Control method and device for unmanned catamaran formation and electronic equipment

Abstract

The invention relates to an unmanned catamaran formation control method and device and electronic equipment, and belongs to the technical field of unmanned ship formation cooperative control, and the method comprises the steps: constructing a communication topology model of a target unmanned catamaran cluster, and determining the communication disturbance of each unmanned catamaran; when determining that the navigator in the cluster has a fault, screening out a new navigator in the cluster based on a preset candidate scoring function, and determining a formation trajectory; adding the environment disturbance and the communication disturbance into bounded external disturbance in the dynamic model to obtain a target dynamic model; constructing and evaluating bounded external disturbance based on a nonlinear disturbance observer to obtain a disturbance estimation value; and determining a formation control instruction based on the formation trajectory and the disturbance estimation value, the formation control instruction being a control input of the target dynamic model, and performing formation control on the cluster based on an output of the target dynamic model. According to the invention, the robustness of unmanned catamaran formation control is improved.

Description

Technical Field

[0001] This invention relates to the field of unmanned vessel formation cooperative control technology, and in particular to a control method, device and electronic equipment for unmanned catamaran formations. Background Technology

[0002] With the rapid development of unmanned catamaran swarm technology, its potential in fields such as marine exploration, environmental monitoring, and military applications is increasingly evident. As a core technology for achieving collaborative operations, unmanned catamaran swarm formation control relies on efficient information exchange and coordinated decision-making among intelligent agents. In complex marine environments, communication links are susceptible to factors such as distance limitations, electromagnetic interference, and sea surface obstruction, leading to limited communication bandwidth, latency fluctuations, and even sudden outages. This poses a severe challenge to the stability and reliability of the formation control system.

[0003] To address the unique control challenges of unmanned surface platforms under the coupling effect of environmental disturbances (such as wave undulation and water drift) and communication constraints, existing methods lack a joint compensation mechanism for state estimation errors, communication packet loss, and external interference. Their fault recovery strategies are also mostly limited to simple reconnection or static switching, failing to achieve adaptive adjustment of formation structure and robust generation of control commands under dynamically changing communication resources.

[0004] In summary, there is a lack of methods in the existing technology to improve the robustness of unmanned catamaran formation control. Summary of the Invention

[0005] In view of this, it is necessary to provide a control method, device and electronic equipment for unmanned catamaran formations in order to improve the robustness of unmanned catamaran formation control.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a control method for an unmanned catamaran formation, comprising: A communication topology model of the target unmanned catamaran cluster is constructed. Based on the communication topology model, the communication disturbance of each unmanned catamaran is determined. The communication topology model uses an undirected graph to describe the information interaction between the agents in the target unmanned catamaran cluster. Construct a dynamic model for each unmanned catamaran in the target unmanned catamaran cluster; When it is determined that the navigator in the target unmanned catamaran cluster has failed, a new navigator is selected in the target unmanned catamaran cluster based on a preset candidate scoring function. The formation trajectory is determined based on the shortest path from the target unmanned catamaran cluster to the target point corresponding to the new navigator and the preset formation. By incorporating environmental disturbances and communication disturbances into the bounded external disturbances of the dynamic model, the target dynamic model is obtained. A bounded external disturbance is evaluated based on a nonlinear disturbance observer to obtain a disturbance estimate. The formation control command is determined based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model. The formation control is performed on the target unmanned catamaran cluster based on the output of the target dynamics model.

[0007] In one possible implementation, the expression for the dynamic model is:

[0008] In the formula, Indicates the first i Estimates of the condition of an unmanned catamaran. It is a nonlinear function. To control the input gain matrix, For the control input to be designed, For bounded external disturbances. Indicates the first i The status of an unmanned catamaran. In one possible implementation, determining that the navigator in the target unmanned catamaran swarm has failed includes: Acquire the heartbeat signal of the navigator heard by the followers in the target unmanned catamaran cluster, as well as the status data broadcast by the navigator; When the heartbeat signal is greater than the preset heartbeat threshold, or the number of consecutive preset number of times the status data is received exceeds the preset broadcast threshold, it is determined that the navigator has malfunctioned.

[0009] In one possible implementation, the expression for the preset candidate scoring function is:

[0010] In the formula, This represents the candidate score value for the i-th ship. Indicates the first The remaining power of the ship, Indicates the first The weight corresponding to the remaining power of each ship. Indicates the first The formation adaptability of the ships Indicates the first The weights corresponding to the formation fitness of each ship. Indicates the first Average communication delay per ship Indicates the first The weight of the average communication delay of each ship. Indicates the first The computational load of the ship Indicates the first The weights of the calculated load for each ship, where, .

[0011] In one possible implementation, the preset formation includes: One or more of the following formations: straight line formation, circular formation, and fan formation.

[0012] In one possible implementation, the process of determining formation control commands based on formation trajectories and disturbance estimates, whereby the formation control commands are the control inputs to the target dynamics model, and performing formation control on the target unmanned catamaran cluster based on the outputs of the target dynamics model, includes: The formation error of each ship is determined based on the formation trajectory and the preset geometric configuration; The formation control command is determined based on the disturbance estimate and the formation error. The formation control command is used as the control input to the target dynamics model, and the formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamics model.

[0013] In one possible implementation, the expression for the formation control command is:

[0014] In the formula, This represents the control input to the target dynamics model. and These are represented as proportional gain coefficient and differential gain coefficient, respectively. For the first The ship's local state estimator estimates its own state. This represents an estimated value. Indicates from the first The ship arrived at the The link quality of the ship This represents the state estimate received by the controller from the neighboring nodes. Indicates the first The geometric configuration of the ship, Indicates the first The geometric configuration of the ship.

[0015] One possible implementation also includes: evaluating the formation performance of the target unmanned catamaran swarm based on a preset comprehensive performance index function; The expression for the preset comprehensive performance index function is:

[0016] In the formula, Indicates comprehensive performance indicators, Indicates the error in maintaining formation. Indicates the quality of the communication link. Indicates energy consumption. This indicates the weight of the formation preservation error. Weights that represent the quality of the communication link. The weights representing energy consumption are as follows: .

[0017] Secondly, the present invention also provides a control device for an unmanned catamaran formation, comprising: The communication topology model construction module is used to construct the communication topology model of the target unmanned catamaran cluster. Based on the communication topology model, the communication disturbance of each unmanned catamaran is determined. The communication topology model uses an undirected graph to describe the information interaction between the agents in the target unmanned catamaran cluster. The dynamics model building module is used to build the dynamics model of each unmanned catamaran in the target unmanned catamaran cluster; The formation trajectory module is used to select a new navigator in the target unmanned catamaran cluster based on a preset candidate scoring function when the navigator in the target unmanned catamaran cluster fails, and to determine the formation trajectory based on the shortest path from the target unmanned catamaran cluster to the target point corresponding to the new navigator and the preset formation. The target dynamics model determination module is used to add environmental disturbances and communication disturbances to the bounded external disturbances in the dynamics model to obtain the target dynamics model; The disturbance estimation module is used to construct and evaluate bounded external disturbances based on a nonlinear disturbance observer to obtain disturbance estimates. The formation control module is used to determine the formation control command based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model, and the formation control is performed on the target unmanned catamaran cluster based on the output of the target dynamics model.

[0018] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the control method for an unmanned catamaran formation as described in any of the above implementations.

[0019] The beneficial effects of this invention are as follows: This invention provides a control method for an unmanned catamaran (UCC) swarm. First, a communication topology model of the target UCC swarm is constructed. Based on this model, the communication disturbances of each UCC are determined. The communication topology model uses an undirected graph to describe the information interaction between agents in the target UCC swarm. A dynamic model of each UCC in the target UCC swarm is then constructed. When it is determined that the navigator in the target UCC swarm has failed, a new navigator is selected from the target UCC swarm based on a preset candidate scoring function. Finally, the shortest path from the new navigator to the target point is determined, along with a preset swarm control method. The formation trajectory is determined by the shape of the target, and adaptive formation adjustment of the cluster is achieved through this fault repair mechanism. Environmental and communication disturbances are added to the bounded external disturbances in the dynamic model to obtain the target dynamic model. Environmental and communication factors affecting the cluster formation are used as formation influencing factors for formation adjustment, enabling the cluster to better adaptively adjust its formation. A nonlinear disturbance observer is constructed and used to evaluate the bounded external disturbances to obtain disturbance estimates. Based on the formation trajectory and disturbance estimates, formation control commands are determined, which serve as the control inputs to the target dynamic model. Formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamic model. This invention uses environmental and communication disturbances as influencing factors affecting cluster formation, improving the robustness of formation control. Furthermore, the adaptive formation adjustment of the cluster through the fault repair mechanism further enhances the robustness of cluster formation control. Attached Figure Description

[0020] Figure 1 A flowchart illustrating an embodiment of the control method for an unmanned catamaran formation provided by the present invention; Figure 2 This is a flowchart illustrating the logical process of dynamic communication topology modeling and adaptive formation adjustment in this invention. Figure 3 This is a logical flowchart of the leader fault tolerance and formation reconstruction strategy in this invention; Figure 4 This is a schematic diagram of the framework of the distributed robust formation controller and multi-source disturbance joint compensation in this invention; Figure 5 This is a schematic diagram of the multi-level interaction relationship and data flow between the unmanned catamaran cluster and the shore-based / mother ship control center in this invention; Figure 6 A schematic flowchart of an embodiment of a control device for an unmanned catamaran formation provided by the present invention; Figure 7 A schematic diagram of an embodiment of the electronic device provided by the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0023] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0024] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0025] This invention provides a control method, device, and electronic equipment for unmanned catamaran formations, which will be described below.

[0026] Figure 1 A schematic flowchart of an embodiment of the control method for unmanned catamaran formations provided by the present invention is shown below. Figure 1 As shown, the control method for unmanned catamaran formations includes: S101. Construct a communication topology model of the target unmanned catamaran cluster, determine the communication disturbance of each unmanned catamaran based on the communication topology model, and use an undirected graph to describe the information interaction between each agent in the target unmanned catamaran cluster. Use undirected graphs to describe the information exchange relationships between ships and clarify who can communicate directly with whom.

[0027] S102. Construct a dynamic model of each unmanned catamaran in the target unmanned catamaran cluster; The position, velocity, and acceleration of each ship are described using a dynamic model.

[0028] S103. When it is determined that the navigator in the target unmanned catamaran cluster has failed, a new navigator is selected in the target unmanned catamaran cluster based on the preset candidate scoring function, and the formation trajectory is determined based on the shortest path of the target unmanned catamaran cluster corresponding to the new navigator to the target point and the preset formation. When the navigator encounters a problem, quickly select a new navigator and plan the shortest path and formation trajectory.

[0029] S104. Add environmental disturbances and communication disturbances to the bounded external disturbances in the dynamic model to obtain the target dynamic model; By incorporating environmental disturbances (such as wind and waves) and communication disturbances (such as signal delays) into the dynamic model, a more realistic target dynamic model can be formed.

[0030] S105. Construct and evaluate the bounded external disturbance based on the nonlinear disturbance observer to obtain the disturbance estimate; The values ​​of environmental and communication disturbances are estimated using a nonlinear disturbance observer.

[0031] S106. Determine the formation control command based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model. Perform formation control on the target unmanned catamaran cluster based on the output of the target dynamics model.

[0032] Based on trajectory and disturbance estimates, control commands are generated to drive the unmanned vessels to move in formation.

[0033] Compared with existing technologies, this embodiment provides a control method for an unmanned catamaran (UCAV) swarm. First, a communication topology model of the target UCAV swarm is constructed. Based on this model, the communication disturbances of each UCAV are determined. The communication topology model uses an undirected graph to describe the information interaction between agents in the target UCAV swarm. A dynamic model of each UCAV in the target UCAV swarm is then constructed. When it is determined that the navigator in the target UCAV swarm has failed, a new navigator is selected from the target UCAV swarm based on a preset candidate scoring function. The control method is then determined based on the shortest path from the new navigator to the target point and a preset swarm number. The formation trajectory is determined by the shape of the target, and adaptive formation adjustment of the cluster is achieved through this fault repair mechanism. Environmental and communication disturbances are added to the bounded external disturbances in the dynamic model to obtain the target dynamic model. Environmental and communication factors affecting the cluster formation are used as formation influencing factors for formation adjustment, enabling the cluster to better adaptively adjust its formation. A nonlinear disturbance observer is constructed and used to evaluate the bounded external disturbances to obtain disturbance estimates. Based on the formation trajectory and disturbance estimates, formation control commands are determined, which serve as the control inputs to the target dynamic model. Formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamic model. This invention uses environmental and communication disturbances as influencing factors affecting cluster formation, improving the robustness of formation control. Furthermore, the adaptive formation adjustment of the cluster through the fault repair mechanism further enhances the robustness of cluster formation control.

[0034] It is understood that the embodiments of the present invention are not limited to unmanned catamarans, but are applicable to any type of unmanned vessel.

[0035] In a specific embodiment of the present invention, the method is divided into functional modules such as a dynamic communication topology sensing module, a distributed robust control module, a leader fault tolerance and formation reconstruction module, a multi-source disturbance joint compensation module, and an adaptive formation adjustment module to complete the process steps of the method.

[0036] The dynamic communication topology sensing module is responsible for capturing the time-varying characteristics of communication links between agents within the unmanned catamaran swarm in real time, including key indicators such as link connectivity, bandwidth, latency, and packet loss rate. The distributed robust control module, based on the topology sensing results, designs a control algorithm with error compensation capabilities to ensure the stability of the formation under communication constraints. The leader fault tolerance and formation reconfiguration module constructs a resilient formation architecture to address single-point failure risks. The multi-source disturbance joint compensation module jointly suppresses the coupling effect of environmental disturbances and communication constraints. The adaptive formation adjustment module ultimately achieves dynamic formation optimization and continuous task execution for the swarm in complex scenarios. The global performance monitoring unit provides data support for offline analysis and parameter tuning.

[0037] In a specific embodiment of the present invention, the method steps are as follows: Step 1: Construct a dynamic communication topology model and a cluster dynamics model to complete system initialization. For example... Figure 2 As shown, the communication link status between agents in the unmanned catamaran swarm is monitored in real time, and the swarm's communication topology is dynamically updated based on the monitoring results. Assuming the swarm contains N unmanned catamarans, its communication topology can be represented as a time-varying directed graph. , where the node set Corresponding to unmanned catamarans, edge sets Indicates available communication links, adjacency matrix elements The value is determined by the communication delay. and packet loss rate The decision is made jointly, and its calculation logic is as follows: when Exceeding the preset maximum tolerance delay threshold or Exceeding the maximum tolerable packet loss rate threshold When the link is deemed unavailable, Set to 0; otherwise, It is assigned a positive value between 0 and 1, and the value follows The reduction and The reliability of the link is quantified by the reduction in [something unclear - possibly related to a specific parameter or parameter]. Each unmanned catamaran is equipped with a dedicated communication status monitoring module, which periodically sends heartbeat signals to its neighboring nodes and records the timestamps of received responses and the number of successfully received data packets, thereby calculating [something unclear - possibly related to a specific parameter or parameter] in real time. and .

[0038] Simultaneously, to clearly define the controlled object, a cluster dynamics model is established. In some embodiments of the present invention, the expression of the dynamics model is:

[0039] In the formula, Indicates the first i Estimates of the condition of an unmanned catamaran. It is a nonlinear function. To control the input gain matrix, For the control input to be designed, For bounded external disturbances. Indicates the first i The status of an unmanned catamaran.

[0040] In addition, the dynamic communication topology model supports predictive optimization. Based on historical link quality data and current sea state parameters (such as wind speed, wave height, and visibility), the system's built-in predictive model can predict link degradation trends in advance. For example, if it is predicted that a certain area will experience communication disruption due to a large surge within the next T seconds, the system will proactively trigger local topology reconfiguration, pre-establishing detour paths or prioritizing backup links, thereby avoiding the impact of communication interruptions on formation control.

[0041] This embodiment constructs a dynamic communication topology model to accurately capture the time-varying characteristics of communication links between unmanned catamaran swarms, enabling real-time perception and adaptive adjustment of link connectivity, bandwidth fluctuations, and latency changes. Combined with a distributed robust controller and a state estimation error compensation mechanism, it effectively suppresses adverse effects such as information interaction distortion and control command lag under communication constraints. This fundamentally overcomes the inherent defects of traditional formation control methods, such as poor stability and formation divergence in communication-constrained scenarios, significantly expanding the effective operating range of unmanned catamaran swarms in complex communication environments.

[0042] Step 2: Implement leader fault tolerance and formation reconfiguration strategies. Set leader fault detection thresholds and heartbeat signal timeout thresholds. Once a fault is triggered, the system automatically reselects a leader based on a candidate scoring function. The scoring comprehensively considers factors such as remaining battery power, formation fitness, average communication latency, and computational load. After the new leader is selected, the cluster generates a reconfiguration trajectory by solving a distributed optimization problem with safety spacing constraints, establishing a formation reference benchmark.

[0043] Specifically, the system sets a navigator fault detection threshold and a heartbeat signal timeout threshold. The navigator (whether physically present or virtual) needs to periodically broadcast its status and heartbeat signal. All follower nodes in the cluster continuously listen to this signal. Once the heartbeat signal timeout threshold is triggered, or the status data broadcast by the navigator exceeds the preset reasonable range multiple times consecutively (i.e., triggering the fault detection threshold), the navigator is determined to have malfunctioned. In some embodiments of the present invention, determining that the navigator in the target unmanned catamaran cluster has malfunctioned includes: Acquire the heartbeat signal of the navigator heard by the followers in the target unmanned catamaran cluster, as well as the status data broadcast by the navigator; When the heartbeat signal is greater than the preset heartbeat threshold, or the number of consecutive preset number of times the status data is received exceeds the preset broadcast threshold, it is determined that the navigator has malfunctioned.

[0044] At this point, the system immediately initiates the leader re-election process. Candidate scoring function. It is used to evaluate each potential candidate (usually a node with sufficient remaining power and good communication), and its calculation formula takes into account the remaining power. Formation adaptability (Measures how close the node's current position is to the ideal navigation position), average communication latency and computational load Factors such as ,in , , , The preset weights are used. The node with the highest score is automatically selected as the new leader. In some embodiments of the present invention, the expression of the preset candidate scoring function is:

[0045] In the formula, Indicates the first The candidate rating values ​​for each ship. Indicates the first The remaining power of the ship, Indicates the first The weight corresponding to the remaining power of each ship. Indicates the first The formation adaptability of the ships Indicates the first The weights corresponding to the formation fitness of each ship. Indicates the first Average communication delay per ship Indicates the first The weight of the average communication delay of each ship. Indicates the first The computational load of the ship Indicates the first The weights of the calculated load for each ship, where .

[0046] Once a new leader is selected, the cluster needs to quickly generate a new formation trajectory to maintain the mission. This process is achieved by solving a distributed optimization problem with safety spacing constraints. The goal is to minimize the total energy consumption or total time for all nodes to reach the new formation position, while ensuring that the distance between any two ships is always greater than a preset safety distance. This is to avoid collisions. See [link to full logic flow of this strategy] for details. Figure 3 The diagram illustrates the logical flow framework of the leader fault tolerance and formation reconfiguration strategy. Preferably, in step 2, the virtual leader state is generated by the shore-based or mothership control center, with its initial position taken as the cluster centroid, and the remaining nodes synchronize their reference trajectories through a consensus protocol. This mode reduces dependence on a single physical platform and enhances the system's flexibility and survivability.

[0047] The leader fault tolerance and formation reconfiguration strategy introduced in this embodiment transforms formation control from a centralized architecture relying on a single strong leader to a resilient architecture with dynamic switching of multiple leaders and distributed autonomous decision-making. When some leaders fail, the system can autonomously identify the faulty nodes and trigger the formation reconfiguration mechanism. Through adaptive switching of node roles and task reallocation, the risk of formation disintegration caused by single-point failures is significantly reduced. This enables the system to have autonomous survival and continuous operation capabilities in scenarios with dynamically changing leaders, demonstrating excellent robustness and reliability when facing complex ocean missions.

[0048] Step 3: Integrate the multi-source disturbance joint compensation module. Environmental disturbances such as wind, waves, and ocean currents, along with communication uncertainties, are modeled as a unified lumped disturbance and estimated online using a nonlinear disturbance observer. The compensation control law uses the disturbance estimate to correct subsequent control inputs, enabling rapid convergence of observation errors and providing the controller with clean environmental parameters.

[0049] Specifically, environmental disturbances such as wind, waves, and ocean currents, along with the communication uncertainties monitored in step 1 (such as control command distortion caused by packet loss and delay), are modeled as a unified disturbance acting on the system dynamics equations. To counteract the effects of this disturbance, the system employs a nonlinear disturbance observer for online estimation. The structure of this observer is typically as follows: Where L is the observer gain matrix, To The estimated value. Preferably, in step 3, the disturbance observer can switch to a higher-order sliding mode form under strong disturbance scenarios. When the system detects that the disturbance intensity exceeds a certain threshold, it will automatically activate the higher-order sliding mode disturbance observer. This observer has stronger robustness and faster convergence speed, and can more accurately estimate high-frequency, large-amplitude composite disturbances, ensuring the stability of formation control under extreme sea conditions.

[0050] This embodiment innovatively integrates environmental disturbance modeling with communication constraint coupling analysis. Addressing the coupling effects of wind, wave, and current disturbances in the marine environment with limited communication bandwidth and link interruptions, a multi-dimensional disturbance observation and compensation algorithm is designed. This module can identify and compensate for composite disturbances under both environmental and communication constraints in real time, effectively solving the problem of insufficient control accuracy caused by separately handling environmental disturbances and communication constraints in existing technologies. This provides strong support for the stable formation of unmanned catamaran swarms in harsh marine environments.

[0051] Step 4: Design a distributed robust formation controller. Based on the dynamic model from Step 1, the reference trajectory from Step 2, and the disturbance estimation from Step 3, a controller is designed. The controller generates control commands based on the neighbor state estimates and the desired relative positions, and defines a formation error to measure the formation maintenance effect. By constructing a suitable Lyapunov function, it can be proven that the formation error is eventually bounded under appropriate gain selection.

[0052] Specifically, based on the dynamic model constructed in step 1, the leader reference determined in step 2, and the disturbance estimation provided in step 3, the controller is designed to enable all unmanned catamarans to track a common reference trajectory. While maintaining the preset relative geometric configuration Therefore, the formation error of the i-th ship is defined as... The controller bases its decisions on the state estimates received from neighboring nodes. (in , (the set of neighbors of i) and the expected relative position Generate control commands. In some embodiments of the present invention, in conjunction with the disturbance compensation in step 3, the determination of formation control commands based on the formation trajectory and disturbance estimates, wherein the formation control commands are the control input to the target dynamics model, and formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamics model, including: The formation error of each ship is determined based on the formation trajectory and the preset geometric configuration; The formation control command is determined based on the disturbance estimate and the formation error. The formation control command is used as the control input to the target dynamics model, and the formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamics model.

[0053] In some embodiments of the present invention, the expression of the formation control command is:

[0054] In the formula, This represents the control input to the target dynamics model. and These are represented as proportional gain coefficient and differential gain coefficient, respectively. For the first The ship's local state estimator estimates its own state. This represents an estimated value. Indicates from the first The ship arrived at the The link quality of the ship This represents the state estimate received by the controller from the neighboring nodes. Indicates the first The geometric configuration of the ship, Indicates the first The geometric configuration of the ship.

[0055] By constructing a suitable Lyapunov function (P is a positive definite matrix), and using Lyapunov stability theory, it can be proven that with appropriate selection of gain... and In the case of formation error Ultimately bounded, and its upper bound is the same as that of external disturbances. and communication delay It is proportional to the upper bound. For the core principle of this controller and its synergistic effect with the disturbance compensation module, please refer to [link to relevant documentation]. Figure 2 The diagram shows the core principle framework.

[0056] Preferably, in step 4, the controller integrates an event triggering mechanism. The local triggering condition is based on the state estimation error. With current state amplitude The system is configured to only trigger an update of control commands and broadcast the latest status to neighbors when the combined error exceeds a dynamic threshold, thereby effectively reducing unnecessary communication overhead and extending system battery life.

[0057] In some embodiments of the present invention, the preset formation includes: One or more of the following formations: straight line formation, circular formation, and fan formation.

[0058] In some embodiments of the present invention, the method further includes: evaluating the formation performance of the target unmanned catamaran cluster based on a preset comprehensive performance index function; The expression for the preset comprehensive performance index function is:

[0059] In the formula, Indicates comprehensive performance indicators, Indicates the error in maintaining formation. Indicates the quality of the communication link. Indicates energy consumption. This indicates the weight of the formation preservation error. Weights that represent the quality of the communication link. The weights representing energy consumption are as follows: .

[0060] Finally, adaptive formation adjustment and control command generation are executed. Specifically, the system defines a comprehensive performance index. This metric includes formation maintenance error. Communication link quality and energy consumption Three sub-indicators, namely Weights of each item , , It is not fixed, but dynamically adjusted according to the current operating status of the system. For example, when an increase in the average packet loss rate or the average latency is detected, the system will automatically increase... The weight is determined to prioritize communication efficiency; when an increase in the intensity of external disturbances is detected, the weight is increased. The weights are assigned to prioritize formation accuracy. This is based on a dynamically adjusted comprehensive performance index. The system's control update frequency also changes adaptively accordingly. When When performance is good, reduce the control update frequency to save communication and computing resources; when... When the situation worsens, the update frequency is increased to strengthen control. This adaptive logic is also reflected in... Figure 3 Within the process framework, preferably, the formation reference trajectory is generated online by the mission planning layer. The baseline formation and movement mode are automatically adjusted according to different mission modes (such as straight-line cruising, circular search, and sector coverage) to ensure formation closure and mission adaptability. Furthermore, the system includes a global performance monitoring unit, which continuously records key data such as formation error, link status, control variables, disturbance estimates, and leader switching events, storing them locally or uploading them to a shore-based data center for offline analysis and iterative optimization of controller parameters.

[0061] The adaptive formation adjustment mechanism in this embodiment dynamically optimizes the formation topology and control parameters by collecting multi-source data such as cluster status, communication links, and environmental disturbances in real time. In complex and ever-changing marine environments, it can autonomously adjust formation density, geometric configuration, and node roles, achieving highly robust control, stable formation maintenance, and continuous mission execution capabilities for unmanned catamaran swarm formations. Compared with existing technologies, it significantly improves the swarm's adaptability and mission completion rate in dynamic environments.

[0062] To better implement the control method for an unmanned catamaran formation in this embodiment of the invention, based on the control method for an unmanned catamaran formation, correspondingly, as follows: Figure 6 As shown, this embodiment of the invention also provides a control device for an unmanned catamaran formation. The control device 600 for an unmanned catamaran formation includes: The communication topology model construction module 601 is used to construct the communication topology model of the target unmanned catamaran cluster. Based on the communication topology model, the communication disturbance of each unmanned catamaran is determined. The communication topology model uses an undirected graph to describe the information interaction between the various agents in the target unmanned catamaran cluster. The dynamic model construction module 602 is used to construct the dynamic model of each unmanned catamaran in the target unmanned catamaran cluster; The formation trajectory module 603 is used to select a new navigator in the target unmanned catamaran cluster based on a preset candidate scoring function when the navigator in the target unmanned catamaran cluster is found to have failed, and to determine the formation trajectory based on the shortest path from the target unmanned catamaran cluster corresponding to the new navigator to the target point and the preset formation. The target dynamics model determination module 604 is used to add environmental disturbances and communication disturbances to the bounded external disturbances in the dynamics model to obtain the target dynamics model; The disturbance estimate determination module 605 is used to construct and evaluate the bounded external disturbance based on the nonlinear disturbance observer to obtain the disturbance estimate. The formation control module 606 is used to determine the formation control command based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model. Based on the output of the target dynamics model, the module performs formation control on the target unmanned catamaran cluster.

[0063] The control device 600 for an unmanned catamaran formation provided in the above embodiments can realize the technical solution described in the above embodiments of the control method for an unmanned catamaran formation. The specific implementation principle of each module or unit can be found in the corresponding content in the above embodiments of the control method for an unmanned catamaran formation, which will not be repeated here.

[0064] like Figure 7 As shown, the present invention also provides an electronic device 700. The electronic device 700 includes a processor 701, a memory 702, and a display 703. Figure 7 Only some components of the electronic device 700 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0065] In some embodiments, processor 701 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 702 or process data, such as a control method for an unmanned catamaran formation in this invention.

[0066] In some embodiments, processor 701 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 701 may be local or remote. In some embodiments, processor 701 may be implemented on a cloud platform. In some embodiments, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, or any combination thereof.

[0067] In some embodiments, memory 702 may be an internal storage unit of electronic device 700, such as a hard disk or memory of electronic device 700. In other embodiments, memory 702 may also be an external storage device of electronic device 700, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 700.

[0068] Furthermore, the memory 702 may include both internal storage units of the electronic device 700 and external storage devices. The memory 702 is used to store application software and various types of data installed on the electronic device 700.

[0069] In some embodiments, display 703 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 703 is used to display information from electronic device 700 and to display a visual user interface. Components 701-703 of electronic device 700 communicate with each other via a system bus.

[0070] In one embodiment, when processor 701 executes a control program for an unmanned catamaran formation stored in memory 702, the following steps can be implemented: A communication topology model of the target unmanned catamaran cluster is constructed. Based on the communication topology model, the communication disturbance of each unmanned catamaran is determined. The communication topology model uses an undirected graph to describe the information interaction between the agents in the target unmanned catamaran cluster. Construct a dynamic model for each unmanned catamaran in the target unmanned catamaran cluster; When it is determined that the navigator in the target unmanned catamaran cluster has failed, a new navigator is selected in the target unmanned catamaran cluster based on a preset candidate scoring function. The formation trajectory is determined based on the shortest path from the target unmanned catamaran cluster to the target point corresponding to the new navigator and the preset formation. By incorporating environmental disturbances and communication disturbances into the bounded external disturbances of the dynamic model, the target dynamic model is obtained. A bounded external disturbance is evaluated based on a nonlinear disturbance observer to obtain a disturbance estimate. The formation control command is determined based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model. The formation control is performed on the target unmanned catamaran cluster based on the output of the target dynamics model.

[0071] It should be understood that when the processor 701 executes the control program for an unmanned catamaran formation stored in the memory 702, in addition to the functions mentioned above, it can also perform other functions, as detailed in the description of the corresponding method embodiments above.

[0072] Furthermore, the embodiments of the present invention do not specifically limit the type of electronic device 700 mentioned. Electronic device 700 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic device. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, electronic device 700 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0073] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0074] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A control method for an unmanned catamaran formation, characterized in that, include: A communication topology model of the target unmanned catamaran cluster is constructed. Based on the communication topology model, the communication disturbance of each unmanned catamaran is determined. The communication topology model uses an undirected graph to describe the information interaction between the agents in the target unmanned catamaran cluster. Construct a dynamic model for each unmanned catamaran in the target unmanned catamaran cluster; When it is determined that the navigator in the target unmanned catamaran cluster has failed, a new navigator is selected in the target unmanned catamaran cluster based on a preset candidate scoring function. The formation trajectory is determined based on the shortest path from the target unmanned catamaran cluster to the target point corresponding to the new navigator and the preset formation. By incorporating environmental disturbances and communication disturbances into the bounded external disturbances of the dynamic model, the target dynamic model is obtained. A bounded external disturbance is evaluated based on a nonlinear disturbance observer to obtain a disturbance estimate. The formation control command is determined based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model. The formation control is performed on the target unmanned catamaran cluster based on the output of the target dynamics model.

2. The control method for unmanned catamaran formations according to claim 1, characterized in that, The expression for the dynamic model is: In the formula, Indicates the first i Estimates of the condition of an unmanned catamaran. It is a nonlinear function. To control the input gain matrix, For the control input to be designed, For bounded external disturbances. Indicates the first i The status of an unmanned catamaran.

3. The control method for unmanned catamaran formations according to claim 1, characterized in that, The navigator in the target unmanned catamaran swarm has been identified as malfunctioning, including: Acquire the heartbeat signal of the navigator heard by the followers in the target unmanned catamaran cluster, as well as the status data broadcast by the navigator; When the heartbeat signal is greater than the preset heartbeat threshold, or the number of consecutive preset number of times the status data is received exceeds the preset broadcast threshold, it is determined that the navigator has malfunctioned.

4. The control method for unmanned catamaran formations according to claim 1, characterized in that, The expression for the preset candidate scoring function is: In the formula, Indicates the first The candidate rating values ​​for each ship. Indicates the first The remaining power of the ship, Indicates the first The weight corresponding to the remaining power of each ship. Indicates the first The formation adaptability of the ships Indicates the first The weights corresponding to the formation fitness of each ship. Indicates the first Average communication delay per ship Indicates the first The weight of the average communication delay of each ship. Indicates the first The computational load of the ship Indicates the first The weights of the calculated load for each ship, where .

5. The control method for unmanned catamaran formations according to claim 1, characterized in that, The preset formation includes: One or more of the following formations: straight line formation, circular formation, and fan formation.

6. The control method for unmanned catamaran formations according to claim 1, characterized in that, The formation control command is determined based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model. The formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamics model, including: The formation error of each ship is determined based on the formation trajectory and the preset geometric configuration; The formation control command is determined based on the disturbance estimate and the formation error. The formation control command is used as the control input to the target dynamics model, and the formation control of the target unmanned catamaran cluster is performed based on the output of the target dynamics model.

7. The control method for unmanned catamaran formations according to claim 6, characterized in that, The expression for the formation control command is: In the formula, This represents the control input to the target dynamics model. and These are represented as proportional gain coefficient and differential gain coefficient, respectively. For the first The ship's local state estimator estimates its own state. This represents an estimated value. Indicates from the first The ship arrived at the The link quality of the ship This represents the state estimate received by the controller from the neighboring nodes. Indicates the first The geometric configuration of the ship, Indicates the first The geometric configuration of the ship.

8. The control method for unmanned catamaran formations according to claim 1, characterized in that, Also includes: The formation performance of the target unmanned catamaran swarm is evaluated based on a preset comprehensive performance index function. The expression for the preset comprehensive performance index function is: In the formula, Indicates comprehensive performance indicators, Indicates the error in maintaining formation. Indicates the quality of the communication link. Indicates energy consumption. This indicates the weight of the formation preservation error. Weights that represent the quality of the communication link. The weights representing energy consumption are as follows: .

9. A control device for an unmanned catamaran formation, characterized in that, include: The communication topology model construction module is used to construct the communication topology model of the target unmanned catamaran cluster. Based on the communication topology model, the communication disturbance of each unmanned catamaran is determined. The communication topology model uses an undirected graph to describe the information interaction between the agents in the target unmanned catamaran cluster. The dynamics model building module is used to build the dynamics model of each unmanned catamaran in the target unmanned catamaran cluster; The formation trajectory module is used to select a new navigator in the target unmanned catamaran cluster based on a preset candidate scoring function when the navigator in the target unmanned catamaran cluster fails, and to determine the formation trajectory based on the shortest path from the target unmanned catamaran cluster to the target point corresponding to the new navigator and the preset formation. The target dynamics model determination module is used to add environmental disturbances and communication disturbances to the bounded external disturbances in the dynamics model to obtain the target dynamics model; The disturbance estimation module is used to construct and evaluate bounded external disturbances based on a nonlinear disturbance observer to obtain disturbance estimates. The formation control module is used to determine the formation control command based on the formation trajectory and disturbance estimate. The formation control command is the control input of the target dynamics model, and the formation control is performed on the target unmanned catamaran cluster based on the output of the target dynamics model.

10. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the control method for an unmanned catamaran formation according to any one of claims 1 to 8.

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