the detection formation are obtained, and the ideal yaw is input into the yaw controller in the tracking controller to obtain the steering gear control torque, and the ideal position is input into the speed controller in the tracking controller to obtain the thrust of the propeller;

The tracking controller controls the detection formation according to the steering gear control torque and the thrust of the propeller to track the suspicious target.

The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

In the embodiments of the present disclosure, through the above-mentioned AUV cluster hierarchical agile collaborative control method for ocean detection scenarios, firstly, the group performance of the AUV cluster is analyzed according to the characteristics of the ocean detection scenario and the task requirements, and an AUV cluster hierarchical collaborative control architecture is proposed; then, facing the hierarchical collaborative control architecture, a hierarchical cluster agile collaborative network model is established according to the network characteristics such as high dynamic topology and high burst detection data of offshore area detection and control; finally, the AUV cluster hierarchical collaborative control architecture and the hierarchical cluster agile collaborative network model are combined with the information fusion results to analyze the control objectives and control requirements of the collaborative control architecture, and a corresponding formation control method is given.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

FIG1 shows a step diagram of a hierarchical agile collaborative control method for an AUV cluster for an ocean exploration scenario in an exemplary embodiment of the present disclosure;

FIG2 is a schematic diagram showing a hierarchical structure in an exemplary embodiment of the present disclosure;

FIG3 is a schematic diagram showing a control architecture of a UV cluster hierarchical collaborative control architecture in an exemplary embodiment of the present disclosure;

FIG4 shows a schematic diagram of a high dynamic self-organizing detection network in an exemplary embodiment of the present disclosure;

FIG5 is a schematic diagram showing a hierarchical cluster agile collaborative network model in an exemplary embodiment of the present disclosure;

FIG6 is a schematic diagram showing the positional relationship between the leader AUV and the virtual leader AUV in an exemplary embodiment of the present disclosure;

FIG7 is a schematic diagram showing the positional relationship between a virtual leading AUV and a following AUV in an exemplary embodiment of the present disclosure;

FIG8 shows an AUV formation control framework in an exemplary embodiment of the present disclosure;

FIG9 is a schematic diagram showing the principle of the PP guidance method in an exemplary embodiment of the present disclosure;

FIG. 10 shows a PID control framework in an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION

Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

In addition, the accompanying drawings are only schematic illustrations of the embodiments of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated descriptions will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities.

In this example implementation, a hierarchical agile collaborative control method for AUV clusters in an ocean exploration scenario is provided. Referring to FIG1 , the hierarchical agile collaborative control method for AUV clusters in an ocean exploration scenario may include: steps S101 to S104.

Step S101: Based on the ocean exploration scenario and the characteristics of each AUV, an AUV cluster hierarchical collaborative control architecture is established; wherein the AUV cluster includes a number of AUV subclusters, and an AUV subcluster includes a leading AUV and a number of follower AUVs;

Step S102: Based on the AUV cluster hierarchical collaborative control architecture and the detection task, a plurality of detection formations are established; wherein one detection formation corresponds to one AUV sub-cluster;

Step S103: for a detection formation, construct an AUV kinematic model, and calculate the position error and angle error between the actual position and the ideal position of each following AUV in the carrier coordinate system;

Step S104: the error between the actual position and the ideal position of the following AUV in the carrier coordinate system is input into the formation controller to calculate the expected angular velocity and the expected speed. The formation controller controls each following AUV according to the expected angular velocity and the expected speed, so that each following AUV and the leading AUV reach asymptotic stability.

Through the above-mentioned AUV cluster hierarchical agile collaborative control method for ocean detection scenarios, we first analyze the group performance of the AUV cluster according to the characteristics of the ocean detection scenario and task requirements, and propose an AUV cluster hierarchical collaborative control architecture; then, facing the hierarchical collaborative control architecture, according to the network characteristics of high dynamic topology and high burst detection data of offshore area detection and control, a hierarchical cluster agile collaborative network model is established; finally, the AUV cluster hierarchical collaborative control architecture and the hierarchical cluster agile collaborative network model are combined with the information fusion results to analyze the control objectives and control requirements of the collaborative control architecture, and give the corresponding formation control method.

Below, each step of the above-mentioned AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios in this example implementation will be described in more detail with reference to Figures 1 to 10.

In step S101, there are three main types of multi-AUV collaborative control structures, namely centralized, distributed, and hierarchical architectures. In the centralized architecture, there is a central node, and all AUV nodes communicate directly with the central node. In the distributed control structure, there is no central node, and AUVs communicate with each other. In the hierarchical structure, the upper node serves as the hierarchical control center of the lower node, and AUVs at the same level can communicate with the hierarchical control center or with each other.

Based on the characteristics of the ocean exploration scenario, this application applies a hierarchical collaborative control structure (i.e., the structure of the hierarchical collaborative control architecture of the AUV cluster), and the hierarchical collaborative control structure is shown in Figure 2. The hierarchical agile collaborative control architecture divides the AUV nodes into multiple levels. On the one hand, the multi-AUV system forms a hierarchical organizational structure according to different times and functions, and each upper node and several lower nodes form a formation. On the other hand, all nodes that form the formation are physically completely distributed, and information flow interactions can exist between any nodes. The upper node is locally concentrated on the collaborative layer, giving the top-level constraints of the cluster collaborative control design, organizing and coordinating tasks, information fusion, making decisions based on environmental models and mission objectives, and the capabilities of each member in the collaborative layer. It transmits instructions and data to the lower nodes through the information network to control the lower nodes to perform tasks.

According to the ocean exploration mission objectives and application scenarios, the requirements of the AUV cluster collaboration system are analyzed, and a task-oriented hierarchical agile collaborative control architecture is established.

The task-oriented hierarchical agile collaborative control architecture (i.e., the control architecture of the AUV cluster hierarchical collaborative control architecture) is shown in Figure 3 and is divided into three parts:

Information network layer: This layer is the basic layer in the AUV cluster collaborative control architecture, responsible for realizing communication and information transmission between AUV nodes. The characteristic of this layer is the optimal queuing delay. In order to achieve this characteristic, this application adopts an efficient communication protocol and data transmission mechanism to minimize communication delay and improve communication efficiency, so as to ensure the minimum queuing waiting time when transmitting information, so as to ensure the timeliness and stability of information transmission.

Data support layer: This layer is mainly responsible for processing, fusing and analyzing the marine environment data obtained by the AUV sensor to provide it to the control planning layer. Its characteristic is feature-level fusion, which effectively integrates multi-source data from different sensors and extracts useful feature information, such as target location, obstacles, current interference, etc., to provide accurate data support for control planning.

Control planning layer: This layer is the core layer in the AUV cluster collaborative control architecture, responsible for realizing the path planning, dynamic control and task allocation of the detection mission. The characteristic is that the delay margin is optimal. According to the feature fusion results of the data support layer, under the premise of ensuring the control response speed, it is dynamically adjusted and optimized according to the task requirements to minimize the delay of control planning, so as to improve the efficiency and flexibility of AUV cluster collaborative detection.

In addition, in view of the network characteristics of high dynamic topology and highly sudden detection data in offshore area detection and control, a layered agile collaborative network is established with the assistance of buoys, submersibles, unmanned boats and other nodes.

As shown in Figure 4, surface nodes such as wave gliders, mother ships, and buoys can exchange information through wireless communication. The mother ship is a first-level node, which is the command center and support platform in the network. It is responsible for monitoring and managing the lower-level nodes, and then performing data analysis, task planning, and command deployment on the entire network. Underwater acoustic communication is carried out between the submerged buoy, AUV, wave glider, and buoy, and a corresponding hierarchical structure can be formed according to different task requirements. The AUV can randomly access or exit the upper-level node when cruising underwater. The buoy and wave glider can both serve as the upper-level node of the AUV, and the underwater master AUV can also serve as the upper-level node of the slave AUV. The lower-level node uses underwater communication equipment to send the detected information to the upper-level node, which is then organized and coordinated and makes target decisions.

This application aims at network characteristics such as high burst detection data of the hierarchical collaborative control architecture, establishes a high-dynamic self-organizing detection network with optimal queuing delay, and designs a task collaboration structure with optimal delay margin. The network model is shown in Figure 5.

Node communication uses time slot division, and a reasonable time slot length evaluation is performed based on the performance analysis model. During the communication stage between the mother ship and the secondary node, data is sent according to the pre-set sending order and time slot length. The secondary node and the tertiary node communicate using frequency division access. The data packet sent by the secondary node to the mother ship is also used as a detection packet for AUV access. When all AUVs within the communication range receive the data packet sent by the secondary node to the mother ship, they reply to the secondary node with a REQ access packet. The secondary node can obtain the AUV's position and speed information through the REQ packet and record it.

Each data packet still contains the updated position and speed information of each AUV. The mother ship parses the data and updates the AUV data table, and broadcasts an ACK data packet to confirm each data packet.

Establish AUV cluster communication protocol.

The communication protocols of existing underwater acoustic equipment have drawbacks such as narrow bandwidth, low rate, complex underwater acoustic environment and inconsistent equipment manufacturer protocols, which make it impossible to achieve stable and efficient information exchange between AUVs. In order to effectively overcome the drawbacks of underwater acoustic communication, this application optimizes these drawbacks and adopts an underwater acoustic modem with unicast and networking functions, which improves data transmission efficiency and communication quality, enhances communication robustness, and realizes interoperability between devices.

The communication between AUVs adopts a communication protocol based on an underwater acoustic modem. The protocol requires a total of 32 bytes. The protocol structure is shown in Table 1.

Table 1 Communication protocol structure

The information header is used as a synchronization header for frame synchronization and occupies 2 bytes. The tail is used as a data check bit to verify the data and occupies 2 bytes. The source address occupies 2 bytes and indicates the address of the source AUV. AUV communication adopts a broadcast networking mode, so the address of the target AUV is not marked in the protocol. The source role indicates the control architecture layer to which the AUV belongs in the formation, which occupies 3 bytes. 001 indicates the information network layer, 010 indicates the data support layer, and 100 indicates the control planning layer. The role type corresponding to each flag bit is not completely independent. For example, 101 means that the current AUV belongs to both the control planning layer and the information network layer. The third field indicates the level of the information sender in the formation system, which occupies 3 bytes and can represent up to 8 different levels.

There are different types of mission status for different roles. Currently, AUV has 8 states: roaming, assembly, search, detection, cruise, standby, return and failure. As shown in Table 2, it is represented by the fourth field "mission status", which occupies 3 bytes.

Table 2 AUV mission status and corresponding number

The communication status indicates the communication status between the local AUV and the other AUVs. It can determine whether there is a communication failure with the AUV. It occupies 4 bytes, and each byte corresponds to an AUV. "0" indicates that the source AUV had a communication abnormality with the AUV last time, and "1" indicates normal. If the number of AUVs is more than 4, this field needs to be expanded.

The posture information field contains the longitude and latitude, heading angle, depth and speed of the source AUV, which is mainly used to coordinate the formation and avoid collisions between AUVs, and occupies a total of 13 bytes. This field is a numerical type of data. In order to reduce the occupation of communication bandwidth, this field is stored in hexadecimal form. Longitude and latitude each occupy 4 bytes. The hundreds digit of longitude rarely changes and can be preset in the configuration file according to the specific sea area. Speed occupies 1 byte and can be expressed in the range of -5.0~5.0 meters per second. Depth and heading each occupy 2 bytes, the depth range is 0~999 meters, and the heading ranges from 0~359 degrees.

The "collaborative data" field is the main content of the communication protocol, which consists of a sequence number, information type, and data content, as shown in Table 3.

Table 3 Collaborative data field composition

The information type occupies 1 byte. Currently, there are several types of collaborative data: information test, assembly formation, target identification, formation configuration and forwarding information, which are numbered 1, 11, 21, 14/101 respectively. The available bandwidth of data content is 13 bytes, including the target AUV address and 5 parameters for specific description of the corresponding information type. The target AUV address occupies 2 bytes, the first 2 parameters each occupy 4 bytes, which are used to describe the longitude and latitude, and the last 3 parameters each occupy 1 byte.

The assembly formation specifies the ideal time and final heading to arrive at the starting point; the identification target transmits the location of the detection target and the credibility of the detection target; the encapsulation of the forwarded information complies with the encapsulation rules of general collaborative data, that is, it is encapsulated in the following way based on the original information, "information type (i.e. forwarded information) + forwarded information content", where the forwarded information content is "information source + forwarded information type + forwarded information content", and the information source represents the original sender of the forwarded information. Two points need to be noted: first, a certain AUV only sends/forwards the same information once; second, the information carrying capacity of the forwarded information is reduced, and the fields describing the information are shortened to two 4-byte fields and one 1-byte field.

In step S102 to step S104, in the application scenario of ocean collaborative detection, due to the wide ocean space area and high requirements for task execution efficiency, the current domestic and foreign methods of coverage formation detection are mostly used. Faced with the complex and changeable ocean environment, long-term ocean detection can easily bring various problems to the AUV system, such as communication failure, actuator failure, etc., resulting in missed detection of the target area and inability to complete full coverage of the search area. Therefore, it is necessary for the AUV system to design an effective collaborative strategy to ensure effective search of the area. In the hierarchical agile control system, the upper node serves as the hierarchical control center of the lower node, and shares the faulty AUV to the lower node through the communication network, so that the edge AUV can make formation compensation.

In order to ensure that the system can achieve full coverage of the area, the formation system needs to maintain long-term stability and robustness, and has strict requirements on the design of the formation controller. This application targets a hierarchical structure, assumes that the master AUV is the superior node of the slave AUV, adopts a leader-follower formation model, and designs a controller based on the backstepping method. According to the posture information of the leader AUV, a virtual leader is generated according to the geometric relationship, the state of the follower AUV is adjusted, and the path following of the follower AUV is completed, thereby improving the efficiency of completing the collaborative detection task.

When the AUV detection system finds a target, the formation system will adopt a corresponding strategy to track the target. This application designs a target tracking guidance strategy and a target tracking controller so that the AUV can track the target persistently and stably.

This application adopts a three-degree-of-freedom two-dimensional plane formation model, and only considers the linear motion of the AUV along the x- axis of the carrier and the yaw motion along the z -axis at a fixed depth.

Assuming that the multi-AUV model contains N single AUVs, the kinematic model of the nth AUV at a constant depth can be expressed as:

(1)

In the formula, is the position and attitude information of the i- th AUV in the north-east coordinate system, is the x- axis coordinate of the ith AUV in the north-east coordinate system, is the y- axis coordinate of the i -th AUV in the north-east coordinate system, is the yaw angle of the i- th AUV in the north-east coordinate system, is the velocity information and angular velocity information of the i - th AUV in the carrier coordinate system, For the The x- axis speed of an AUV in the carrier coordinate system, is the y- axis speed of the i - th AUV in the carrier coordinate system, is the yaw angular velocity of the i - th AUV in the carrier coordinate system, is the transformation matrix from the north-east coordinate system to the carrier coordinate system, The transformation matrix from the north-east coordinate system to the carrier coordinate system is expressed as the following expression:

(2)

In the formula, It is the angle between the carrier coordinate system rotated around the axis and the north-east coordinate system;

The position and attitude information of the leading AUV is used Indicates that the position and attitude information of the following AUV is expressed as Directly, assuming that the ideal distance between the leader AUV and the virtual leader AUV is The ideal angle is , as shown in Figure 6, the position of the virtual leader (i.e., the virtual leader AUV) is as follows:

(3)

In the formula, is the x- axis coordinate of the virtual leader AUV in the north-east coordinate system, is the y- axis coordinate of the virtual leader AUV in the north-east coordinate system, is the yaw angle of the virtual leader AUV in the north-east coordinate system, is the x- axis coordinate of the leading AUV in the north-east coordinate system, is the y- axis coordinate of the leading AUV in the north-east coordinate system, is the yaw angle of the leading AUV in the north-east coordinate system, The ideal distance between the leader AUV and the virtual leader AUV, Ideal angle for the leader AUV and the virtual leader AUV.

use It represents the error between the actual position of the following AUV and the virtual leading AUV. In the north-east coordinate system, the AUV error model is:

(4)

In the formula, is the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the north-east coordinate system, is the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the north-east coordinate system, is the yaw angle error between the actual position of the following AUV and the position of the virtual leader AUV in the north-east coordinate system, is the x- axis coordinate of the AUV in the north-east coordinate system, is the y- axis coordinate of the AUV in the north-east coordinate system, is the yaw angle of the following AUV in the north-east coordinate system;

Taking the position of the virtual leader AUV as the coordinate origin, the carrier coordinate system is established, as shown in Figure 7.

use The error between the ideal position and the actual position of the following AUV in the carrier coordinate system is:

(5)

In the formula, is the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the yaw angle error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, It is the angle between the AUV carrier coordinate system rotating around the axis and the north-east coordinate system;

Differentiating with respect to time gives:

(6)

In the formula, is the differential of the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the differential of the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the differential of the yaw angle error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, To follow the x-axis speed of the AUV in the carrier coordinate system, To follow the yaw angle of the AUV in the carrier coordinate system, is the x-axis speed of the AUV in the carrier coordinate system, is the yaw angle of the leader AUV in the carrier coordinate system.

Design the controller so that the virtual leader AUV and the follower AUV are consistent, that is:

(7)

The controller framework is shown in Figure 8.

To facilitate calculation, the following transformation is defined:

(8)

In the formula, is the first parameter, is the second parameter, is the third parameter, is the fourth parameter, is a dummy control variable;

Differentiate formula (8) and substitute it into formula (6) to obtain:

(9)

In the formula, is the differential of the first parameter, is the differential of the second parameter, is the differential of the third parameter, is the differential of the fourth parameter, is the differential of the yaw angle of the following AUV in the carrier coordinate system, is the differential of the dummy control variable;

make , then formula (9) can be expressed as:

(10)

In the formula, are the derivatives of the first parameter, the second parameter, and the third parameter with respect to time, is the controller parameter;

The formation controller is designed using the backstepping method, that is, first , the designed control law is as follows:

(11)

In the formula, is the first normal number, is the second normal number, is the third normal constant;

The Lyapunov function is selected as follows:

(12)

Taking the derivative of the Lyapunov function, we have:

Obviously when , and There is one that does not hour, ;

According to the Lyapunov stability theorem, the subsystem is asymptotically stable.

On this basis, for formula (10), the following control law is selected:

In the formula, is the fourth normal constant;

The Lyapunov function is selected as follows:

(13)

Taking the derivative of the Lyapunov function, we have:

Obviously when There is one that does not hour, .

According to the Lyapunov stability theorem, the system is asymptotically stable.

In summary, the formation controller is designed as follows:

(14)

In the formula, For controller parameters.

Design tracking guidance algorithm for target tracking application scenarios.

This application adopts the PP guidance method to improve the anti-interference ability of target tracking.

As shown in Figure 9, assuming that the AUV system discovers the target P during formation detection, the target position is obtained based on the sensor measurement information. , the position of the AUV is , the yaw angle is .

According to the principle of PP guidance method, the relative distance between AUV and target can be obtained by the following formula:

The difference in heading angle between the AUV and the target is obtained by the following formula:

According to the definition of the PP guidance method, the control goal of target tracking is to design a controller so that

The structure of AUV is very complex, and its structural parameters are difficult to measure accurately, and can only be determined by debugging such as tank tests. Considering engineering practice, this application adopts PID control method to control the heading and speed of AUV.

The PID control principle is shown in formula (15):

(15)

in, is the proportional control coefficient, is the integral control coefficient, is the differential control coefficient.

PID control algorithm has been widely used in engineering practice. Currently, PID control can be divided into two forms: position PID and incremental PID. The error of position PID accumulates continuously when calculating sampling. Compared with position PID, the calculation amount of incremental PID is much smaller. Considering the actual engineering application, this application adopts incremental PID controller as the motion controller of AUV.

The mathematical expression of incremental PID is as follows:

The tracking controller framework is shown in Figure 10.

The position and distance of the target are measured by the AUV's sensors. According to the principle of the PP guidance method, the ideal value of the AUV's heading can be calculated and used as the control input of the PID controller to obtain the AUV's rudder control torque, thereby making the AUV's heading close to the target heading. At the same time, according to the PP guidance method, the distance error information is used as the control input of the AUV's speed controller to output the thrust of the thruster, so that the distance error is continuously reduced, so that the AUV can track the target stably and persistently.

Determines the direct control effect of the controller, If increases, the steady-state error decreases, but the dynamic response of the system will deteriorate. Too large a value will affect the stability of the system; The introduction of eliminates the steady-state error, but too large an integral coefficient will affect the dynamic performance of the system; It can speed up the response of the system, but reduce the anti-interference ability of the system. The three parameters determine the control effect of the controller from different angles and need to be adjusted and calibrated in actual application.

Through the above-mentioned AUV cluster hierarchical agile collaborative control method for ocean detection scenarios, we first analyze the group performance of the AUV cluster according to the characteristics of the ocean detection scenario and task requirements, and propose an AUV cluster hierarchical collaborative control architecture; then, facing the hierarchical collaborative control architecture, according to the network characteristics of high dynamic topology and high burst detection data of offshore area detection and control, a hierarchical cluster agile collaborative network model is established; finally, the AUV cluster hierarchical collaborative control architecture and the hierarchical cluster agile collaborative network model are combined with the information fusion results to analyze the control objectives and control requirements of the collaborative control architecture, and give the corresponding formation control method.

In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims (8)

1. A hierarchical agile collaborative control method for AUV clusters for ocean exploration scenarios, characterized in that the method includes: Based on the ocean exploration scenario and the characteristics of each AUV, a hierarchical collaborative control architecture of an AUV cluster is established; wherein an AUV cluster includes several AUV subclusters, and an AUV subcluster includes a leading AUV and several follower AUVs; Based on the AUV cluster hierarchical collaborative control architecture and detection tasks, several detection formations are established; one detection formation corresponds to one AUV sub-cluster; For a detection formation, an AUV kinematic model is constructed, and the position error and angle error between the actual position and the ideal position of each following AUV in the carrier coordinate system are calculated; The error between the actual position and the ideal position of the following AUV in the carrier coordinate system is input into the formation controller to calculate the expected angular velocity and the expected speed. The formation controller controls each following AUV according to the expected angular velocity and the expected speed, so that each following AUV and the leading AUV can reach asymptotic stability. 2. According to the AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios according to claim 1, it is characterized in that the method also includes: According to the network characteristics of ocean exploration scenarios, a hierarchical cluster agile collaborative network model is established, and a communication protocol based on an acoustic modem is adopted. The leader AUV and each follower AUV, each leader AUV, and the AUV cluster and collaborative nodes all communicate using the hierarchical cluster agile collaborative network model and a communication protocol based on an acoustic modem. 3. According to the AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios in claim 2, it is characterized in that the communication protocol based on the underwater acoustic modem includes a header, a source address, a source role, a source level, a task status, a communication status, a posture information, collaborative data and a tail in sequence. 4. According to the AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios described in claim 3, it is characterized in that the structure of the AUV cluster hierarchical collaborative control architecture is a hierarchical structure. In the hierarchical structure, the leading AUV is the hierarchical control center of the following AUVs, the leading AUV communicates with each following AUV, and each following AUV communicates with each other. The control architecture of the AUV cluster hierarchical collaborative control architecture includes an information network layer, a data support layer and a control planning layer. 5. According to claim 4, the AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios is characterized in that the step of constructing an AUV kinematic model and calculating the error between the actual position and the ideal position of each follower AUV in the carrier coordinate system includes: For a detection formation, the AUV kinematic model is constructed based on the position and attitude information of the leading AUV and each following AUV in the AUV cluster in the north-east coordinate system, and the velocity information and angular velocity information of the leading AUV and each following AUV in the carrier coordinate system; Based on the AUV kinematic model, the ideal distance and angle between the leader AUV and the virtual leader AUV are set, and the position and attitude information of the virtual leader AUV in the north-east coordinate system is calculated; According to the position and attitude information of the virtual leader AUV in the north-east coordinate system and the position and attitude information of the follower AUV in the north-east coordinate system, the position error and angle error of the virtual leader AUV and the follower AUV in the north-east coordinate system are obtained; The carrier coordinate system is established with the position of the virtual leader AUV as the coordinate origin; According to the position error and angle error of the virtual leader AUV and the follower AUV in the north-east coordinate system, the position error and angle error between the actual position and the ideal position of the follower AUV in the carrier coordinate system are obtained. 6. According to the AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios according to claim 5, it is characterized in that the expression of the AUV kinematic model is: (1) In the formula, is the position and attitude information of the i- th AUV in the north-east coordinate system, for The differential of is the x- axis coordinate of the ith AUV in the north-east coordinate system, is the y- axis coordinate of the i -th AUV in the north-east coordinate system, is the yaw angle of the i- th AUV in the north-east coordinate system, is the velocity information and angular velocity information of the i - th AUV in the carrier coordinate system, For the The x- axis speed of an AUV in the carrier coordinate system, is the y- axis speed of the i - th AUV in the carrier coordinate system, is the yaw angular velocity of the i - th AUV in the carrier coordinate system, is the transformation matrix from the north-east coordinate system to the carrier coordinate system, where (2) In the formula, It is the angle between the carrier coordinate system rotated around the axis and the north-east coordinate system; The virtual leaders are: (3) In the formula, is the x- axis coordinate of the virtual leader AUV in the north-east coordinate system, is the y- axis coordinate of the virtual leader AUV in the north-east coordinate system, is the yaw angle of the virtual leader AUV in the north-east coordinate system, is the x- axis coordinate of the leading AUV in the north-east coordinate system, is the y- axis coordinate of the leading AUV in the north-east coordinate system, is the yaw angle of the leading AUV in the north-east coordinate system, The ideal distance between the leader AUV and the virtual leader AUV, The ideal angle for the leader AUV and the virtual leader AUV; use It represents the error between the actual position of the following AUV and the virtual leading AUV. In the north-east coordinate system, the AUV error model is: (4) In the formula, is the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the north-east coordinate system, is the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the north-east coordinate system, is the yaw angle error between the actual position of the following AUV and the position of the virtual leader AUV in the north-east coordinate system, is the x- axis coordinate of the AUV in the north-east coordinate system, is the y- axis coordinate of the AUV in the north-east coordinate system, is the yaw angle of the following AUV in the north-east coordinate system; use The error between the ideal position and the actual position of the following AUV in the carrier coordinate system is: (5) In the formula, is the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the yaw angle error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, It is the angle between the AUV carrier coordinate system rotating around the axis and the north-east coordinate system; Differentiating with respect to time gives: (6) In the formula, is the differential of the x- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the differential of the y- axis error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, is the differential of the yaw angle error between the actual position of the following AUV and the position of the virtual leading AUV in the carrier coordinate system, To follow the x-axis speed of the AUV in the carrier coordinate system, To follow the yaw angle of the AUV in the carrier coordinate system, is the x-axis speed of the AUV in the carrier coordinate system, is the yaw angle of the leader AUV in the carrier coordinate system. 7. According to claim 6, the AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios is characterized in that the design steps of the formation controller control include: Make the virtual leader AUV and the follower AUV consistent, that is: (7) Then (8) In the formula, is the first parameter, is the second parameter, is the third parameter, is the fourth parameter, is a dummy control variable; Differentiate formula (8) and substitute it into formula (6) to obtain: (9) In the formula, is the differential of the first parameter, is the differential of the second parameter, is the differential of the third parameter, is the differential of the fourth parameter, is the differential of the yaw angle of the following AUV in the carrier coordinate system, is the differential of the dummy control variable; make , then convert formula (9) into: (10) In the formula, are the derivatives of the first parameter, the second parameter, and the third parameter with respect to time, is the controller parameter; The formation controller is designed using the backstepping method, that is, first , the designed control law is as follows: (11) In the formula, is the first positive constant, is the second normal number, is the third normal constant; The Lyapunov function is selected as follows: (12) Taking the derivative of the Lyapunov function, we have: when , and There is one that does not hour, ; Based on formula (10), the following control law is selected: In the formula, is the fourth normal constant; The Lyapunov function is selected as follows: (13) Taking the derivative of the Lyapunov function, we have: when There is one that does not hour, ; In summary, the formation controller is designed as follows: (14) In the formula, For controller parameters. 8. The AUV cluster hierarchical agile collaborative control method for ocean exploration scenarios according to claim 7, characterized in that the method also includes: If a suspicious target is found, the position and heading angle of the suspicious target are obtained according to the measurement information, and the relative distance and heading angle difference between the detection formation and the suspicious target are calculated according to the PP guidance method; According to the relative distance and the difference in the yaw angle between the detection formation and the suspicious target, the ideal yaw and ideal position of the detection formation are obtained, and the ideal yaw is input into the yaw controller in the tracking controller to obtain the steering gear control torque, and the ideal position is input into the speed controller in the tracking controller to obtain the thrust of the propeller; The tracking controller controls the detection formation according to the steering gear control torque and the thrust of the propeller to track the suspicious target.