CN117687322B - AUV cluster countermeasure simulation system and method considering individual faults - Google Patents
AUV cluster countermeasure simulation system and method considering individual faults Download PDFInfo
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Abstract
The invention provides an AUV cluster countermeasure simulation system and method considering individual faults, and belongs to the technical field of autonomous underwater vehicles. The system comprises: the system comprises a user interaction layer, a decision support layer, a simulation core layer, a data model layer and a support service layer; the user interaction layer is the topmost layer of the system, and initial configuration input is carried out on the whole AUV cluster countermeasure simulation process; the decision support layer is used for carrying out fault detection and task planning on the AUV cluster; the simulation core layer is used for simulating the ocean environment and dynamic changes and simulating the running state of the AUV cluster; the data model layer is used for collecting sensor data and providing data for the simulation core layer; the support service layer is used for recording the abnormal state and maintaining and upgrading the system. The technical scheme of the invention solves the problem that fault diagnosis is less considered for AUV cluster countermeasure in the prior art.
Description
Technical Field
The invention relates to the technical field of autonomous underwater vehicles, in particular to an AUV cluster countermeasure simulation system and method considering individual faults.
Background
Autonomous Underwater Vehicle (AUV) clusters are one of the important technological developments in the field of underwater exploration and operation. The AUV cluster is composed of a plurality of AUVs, and can realize more efficient and flexible underwater task execution, such as marine exploration, marine environment monitoring, underwater search and rescue and the like through cooperative work and mutual communication. However, in practical applications, AUV clusters face a number of challenges, one of which is the impact of individual failures.
Individual failure refers to a failure or failure of one or more individuals in an AUV cluster, resulting in an inability to perform tasks normally or to communicate effectively with other AUVs. Such failure phenomena may be caused by various factors including mechanical failure, electronic component failure, communication failure, and the like. The occurrence of individual failures may have a serious impact on the performance and task completion capability of the overall AUV cluster.
In military applications, the AUV cluster may perform tasks including reconnaissance, surveillance, and mine search. Chase-and-flee games can be used to simulate the countering actions of both sides of the friend or foe, wherein the chaser may be the party attempting to capture or monitor the enemy AUV, and the escapers are the parties attempting to evade the monitoring of the opponent or foe. The ability of the AUV cluster to combat hostile underwater devices can be enhanced by using a chase game strategy. Less research work is currently taking into account the impact of individual faults on the AUV cluster and providing corresponding countermeasure simulation systems and methods to evaluate and cope with such impact. Therefore, developing an AUV cluster countermeasure simulation system and method considering individual faults has important theoretical significance and practical application value.
First, an AUV cluster countermeasure simulation system and method that accounts for individual faults may help researchers better understand the impact of individual faults on AUV cluster behavior and performance. By simulating and analyzing the occurrence and propagation process of individual faults, the vulnerability and the robustness of the AUV cluster system can be disclosed, so that the reliability and the stability of the system can be better known. This helps researchers fully consider the effects of individual faults and take corresponding measures to improve the reliability and flexibility of the system when designing and developing an AUV cluster system.
Second, the challenge simulation system and method may be used to evaluate and improve the task performance capabilities and robustness of the AUV cluster. By introducing an individual fault model, the performance of the AUV cluster under different fault conditions can be quantitatively evaluated and compared to determine weak links in system design and task planning, and a corresponding improvement strategy is provided. This helps to optimize the task allocation and path planning algorithms for the AUV cluster, improving the efficiency and reliability of overall task execution.
Furthermore, the AUV cluster challenge simulation system that accounts for individual faults may also be used to validate and optimize cluster management algorithms and cooperative control strategies. By simulating fault conditions in a simulation environment, the robustness and adaptability of the algorithm can be tested and verified, so that the effectiveness and reliability of the algorithm are improved. This helps researchers better understand the performance of cluster management algorithms and cooperative control strategies in the event of a failure and provides guidance for AUV cluster management in practical applications.
In summary, developing an AUV cluster countermeasure simulation system and method that consider individual faults has important significance in promoting the development of AUV cluster technology. The influence of individual faults on the AUV cluster is deeply researched, and a corresponding simulation system and method are provided, so that guidance can be provided for the design, optimization and application of the AUV cluster, the task execution capacity and the robustness of the AUV cluster are improved, and the further development of the underwater detection and operation field is promoted. Thus, there is a need for an AUV cluster countermeasure simulation system and method that accounts for individual failures.
Disclosure of Invention
The invention mainly aims to provide an AUV cluster countermeasure simulation system and method considering individual faults, so as to solve the problems in the prior art.
To achieve the above object, the present invention provides an AUV cluster countermeasure simulation system considering individual faults, including: the system comprises a user interaction layer, a decision support layer, a simulation core layer, a data model layer and a support service layer; the user interaction layer is the topmost layer of the system, initial configuration input is carried out on the whole AUV cluster countermeasure simulation process, and data of the decision support layer, the simulation core layer, the data model layer and the support service layer are input to the user interaction layer for display; the decision support layer is used for carrying out fault detection and task planning on the AUV cluster; the simulation core layer is used for simulating the ocean environment and dynamic changes and simulating the running state of the AUV cluster; the data model layer is used for collecting sensor data and providing data for the simulation core layer; the support service layer is used for recording the abnormal state and maintaining and upgrading the system.
The invention also provides an AUV cluster countermeasure simulation method considering individual faults, which comprises the following steps:
S1, performing fault detection on the AUV by using a sensor, starting to calculate a matching combination when the fault is detected, and matching relatively nearest evasions for each chaser in the AUV cluster, wherein the chaser in the matching combination adopts an interception strategy based on an escape space.
S2, updating the cluster position after each constant time step is continued in the AUV cluster pursuit cluster countermeasure processSum and quantityThereby re-matching.
S3, for all evades in each constant time stepStatistics of captured and escape conditions of (a), wherein。
S4, if the user escapesCaptured or escaped, the escapement is then assembled from the escapement setRemoved from the collection and added to the corresponding captured collectionAnd escape set。
S5, checking an escape setWhether or not the set is empty, if not, indicating that there is still an escape person in the guard area for being captured or escapedAnd (3) if the internal activity is performed, recalculating the matching combination by utilizing the steps S1-S4, and continuing to fight, otherwise ending the fight.
Further, the step S1 specifically includes the following steps:
S1.1, setting the AUV cluster to track and fight against the two routes Individual chasers and the methodThe escape person is composed of the following players in a set ofThe set of evades is。
Wherein,AndRespectively the chasersAnd escapersAt the time ofIs a position of (2); at the position ofThe dynamics of the AUV are described by the following decoupling system:
。
Wherein, AndIs the chasing personAnd escapersIs used for the initial position of the (c),AndRespectively represent the chasersAnd escapersThe ratio of the speeds of the chaser and the escapement isChasing personAnd escapersAt the time ofIs their respective instantaneous headingAnd。
AUV chaserAttack capture range of (2)In the initial state, the chaser team and the escapement team are distributed in the guard areaIn the guard areaThe outside area is the target area; The goal of the chasing team is in the guard areaAs many escapers as possible are captured, and the objective of the team of escapers is to get rid of the chasers from entering the target area。
S1.2 using potential functionsTo define escape space specificallyThe expression is:
。
Wherein the potential function With respect toFor gradients of (2)The expression is:
。
S1.3, escape space set is defined as ; Chasing personThe interception strategy of (1) is to face to escape spaceDistance from the target areaThe nearest pointAnd (5) movement.
The invention has the following beneficial effects: in the AUV cluster countermeasure process adopting the chase game algorithm, a fault diagnosis mechanism for individuals is added to fuse rolling optimization, the influence caused by individual faults is considered in the cluster countermeasure simulation process, and an adjustment method for cluster countermeasure under the condition is provided.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 shows a block diagram of an AUV cluster challenge-simulation system that accounts for individual faults in accordance with the present invention.
Fig. 2 shows a flowchart of an AUV cluster challenge simulation method of the present invention that considers individual faults.
Fig. 3 shows a block diagram of an AUV platform system.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
An AUV cluster countermeasure simulation system that accounts for individual faults as shown in fig. 1, comprising: the system comprises a user interaction layer, a decision support layer, a simulation core layer, a data model layer and a support service layer; the user interaction layer is the topmost layer of the system, initial configuration input is carried out on the whole AUV cluster countermeasure simulation process, and data of the decision support layer, the simulation core layer, the data model layer and the support service layer are input to the user interaction layer for display; the method is directly oriented to the user, and provides a man-machine interaction interface; the decision support layer is used for carrying out fault detection and task planning on the AUV cluster; the simulation core layer is used for simulating the ocean environment and dynamic changes and simulating the running state of the AUV cluster; the data model layer is used for collecting sensor data and providing data for the simulation core layer; the support service layer is used for recording the abnormal state and maintaining and upgrading the system.
The AUV cluster reactance simulation system provided by the invention comprises: the system comprises a user interaction layer, a decision support layer, a simulation core layer, a data model layer and a support service layer.
The user interaction layer is the top layer of the system and comprises: the AUV cluster input and configuration module, the real-time state display module and the simulation control module; the user interaction layer directly faces the user and provides a man-machine interaction interface. The user sets initial parameters and operation conditions of the cluster, such as the number of the two parties of the cluster, specific initial positions, initial motion states and the like, through the AUV cluster input and configuration module.
The real-time state display module is responsible for feeding back dynamic information in the simulation process to a user, wherein the three-dimensional situation display module and the key index monitoring module respectively provide visual space position information and important performance index information.
The simulation control module allows a user to start, pause or terminate the simulation process according to the needs, so that the real-time control of the simulation flow is realized.
The decision support layer bears the intelligent decision function of the simulation system, and comprises the following steps: the system comprises a task planning and strategy module and a fault adaptation and management module. The task planning and strategy module comprises: the system comprises a task decomposition and distribution module and a strategy generation and optimization module. The task decomposition and distribution module deconstructs and distributes complex tasks, and the strategy generation and optimization module improves the efficiency and effect of task completion through a rolling optimization algorithm based on escape space interception strategy.
The fault adaptation and management module comprises a fault detection module, a fault influence evaluation module and an adaptation strategy making module, a complete fault coping mechanism is formed, and the AUV cluster can be matched again in time when an individual fails, so that high-efficiency task execution capacity is maintained.
The simulation core layer forms the core of the whole simulation system and bears the main responsibility of the simulation operation. The simulation core layer comprises: the system comprises an environment and dynamic module, an AUV cluster simulation engine management module and an AUV interaction module.
The environment and dynamic simulation module comprises an environment parameter simulation module and a dynamic change response module. The simulation system provides a realistic ocean environment and dynamic change for simulation, and the environment is not limited to ocean, but can be other underwater environments suitable for AUV cluster operation such as lakes, rivers and the like.
The AUV cluster simulation engine management module is responsible for the operation of simulation, covers key functions such as a chase-back task interface module, a simulation control module, a time management module, an event processing module and the like, and ensures the consistency and consistency of the simulation.
The AUV interaction module comprises an AUV communication module and an AUV cluster cooperation module; communication and collaboration mechanisms between AUVs are simulated, which is critical to the simulation of cluster behavior.
A data model layer, comprising: a physical database and a simulation data management module. The physical database comprises various necessary data such as an AUV model library, an environment model library, a pursuit task library, a simulation rule library, a simulation database, an abnormal state library and the like, and provides a rich input source for simulation.
The simulation data management module ensures that data generated in the simulation process can be effectively collected, stored, analyzed and processed, so that a physical database is further enriched, and a data base is provided for subsequent decision support and learning optimization.
The support service layer provides auxiliary functions required for system operation. The abnormal state recording module comprises: the system comprises a log recording module and a fault tracking and analyzing module; log information in the simulation process is recorded, faults are tracked and analyzed, the faults are conveniently learned to further avoid similar faults, and the faults can be recognized more timely when the same or similar faults occur.
The learning and optimizing module learns by utilizing the collected data and feedback to optimize the behavior of the AUV and improve the self-adaptive capacity to minimize abnormal situations.
The system maintenance and upgrading module comprises a maintenance tool module and a strategy upgrading module. The abnormal state recording module and the learning and optimizing module are combined to maintain the fault abnormality, so that the system can continuously run and adapt to new requirements.
The method provided by the invention comprises the following steps: simulation preparation, simulation process and simulation analysis 3 phases.
In the simulation preparation stage, the AUV cluster is input and configured through AUV cluster system modeling and initialization, wherein the AUV cluster comprises the number of both clusters, specific initial positions, initial motion states and the like.
And modeling the AUV cluster countermeasure environment, and defining the pursuit countermeasure scope on the basis of establishing the countermeasure environment by using underwater environments such as ocean, lake and river which are suitable for the AUV cluster operation without strict limitation to the environment.
The initial conditions, environment and chase-challenge range provide for input preparation for the computation of matching combinations in the simulation process.
In the simulation preparation phase, it is crucial to establish a fault detection mechanism that will be in a monitoring operation state throughout the simulation process.
In the simulation process stage, after receiving the input of the simulation preparation stage, the AUV cluster starts to operate a rolling optimization algorithm based on an escape space interception strategy, the fault detection mechanism is always in a monitoring state, once the occurrence of a fault chaser individual is found, the fault chaser individual is immediately interfered, and after the fault chaser individual is removed, matching combination is carried out again, so that subsequent countermeasure is carried out.
The countermeasure state in the simulation process stage is always output in real time, a user can observe the state of AUV cluster countermeasure in the simulation process in real time, and simulated data are collected so as to simulate the processing of the analysis stage.
The simulation analysis stage analyzes the pursuit efficiency of the cluster pursuit and evasion countermeasure based on the data acquired in the simulation process, analyzes the fault data in the simulation process, and provides a data basis for subsequent guarantee and optimization.
As shown in FIG. 3, the invention also provides an AUV platform system which consists of 4 parts of a submersible platform, a power system, a navigation control system and a data communication system.
The submersible platform is composed of a shell, a tail wing, a control surface and other key external components, the shape of the shell is not particularly limited, and the autonomous underwater robots with the torpedo-shaped revolving body, the torpedo-shaped non-revolving body and other bionic shapes can be used for stabilizing and controlling the direction.
The power system comprises a high-efficiency propeller which is responsible for generating thrust; the motor is matched with the motor and converts the electric energy into mechanical energy; an electronic speed regulator for accurately controlling the rotation speed of the motor; and a high-energy battery for providing durable power for the whole system.
The navigation control system is composed of a combined navigation system, an intelligent control system and an underwater positioning system. Integrated navigation systems typically incorporate a variety of sensor inputs, such as Inertial Navigation Systems (INS) and sonar, to improve navigation accuracy; the intelligent control system adopts advanced control methods such as fuzzy control, active disturbance rejection control, sliding mode control and the like to ensure that the intelligent control system can keep a stable navigation situation.
The data communication system consists of a data acquisition unit, a data transmission unit, a data storage unit and a communication interface unit. The data acquisition unit is responsible for gathering information of the AUV sensor; the data transmission unit ensures that these information can be sent to the operator in real time; the data storage unit is responsible for storing important data for a long time; the communication interface unit provides data transmission and communication capability with other AUVs, AUV mother vessels or shore bases.
The invention also provides an AUV individual fault diagnosis simulation system, which comprises an AUV fault injection simulation system, an AUV virtual operation and control system, an AUV fault detection and evaluation system and an AUV simulation system.
The AUV fault injection simulation system can simulate fault conditions possibly encountered by the AUV in a complex underwater environment.
The fault scenario generator is responsible for designing and storing various possible fault conditions and their specific parameter settings.
The fault effect simulator accurately simulates the specific influence of faults on AUV operation based on the setting of the fault scene generator. Such simulation includes not only the immediate effect of the fault as it occurs, but also long term effects and cascading of faults to other systems of the AUV.
The AUV virtual operation and control system allows an operator to perform intuitive AUV operations in a simulation environment to provide a user-friendly operation interface and further simulation control.
The virtual environment builder creates a three-dimensional simulated environment that accurately reproduces the underwater scene of AUV operation, including physical characteristics and dynamic changes.
The AUV mother vessel/shore-based operation control simulator simulates the steering system of the AUV, allowing the user to perform steering exercises in a virtual environment in order to make a quick response in an actual task.
The task control center is responsible for managing simulation tasks and instruction flows of the AUV, ensuring that simulation operations are kept synchronous with actual conditions, and receiving input data from the virtual environment constructor so as to optimize task execution strategies.
The AUV fault detection and assessment system is responsible for realizing real-time monitoring of AUV performance and safety.
The fault state model includes specific causes that cause the fault mode, including design defects, material fatigue, operational errors, improper maintenance, environmental factors, and the like. Failure mode refers to the specific manner in which a component or system of the AUV fails, for example, the propulsion system may fail due to motor failure, power supply failure, or control software issues.
The fault analysis engine performs in-depth analysis of the abnormal behavior to determine the potential fault type and severity. The analysis of this sub-module is crucial to decide whether intervention is needed.
The health condition detector monitors the critical system state of the AUV in real time, and detects any deviation from normal behaviors by comparing the current behaviors of the AUV with the standard behavior patterns, so that possible faults or anomalies, such as a power system, a navigation sensor, an underwater positioning system, communication equipment and the like, are prompted, and necessary data support is provided for the fault analysis engine.
The simulation object of the AUV individual fault diagnosis simulation system is the AUV individual, and the AUV simulation system provides simulation objects and data sources for other 3 subsystems in the system through simulation of the AUV platform architecture, and simultaneously provides necessary support for cluster countermeasure simulation.
As shown in fig. 2, the invention further provides an AUV cluster countermeasure simulation method considering individual faults, which specifically includes the following steps:
S1, performing fault detection on the AUV by using a sensor, starting to calculate a matching combination when the fault is detected, and matching relatively nearest evasions for each chaser in the AUV cluster, wherein the chaser in the matching combination adopts an interception strategy based on an escape space.
S2, updating the cluster position after each constant time step is continued in the AUV cluster pursuit cluster countermeasure processSum and quantitySo that the matching is resumed and the escape of the escapers is prevented as much as possible in the form of a rolling optimization.
S3, for all evades in each constant time stepStatistics of captured and escape conditions of (a), wherein。
S4, if the user escapesCaptured or escaped, the escapement is then assembled from the escapement setRemoved from the collection and added to the corresponding captured collectionAnd escape set。
S5, checking an escape setWhether or not the set is empty, if not, indicating that there is still an escape person in the guard area for being captured or escapedAnd (3) if the internal activity is performed, recalculating the matching combination by utilizing the steps S1-S4, and continuing to fight, otherwise ending the fight.
Specifically, the fault detection of the AUV by using the sensor in step S1 specifically includes:
Fault detection is carried out on the submersible platform: the fault detection method specifically comprises the step of detecting faults of the shell, the tail wing and the control surface.
A shell: the integrity of the housing is routinely checked and pressure sensors and stress sensors and the like are used to monitor whether the housing is leaking or deforming.
Fin and rudder face: the position and the movement condition of the control surface are monitored through an angular displacement sensor, a moment sensor and the like so as to detect the abnormality of the control system.
Fault detection is carried out on the power system: the method specifically comprises fault detection of the propeller, the motor, the electronic speed regulator and the battery.
Propeller and motor: monitoring the operating current and temperature of the propeller and motor, setting relevant threshold anomaly data according to a particular profile may indicate a potential problem.
An electronic speed regulator: and detecting an electronic signal of the speed regulator to ensure that the rotating speed of the propeller is controlled in a normal range.
A battery: and the battery management system monitors the voltage, current, temperature and charge and discharge states of the battery, and prevents battery faults.
The fault detection of the navigation control system comprises a combined navigation system, an intelligent control system and an underwater positioning system.
An integrated navigation system: using multi-sensor data fusion techniques (e.g., kalman filters), the filter residuals are checked to find anomalies in the navigation sensor readings and to ensure that the data obtained from the inertial measurement unit, pressure sensor, doppler velocimeter, and other navigation sensors are consistent in time. With reference to landmark calibration, these fixed points are used to calibrate the integrated navigation system when the AUV approaches a pre-determined landmark, correcting drift errors.
An intelligent control system: the self-diagnosis is performed periodically to check the integrity and response performance of internal algorithms, such as control laws and decision logic. The monitoring actuator responds to whether the control command is met to detect a failure of the execution system. If an advanced control algorithm is used, the performance index of the advanced control algorithm should be monitored to ensure that the algorithm adjusts the control strategy in time to respond to environmental changes.
And (3) an underwater positioning system: the quality of acoustic signals and the quality of reception transmitted by underwater positioning systems (e.g., USBL, LBL, etc.) are monitored to detect problems in signal transmission. The positioning accuracy is checked by comparison with calibration points of known locations or cross-validation with positioning data of other AUVs. The accuracy of an underwater positioning system is highly dependent on clock synchronization and therefore it is necessary to check the time synchronization status of all relevant devices.
Performing fault detection for a data communication system, comprising: the system comprises a data acquisition unit, a data transmission unit, a data storage unit and a communication interface unit.
A data acquisition unit: and confirming that all sensor data are accurately acquired, wherein the sampling frequency and the data integrity meet preset standards.
A data transmission unit: by testing the sending and receiving of the data packet, whether the packet is lost, delayed or data transmission errors are detected.
A data storage unit: and data writing and reading tests are carried out regularly, so that the reliability of data storage is ensured.
A communication interface unit: and checking the physical connection and the protocol stack of the communication interface to ensure the normal communication link.
Specifically, the step S1 specifically includes the steps of:
S1.1, setting the AUV cluster to track and fight against the two routes Individual chasers and the methodThe escape person is composed of the following players in a set ofThe set of evades is。
Wherein,AndRespectively the chasersAnd escapersAt the time ofIs a position of (2); at the position ofThe dynamics of the AUV are described by the following decoupling system:
。
Wherein, AndIs the chasing personAnd escapersIs used for the initial position of the (c),AndRespectively represent the chasersAnd escapersThe ratio of the speeds of the chaser and the escapement isChasing personAnd escapersAt the time ofIs their respective instantaneous headingAnd。
AUV chaserAttack capture range of (2)In the initial state, the chaser team and the escapement team are distributed in the guard areaIn the guard areaThe outside area is the target area; The goal of the chasing team is in the guard areaAs many escapers as possible are captured, and the objective of the team of escapers is to get rid of the chasers from entering the target area。
S1.2 using potential functionsTo define escape space specificallyThe expression is:
。
Wherein the potential function With respect toFor gradients of (2)The expression is:
。
S1.3, escape space set is defined as ; When (when)Near toIn the time-course of which the first and second contact surfaces,Will become smaller rapidly, simulating the intuitive situation that the evasion person would like to avoid approaching the chaser whenFar enough away fromIn this case, the potential function value can be made relatively large, so that the evasion person is relatively safe. Chasing personThe interception strategy of (1) is to face to escape spaceDistance from the target areaThe nearest pointAnd (5) movement.
It should be understood that the above description is not intended to limit the invention to the particular embodiments disclosed, but to limit the invention to the particular embodiments disclosed, and that the invention is not limited to the particular embodiments disclosed, but is intended to cover modifications, adaptations, additions and alternatives falling within the spirit and scope of the invention.
Claims (2)
1. An AUV cluster countermeasure simulation method considering individual faults is characterized by comprising the following steps:
S1, performing fault detection on an AUV by using a sensor, starting to calculate a matching combination when faults are detected, and matching relatively nearest evasions for each chaser in the AUV cluster, wherein the chasers in the matching combination adopt an interception strategy based on an escape space;
s2, updating the cluster position after each constant time step is continued in the AUV cluster pursuit cluster countermeasure process Sum quantity/>Thereby re-matching;
S3, for all evades in each constant time step Statistics of captured and escape cases of (1), wherein/>；
S4, if the user escapesCaptured or escaped, the escapement is then collected/>, from the escapement setRemove from the collection and add the corresponding captured collection/>And escape set/>；
S5, checking an escape setWhether or not the set is empty, if not, it is stated that there is still an escape in the guard area/>, for the captured or escaped escapementThe internal activity is that the matching combination is recalculated by using the steps S1 to S4, the countermeasure is continued, or else the countermeasure is ended;
the step S1 specifically comprises the following steps:
S1.1, setting the AUV cluster to track and fight against the two routes Individual chasers/>The escape person is composed of the following players in a set ofThe evasion set is/>；
Wherein,And/>Respectively, chaser/>And escapement/>At time/>Is a position of (2); at/>The dynamics of the AUV are described by the following decoupling system:
；
Wherein, And/>Is the chaser/>And escapement/>Initial position of/>And/>Respectively represent the chaser/>And escapement/>The ratio of the speeds of the chaser and the escapement is/>Chasing person/>And escapement/>At time/>Is their respective instantaneous heading/>And/>；
AUV chaserAttack capture range of/>In the initial state, the chasing team and the escaper team are distributed in the guard area/>In guard area/>The outer region is the target region/>; The goal of the chasing team is to be in the guard area/>As many escapers as possible are captured, and the objective of the team of escapers is to get rid of the chasers from entering the target area；
S1.2 using potential functionsTo specifically define escape space/>The expression is:
；
Wherein the potential function Concerning/>Gradient of/>The expression is:
；
S1.3, escape space set is defined as ; Chasing person/>The interception strategy of (1) is directed to escape space/>Distance to target area/>Nearest point/>And (5) movement.
2. An AUV cluster challenge simulation system that accounts for individual faults, utilizing the method of claim 1, comprising: the system comprises a user interaction layer, a decision support layer, a simulation core layer, a data model layer and a support service layer;
The user interaction layer is the topmost layer of the system, initial configuration input is carried out on the whole AUV cluster countermeasure simulation process, and data of the decision support layer, the simulation core layer, the data model layer and the support service layer are input to the user interaction layer for display;
The decision support layer is used for carrying out fault detection and task planning on the AUV cluster;
The simulation core layer is used for simulating the ocean environment and dynamic changes and simulating the running state of the AUV cluster;
The data model layer is used for collecting sensor data and providing data for the simulation core layer;
The support service layer is used for recording the abnormal state and maintaining and upgrading the system.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101557092B1 (en) * | 2015-05-12 | 2015-11-19 | 대한민국(방위사업청장) | UAV simulation system for wargame |
| CN105955028A (en) * | 2016-06-02 | 2016-09-21 | 西北工业大学 | On-orbit guidance avoidance control integrated algorithm for spacecraft |
| CN112295229A (en) * | 2020-10-28 | 2021-02-02 | 中国电子科技集团公司第二十八研究所 | Intelligent game confrontation platform |
| CN113625595A (en) * | 2021-08-02 | 2021-11-09 | 中国人民解放军军事科学院国防科技创新研究院 | Unmanned aerial vehicle deduction and fault diagnosis method and system |
| CN114692397A (en) * | 2022-03-16 | 2022-07-01 | 中山大学 | Cluster distributed capture method based on multi-mechanism combination strategy |
| CN115237000A (en) * | 2022-06-23 | 2022-10-25 | 中国航空工业集团公司沈阳飞机设计研究所 | Unmanned aerial vehicle formation cooperative countermeasure simulation test platform and test method |
| CN115993835A (en) * | 2022-12-27 | 2023-04-21 | 西北工业大学 | Target maneuver intention prediction-based short-distance air combat maneuver decision method and system |
| WO2023093397A1 (en) * | 2021-11-24 | 2023-06-01 | 中国运载火箭技术研究院 | Efficiency evaluation method based on mass adversarial simulation deduction data modeling and analysis |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10207404B2 (en) * | 2017-02-09 | 2019-02-19 | X Development Llc | Generating a robot control policy from demonstrations collected via kinesthetic teaching of a robot |
-
2024
- 2024-02-04 CN CN202410155233.2A patent/CN117687322B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101557092B1 (en) * | 2015-05-12 | 2015-11-19 | 대한민국(방위사업청장) | UAV simulation system for wargame |
| CN105955028A (en) * | 2016-06-02 | 2016-09-21 | 西北工业大学 | On-orbit guidance avoidance control integrated algorithm for spacecraft |
| CN112295229A (en) * | 2020-10-28 | 2021-02-02 | 中国电子科技集团公司第二十八研究所 | Intelligent game confrontation platform |
| CN113625595A (en) * | 2021-08-02 | 2021-11-09 | 中国人民解放军军事科学院国防科技创新研究院 | Unmanned aerial vehicle deduction and fault diagnosis method and system |
| WO2023093397A1 (en) * | 2021-11-24 | 2023-06-01 | 中国运载火箭技术研究院 | Efficiency evaluation method based on mass adversarial simulation deduction data modeling and analysis |
| CN114692397A (en) * | 2022-03-16 | 2022-07-01 | 中山大学 | Cluster distributed capture method based on multi-mechanism combination strategy |
| CN115237000A (en) * | 2022-06-23 | 2022-10-25 | 中国航空工业集团公司沈阳飞机设计研究所 | Unmanned aerial vehicle formation cooperative countermeasure simulation test platform and test method |
| CN115993835A (en) * | 2022-12-27 | 2023-04-21 | 西北工业大学 | Target maneuver intention prediction-based short-distance air combat maneuver decision method and system |
Non-Patent Citations (4)
| Title |
|---|
| Design and Verification of Simulation Data Generator for Rail Transit Switch Machine;Wei, S等;《Journal of Physics: Conference Series》;20231026;全文 * |
| Research on security technology framework of UAV cluster system;Kunlun Wei等;《2021 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)》;20221231;全文 * |
| 战机空战决策方法及分析;傅莉;李伟;;沈阳航空航天大学学报;20131231(06);全文 * |
| 空中作战实验仿真平台设计与实现;刘东洋;孙鹏;张杰勇;;电子科技;20180930(09);全文 * |
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