A time-varying interference underwater unmanned cluster task formation control method based on orientation constraint

Abstract

The application discloses a time-varying interference underwater unmanned cluster task formation control method based on orientation constraint, relates to the underwater unmanned cluster formation control technical field, and aims at the problem that it is difficult to keep the neighbor orientation constraint and pass through the narrow obstacle space under the time-varying external interference and the change of formation movement speed, and proposes the following scheme: obtaining the state, communication relationship and target orientation constraint of each underwater unmanned vehicle, determining the neighbor constraint information, determining the leader target state according to the task environment and generating the leader control input, generating the interference suppression amount according to the neighbor state deviation information and whether the upper limit of the interference is known or not, and then generating the follower control input and updating the formation state. The application is suitable for underwater unmanned cluster task formation control.

Description

Technical Field

[0001] This relates to the field of underwater unmanned swarm formation control under interference conditions. More specifically, it relates to the design of an unmanned swarm formation controller that includes an interference suppression module, and the achievement of formation crossing control in narrow underwater obstacle spaces while keeping constraints between neighboring UAVs unchanged. Background Technology

[0002] With the increasing demand for collaborative operations in underwater unmanned vehicle (UAV) swarms, formation control technology for tasks such as underwater inspection, search, monitoring, and obstacle passage has been extensively studied. During mission execution by an underwater UAV swarm, multiple UAVs typically need to move according to a pre-defined formation configuration, maintaining spatial relationships through information exchange between neighboring UAVs. Existing formation control methods usually establish constraints based on relative displacement, distance, or orientation between UAVs, and combine this with the leader-follower structure, communication topology, and the position and velocity status information of each UAV to calculate the control inputs for the follower UAVs, thereby forming and maintaining the predetermined formation.

[0003] Among the methods described above, formation control based on relative displacement typically achieves formation translation by constraining the relative positional relationships between neighboring underwater unmanned vehicles (UAVs); formation control based on relative distance typically achieves formation maintenance and a certain degree of attitude adjustment by constraining the distance between neighboring UAVs; and formation control based on relative orientation constrains the orientational relationships between neighboring UAVs, enabling the formation to translate, rotate, and scale while satisfying neighbor orientation constraints. For underwater passage through narrow obstacle spaces, the formation typically needs to adjust its overall scale according to the passage space when approaching an obstacle and restore its target configuration after passing through the obstacle. Therefore, formation control based on relative orientation constraints is more suitable for achieving formation scaling without changing the neighbor orientational relationships.

[0004] However, existing formation control methods based on relative orientation constraints still have certain limitations in practical underwater missions. Underwater unmanned vehicles (UAVs) are subject to external disturbances such as water resistance during movement. These disturbances often vary with time, navigation status, and spatial position, and the components of the disturbances in different directions may not be consistent. Some existing formation control methods typically simplify external disturbances to fixed constant disturbances or disturbances with known upper bounds, making it difficult to adapt to mission environments where external disturbances vary over time or whose upper bounds are not easily predetermined. This results in a lack of control compensation basis for time-varying disturbances when follower UAVs maintain neighbor orientation constraints.

[0005] Meanwhile, in existing formation control methods, the speed of the leader underwater drone is often set to a fixed value, or the dynamic changes in the leader's target position and speed with mission requirements are not fully considered during the control process. When traversing narrow underwater obstacle spaces, changes in the overall scale of the formation usually depend on adjustments to the leader's target position. If there is a lack of corresponding dynamic coordination between the leader's motion state and the obstacle passage requirements, it will be difficult to achieve formation shrinking, obstacle passage, and formation recovery while maintaining neighboring orientation constraints.

[0006] Furthermore, when both known and unknown upper limits of interference exist in the mission conditions, using the same fixed-formation formation controller makes it difficult to balance the targeted nature and practical applicability of control compensation. For cases where the upper limit of interference is known, interference suppression terms can be constructed based on this known upper limit; for cases where the upper limit is unknown, the interference suppression amount needs to be adaptively adjusted based on the azimuth error, relative displacement difference, and relative velocity difference between neighboring underwater unmanned vehicles. Existing methods fail to adequately integrate these different interference conditions for controller selection and control input updates, limiting their application in complex underwater mission formation scenarios.

[0007] In summary, existing technologies have shortcomings in maintaining the orientation constraints between neighboring underwater unmanned vehicles and achieving formation traversal control in narrow underwater obstacle spaces under time-varying external interference, unknown upper limits of interference, and time-varying formation motion requirements. Summary of the Invention

[0008] To address the shortcomings of existing technologies in maintaining positional constraints between neighboring underwater unmanned vehicles and achieving formation navigation control in narrow underwater obstacle spaces under time-varying external disturbances, unknown upper limits of disturbances, and time-varying formation motion requirements, the technical solution provided by this invention is as follows: A formation control method for time-varying disturbance underwater unmanned swarm missions based on orientation constraints, comprising: The steps include: acquiring the status information, communication relationships, and target orientation constraints of each underwater unmanned vehicle in an underwater unmanned swarm, and determining the neighbor constraint information of each follower underwater unmanned vehicle based on the communication relationships and target orientation constraints; The steps are as follows: determining the target state of the leader underwater unmanned vehicle based on mission environment information, generating leader control input based on the state information of the leader underwater unmanned vehicle and the target state, and updating the state information of the leader underwater unmanned vehicle. The step of generating neighbor state deviation information that characterizes the deviation between the actual neighbor relationship and the target orientation constraint based on the state information of the follower underwater unmanned vehicle, the state information of the corresponding neighbor underwater unmanned vehicle, and the neighbor constraint information. The step of performing interference suppression processing on the neighbor state deviation information based on whether the external time-varying interference information contains a known upper bound of interference to obtain the interference suppression amount; The steps are as follows: generating the control input of the follower underwater unmanned vehicle and updating the status information of the follower underwater unmanned vehicle based on the neighbor state deviation information, the interference suppression amount and the control input information of the neighbor underwater unmanned vehicle; The process involves calculating the actual position information between neighboring underwater unmanned vehicles (UUVs) based on the updated status information of each UUV, and then determining whether to continue updating the control input or output of the underwater UUV swarm task formation control results based on the comparison between the actual position information and the target position constraints.

[0009] Furthermore, in a preferred embodiment, the neighbor constraint information includes a set of neighboring underwater unmanned aerial vehicles (UAVs) of the follower UAV, and a target orientation constraint matrix between the follower UAV and its corresponding neighboring UAVs.

[0010] Furthermore, in a preferred embodiment, when determining the target state of the leader underwater unmanned vehicle based on the mission environment information, if the mission environment information indicates the presence of a narrow underwater obstacle space, the target position relationship between the leader underwater unmanned vehicles is adjusted, and the adjusted target position and target velocity are taken as the target state.

[0011] Furthermore, in a preferred embodiment, the neighbor state deviation information is generated based on the relative displacement difference vector, relative velocity difference vector, and target orientation constraint between the follower underwater unmanned vehicle and the corresponding neighbor underwater unmanned vehicle.

[0012] Furthermore, in a preferred embodiment, when performing interference suppression processing on the neighbor state deviation information, if the external time-varying interference information contains a known upper bound of interference, the interference suppression amount is generated based on the known upper bound of interference, the target orientation constraint, and the neighbor state deviation information.

[0013] Furthermore, in a preferred embodiment, when performing interference suppression processing on the neighbor state deviation information, if the external time-varying interference information does not contain a known upper bound for interference, the adaptive interference suppression amount is updated according to the change in the neighbor state deviation information after the target orientation constraint is applied, and the adaptive interference suppression amount is used as the interference suppression amount.

[0014] A time-varying interference underwater unmanned swarm formation control device based on orientation constraints, comprising: A module for acquiring the status information, communication relationships, and target orientation constraints of each underwater unmanned vehicle in an underwater unmanned swarm, and determining the neighbor constraint information of each follower underwater unmanned vehicle based on the communication relationships and target orientation constraints; The module determines the target state of the leader underwater unmanned vehicle based on the mission environment information, and generates leader control input based on the state information of the leader underwater unmanned vehicle and the target state, so as to update the state information of the leader underwater unmanned vehicle. A module generates neighbor state deviation information that represents the deviation between the actual neighbor relationship and the target orientation constraint, based on the state information of the follower underwater unmanned vehicle, the state information of the corresponding neighbor underwater unmanned vehicle, and the neighbor constraint information. Based on whether the external time-varying interference information contains a known upper bound, the module performs interference suppression processing on the neighbor state deviation information to obtain the interference suppression amount. The module that generates the control input of the follower underwater unmanned vehicle and updates the status information of the follower underwater unmanned vehicle based on the neighbor status deviation information, the interference suppression amount, and the control input information of the neighbor underwater unmanned vehicle; The module calculates the actual position information between neighboring underwater unmanned vehicles based on the updated status information of each underwater unmanned vehicle, and determines whether to continue updating the control input or output of the underwater unmanned swarm mission formation control results based on the comparison result of the actual position information and the target position constraint.

[0015] A computer storage medium for storing a computer program, which, when read by the computer, is executed by the computer using the method described thereon.

[0016] A computer, including a processor and a storage medium, executes the method when the processor reads a computer program stored in the storage medium.

[0017] A computer program product, which, as a computer program, implements the method when the computer program is executed.

[0018] Compared with the prior art, the advantages of the technical solution provided by the present invention are as follows: The underwater unmanned swarm adopts a second-order integrator motion model of the follower underwater unmanned vehicle and the leader underwater unmanned vehicle. It incorporates position, velocity, control input and external time-varying disturbances into the same control object description, so that the formation control is no longer based solely on static adjustments of positional relationships, but can simultaneously handle changes in the motion state of underwater unmanned vehicles and the effects of external disturbances. This provides a unified state basis for subsequent calculation of control inputs under time-varying velocity and time-varying water resistance conditions.

[0019] Formation constraints are established based on the relative orientations of neighboring underwater unmanned vehicles (UAVs). This allows formation control targets to be controlled without being limited to fixed relative displacements or distances, instead using the orientational relationships between neighboring targets as the basis for maintaining formation configuration. Since these relative orientation constraints remain unchanged during overall formation translation, rotation, and scaling, this feature enables underwater UAV swarms to reduce their formation scale when traversing narrow obstacle spaces without disrupting the pre-defined orientational relationships between neighboring UAVs.

[0020] The target bearing matrix is ​​used to characterize the target bearing constraints between adjacent underwater unmanned vehicles (UAVs), and together with the relative displacement difference vector and relative velocity difference vector, it participates in the control input calculation. This allows the controller to convert the deviation between the actual neighbor relationship and the target neighbor relationship into control corrections. Compared to control methods that rely solely on relative distance or relative position errors, this feature enables formation adjustments to be directly based on bearing errors, making it more suitable for underwater formation crossing missions that require maintaining bearing relationships but allow for changes in overall scale.

[0021] The communication link and neighbor set limit the information sources for each follower UAV to participate in control calculations, enabling follower UAVs to generate control inputs primarily based on the relative displacement, relative velocity, and target orientation constraints of neighboring UAVs. This feature avoids the controller relying on the global state information of all UAVs, matches the formation control relationship with actual underwater communication conditions, and is beneficial for maintaining local cooperative control in underwater swarm scenarios with limited communication links.

[0022] When the upper limit of external time-varying interference is known, the interference suppression module constructs a compensation amount based on the upper limit of interference received by the link, the target azimuth matrix, and the comprehensive deviation formed by relative displacement and relative velocity, thus linking the external interference compensation with the direction of the neighbor's azimuth error. This feature is not simply a matter of superimposing fixed compensation onto the control input, but rather suppressing the interference components that affect the maintenance of azimuth constraints, thereby reducing the impact of time-varying external interferences such as water resistance on the follower underwater unmanned vehicle's ability to maintain the target azimuth relationship.

[0023] When the upper bound of external time-varying disturbances is unknown, the adaptive disturbance suppression module updates the disturbance suppression amount based on the relative displacement and relative velocity deviation norm under the influence of the target azimuth matrix, enabling the disturbance compensation intensity to adjust with changes in actual formation deviations. This feature allows the controller to form adaptive compensation based on the error performance during neighbor azimuth maintenance without needing to obtain the maximum upper bound of external disturbances in advance. This improves upon the problem that traditional control methods rely on known disturbance boundaries and are difficult to apply to complex underwater environments.

[0024] The appropriate formation controller is selected based on whether the maximum upper bound of the external time-varying disturbance is known, allowing different disturbance suppression methods to be used for scenarios with known and unknown disturbance upper bounds. This feature enables the control strategy to match the actual task conditions, avoiding unnecessary adaptive estimation when disturbance information is sufficient, and also preventing the inability to effectively handle external time-varying disturbances due to the lack of fixed compensation parameters when the disturbance upper bound is unknown.

[0025] The formation controller for follower underwater drones simultaneously incorporates relative displacement difference vectors, relative velocity difference vectors, target orientation matrices, and control input information from neighboring underwater drones. This allows the follower's control input to not only correct spatial configuration deviations but also consider velocity consistency and dynamic changes in neighbors. This feature enables follower underwater drones to continuously adjust their motion state as the leader's speed and target position change, thus adapting to swarm cooperative motion under time-varying formation requirements.

[0026] The control input is constrained by a saturation function before being applied to the underwater unmanned vehicle, ensuring that the calculated control input is within an allowable range. This feature connects the formation control algorithm with the input constraints of the underwater unmanned vehicle's actuators, preventing the controller from generating control quantities exceeding its execution capabilities when there is significant interference or formation deviation, thereby improving the feasibility of the control input on actual underwater vehicles.

[0027] By combining obstacle detection results with leader target position adjustments, when a narrow underwater obstacle space is detected, the overall formation scaling is guided by changing the target position of the leader underwater drone. This feature allows formation obstacle avoidance to avoid relying on replanning independent paths for each follower underwater drone, but rather by changing the leader's target position to drive changes in the overall formation scale, thereby enabling passage through narrow obstacle spaces while maintaining neighboring orientation constraints.

[0028] The leader underwater unmanned vehicle employs target position and target velocity tracking control, enabling the leader to move according to the adjusted target position and target velocity. This feature translates obstacle clearance requirements into changes in the leader's movement target, and through the leader's tracking of the target position and target velocity, it drives the follower formation response, giving the formation shrinking, crossing, and recovery processes a clear motion traction basis.

[0029] The azimuth Laplace matrix is ​​constructed in blocks according to the existence of communication links between underwater unmanned vehicles and target azimuth constraints, so that the communication topology and azimuth constraints can be uniformly expressed in the formation control model. This feature allows the controller to describe the azimuth constraint relationships between the leader and followers, and between followers, based on the matrix structure, and provides structured conditions for determining whether the formation configuration can converge.

[0030] The follower correlation matrix, composed of target orientation constraints among neighbors, is constrained to be a positive definite real symmetric matrix, providing a convergent constraint basis for formation control based on orientation constraints. This feature avoids the problem that the target orientation constraint relationship itself cannot support a stable formation configuration, enabling underwater unmanned swarms to converge toward the preset orientation relationship after repeated updates to control inputs and state information.

[0031] By continuously updating the status information of all underwater unmanned vehicles (UAVs) and calculating the relationship between the actual bearings of neighboring UAVs and the target bearing, formation control forms a closed-loop feedback process. This feature enables the controller to continuously correct the control input based on the current motion state and bearing deviation of the UAVs, rather than generating a fixed control quantity all at once, thus adapting to the dynamic mission process under the combined effects of time-varying disturbances and time-varying formation speed. Attached Figure Description

[0032] Figure 1 Here is a flowchart of the formation control algorithm; Figure 2 Target formation configuration diagram; Figure 3 A diagram showing the communication relationships between underwater unmanned vehicles in an unmanned swarm; Figure 4 This is a scene depicting an underwater unmanned swarm mission formation. Detailed Implementation

[0033] To make the advantages and benefits of the technical solution provided by the present invention clearer, the technical solution provided by the present invention will now be described in further detail with reference to the accompanying drawings, specifically: Implementation Method 1: This implementation method provides a formation control method for time-varying interference underwater unmanned swarm missions based on azimuth constraints, including: The steps include: acquiring the status information, communication relationships, and target orientation constraints of each underwater unmanned vehicle in an underwater unmanned swarm, and determining the neighbor constraint information of each follower underwater unmanned vehicle based on the communication relationships and target orientation constraints; The steps are as follows: determining the target state of the leader underwater unmanned vehicle based on mission environment information, generating leader control input based on the state information of the leader underwater unmanned vehicle and the target state, and updating the state information of the leader underwater unmanned vehicle. The step of generating neighbor state deviation information that characterizes the deviation between the actual neighbor relationship and the target orientation constraint based on the state information of the follower underwater unmanned vehicle, the state information of the corresponding neighbor underwater unmanned vehicle, and the neighbor constraint information. The step of performing interference suppression processing on the neighbor state deviation information based on whether the external time-varying interference information contains a known upper bound of interference to obtain the interference suppression amount; The steps are as follows: generating the control input of the follower underwater unmanned vehicle and updating the status information of the follower underwater unmanned vehicle based on the neighbor state deviation information, the interference suppression amount and the control input information of the neighbor underwater unmanned vehicle; The process involves calculating the actual position information between neighboring underwater unmanned vehicles (UUVs) based on the updated status information of each UUV, and then determining whether to continue updating the control input or output of the underwater UUV swarm task formation control results based on the comparison between the actual position information and the target position constraints.

[0034] The neighbor constraint information includes the set of neighboring underwater unmanned vehicles (UUVs) of the follower UUV, and the target orientation constraint matrix between the follower UUV and its corresponding neighboring UUVs.

[0035] When determining the target state of the leader underwater unmanned vehicle based on the mission environment information, if the mission environment information indicates the presence of a narrow underwater obstacle space, the target position relationship between the leader underwater unmanned vehicles is adjusted, and the adjusted target position and target velocity are taken as the target state.

[0036] The neighbor state deviation information is generated based on the relative displacement difference vector, relative velocity difference vector, and target orientation constraint between the follower underwater unmanned vehicle and the corresponding neighbor underwater unmanned vehicle.

[0037] When performing interference suppression processing on the neighbor state deviation information, if the external time-varying interference information contains a known upper limit of interference, the interference suppression amount is generated based on the known upper limit of interference, the target orientation constraint, and the neighbor state deviation information.

[0038] When performing interference suppression processing on the neighbor state deviation information, if the external time-varying interference information does not contain a known upper limit of interference, the adaptive interference suppression amount is updated according to the change in the neighbor state deviation information after the target orientation constraint is applied, and the adaptive interference suppression amount is used as the interference suppression amount.

[0039] A time-varying interference underwater unmanned swarm formation control device based on orientation constraints, comprising: A module for acquiring the status information, communication relationships, and target orientation constraints of each underwater unmanned vehicle in an underwater unmanned swarm, and determining the neighbor constraint information of each follower underwater unmanned vehicle based on the communication relationships and target orientation constraints; The module determines the target state of the leader underwater unmanned vehicle based on the mission environment information, and generates leader control input based on the state information of the leader underwater unmanned vehicle and the target state, so as to update the state information of the leader underwater unmanned vehicle. A module generates neighbor state deviation information that represents the deviation between the actual neighbor relationship and the target orientation constraint, based on the state information of the follower underwater unmanned vehicle, the state information of the corresponding neighbor underwater unmanned vehicle, and the neighbor constraint information. Based on whether the external time-varying interference information contains a known upper bound, the module performs interference suppression processing on the neighbor state deviation information to obtain the interference suppression amount. The module that generates the control input of the follower underwater unmanned vehicle and updates the status information of the follower underwater unmanned vehicle based on the neighbor status deviation information, the interference suppression amount, and the control input information of the neighbor underwater unmanned vehicle; The module calculates the actual position information between neighboring underwater unmanned vehicles based on the updated status information of each underwater unmanned vehicle, and determines whether to continue updating the control input or output of the underwater unmanned swarm mission formation control results based on the comparison result of the actual position information and the target position constraint.

[0040] A computer storage medium for storing a computer program, which, when read by the computer, is executed by the computer using the method described thereon.

[0041] A computer, including a processor and a storage medium, executes the method when the processor reads a computer program stored in the storage medium.

[0042] A computer program product, which, as a computer program, implements the method when the computer program is executed.

[0043] Implementation Method Two: This implementation method is a further detailed description of the technical solution provided in Implementation Method One, specifically: This embodiment provides a formation control method for underwater unmanned swarm missions under time-varying interference based on orientation constraints. This method is used to control an underwater unmanned swarm including a leader underwater unmanned vehicle and follower underwater unmanned vehicles, so that the underwater unmanned swarm can complete formation movement according to the target orientation constraints between neighboring underwater unmanned vehicles under the conditions of external time-varying interference and time-varying formation movement requirements.

[0044] First, the initial position, initial velocity, control input constraints, and mission formation configuration of each underwater unmanned vehicle (UAV) are acquired. Based on the mission formation configuration, the communication links and neighbor relationships between the UAVs are determined. For each follower UAV, those with existing communication links are designated as neighbors, and the target orientation constraints between the follower UAV and its neighbors are determined based on the mission formation configuration. This yields the neighbor set, target orientation constraints, and control parameters for subsequent control input calculations for each follower UAV.

[0045] Then, obstacle detection results are obtained within the current movement area of ​​the underwater unmanned swarm, and the presence of narrow underwater obstacle spaces that need to be traversed is determined based on these results. When the detection results indicate that no narrow underwater obstacle spaces exist, the leader's target position in the original mission formation configuration is used as the current target position of the leader underwater unmanned vehicle. When the detection results indicate that narrow underwater obstacle spaces exist, the target positions of the leader underwater unmanned vehicles are adjusted according to the obstacle passage space, reducing the target position distance between the leader underwater unmanned vehicles relative to the original mission formation configuration. The adjusted leader target position serves as the input for the leader underwater unmanned vehicle's tracking control, and the movement of the leader underwater unmanned vehicle influences the formation scaling of the subsequent following underwater unmanned vehicles.

[0046] Next, the current position and velocity information of the leader underwater drone are acquired, along with the adjusted target position and velocity information. Based on the deviation between the leader's current position and target position, the deviation between its current velocity and target velocity, and the preset formation motion input, the control input for the leader underwater drone is calculated. After control input constraint processing, the calculated leader control input is used as the actual control input for the leader underwater drone, updating its motion state, and also serving as the neighbor control input information for adjacent follower underwater drones when calculating their control inputs.

[0047] Subsequently, for each follower UAV, the relative displacement difference vector and relative velocity difference vector between the follower UAV and each neighboring UAV are obtained, and the corresponding target orientation constraints are read. The relative displacement difference vector is obtained by subtracting the position information of the follower UAV from the position information of the neighboring UAVs, and the relative velocity difference vector is obtained by subtracting the velocity information of the follower UAV from the velocity information of the neighboring UAVs. The aforementioned relative displacement difference vector, relative velocity difference vector, and target orientation constraints are used together as inputs to the follower UAV formation controller.

[0048] Then, it is determined whether the upper bound of the external time-varying disturbance experienced by the follower underwater unmanned vehicle (UUV) is known information. If the upper bound of the external time-varying disturbance is known information, an interference suppression quantity is generated based on the upper bound of the disturbance experienced by the link between the follower UUV and each neighboring UUV, the target orientation constraint, the relative displacement difference vector, and the relative velocity difference vector. This interference suppression quantity is used to characterize the impact of the external time-varying disturbance on the neighboring orientation constraint maintenance process and serves as a compensation term in the calculation of the follower UUV's control input.

[0049] When the maximum upper bound of external time-varying disturbances is not known information, the comprehensive deviation formed by the relative displacement difference vector and the relative velocity difference vector is projected according to the target azimuth constraint, and the adaptive disturbance suppression quantity is updated according to the magnitude of the deviation after projection processing. The updated adaptive disturbance suppression quantity is used as a compensation term in the control input calculation of the follower underwater unmanned vehicle, enabling the follower underwater unmanned vehicle to adjust the disturbance compensation intensity according to the actual neighbor azimuth deviation changes even in the absence of a preset disturbance upper bound.

[0050] Subsequently, based on the target bearing constraints, relative displacement difference vector, relative velocity difference vector, control input information of neighboring underwater drones, and interference suppression parameters for each follower underwater drone, the formation control input for that follower underwater drone is calculated. The calculation of this formation control input aims to reduce the deviation between the actual bearing of the neighboring drones and the target bearing. Simultaneously, it incorporates the relative velocity difference vector to suppress velocity inconsistencies among neighboring underwater drones and utilizes the control input information of neighboring underwater drones to maintain local cooperative motion. The calculated formation control input, after control input constraint processing, is used as the actual control input for that follower underwater drone.

[0051] Next, based on the actual control inputs of the leader and follower underwater unmanned vehicles (UUVs), the velocity and position information of each UUV are updated. For the follower UUVs, the effects of both the actual control inputs and external time-varying disturbances on their motion state are considered when updating the velocity information. For the leader UUV, its velocity information is updated based on the actual control inputs, and its position information is updated based on the updated velocity information. The updated position and velocity information of each UUV serves as the state inputs for calculating the relative displacement difference vector, relative velocity difference vector, and control inputs of the next round of calculations.

[0052] Then, based on the updated position information of each underwater unmanned vehicle (UAV), the actual bearing information between neighboring UAVs with communication links is calculated, and the actual bearing information is compared with the corresponding target bearing constraints. When the actual bearings between all neighboring UAVs meet the corresponding target bearing constraints, the underwater UAV swarm is determined to have reached the target formation configuration. When the actual bearings between at least one neighboring UAV do not meet the corresponding target bearing constraints, the updated UAV state information is used as new input to re-perform obstacle detection, leader target position determination, interference suppression quantity generation, control input calculation, and state update until the underwater UAV swarm reaches the target formation configuration or meets the preset stopping conditions.

[0053] In one optional implementation, an azimuth Laplace matrix is ​​constructed based on the communication links and target orientation constraints among the underwater unmanned vehicles (UAVs) in the underwater unmanned swarm. For two UAVs without a communication link, a corresponding zero-block matrix is ​​set in the azimuth Laplace matrix; for two UAVs with a communication link, a non-diagonal block matrix determined by their target orientation constraints is set in the azimuth Laplace matrix; for the diagonal block matrix corresponding to the same UAV, it is determined by summing the target orientation constraints of its neighboring UAVs. The constructed azimuth Laplace matrix is ​​used to characterize the communication topology and orientation constraint relationships of the underwater unmanned swarm.

[0054] In one alternative implementation, the azimuth Laplace matrix is ​​divided into blocks according to the leader and follower underwater drones, and the block matrix associated with the follower underwater drones satisfies the positive definite real symmetric condition. This block matrix is ​​used to characterize the constrainable relationship of the follower underwater drones under the target azimuth constraint, and serves as a constraint condition for determining the convergence of the target formation configuration.

[0055] In one alternative implementation, both the external time-varying disturbance and the acceleration of the leader underwater drone are set as time-varying bounded quantities. These time-varying bounded quantities can be continuously varying or piecewise varying. Therefore, when calculating the control inputs for the follower underwater drone, the external time-varying disturbance is treated as a disturbance factor that changes with the mission process, rather than as a fixed constant disturbance.

[0056] In one alternative implementation, the underwater unmanned swarm includes multiple leader underwater unmanned vehicles (UAVs) and multiple follower underwater UAVs, with the leader UAVs having the same formation speed and control input reference. By adjusting the target position distances between the multiple leader UAVs, the underwater unmanned swarm can reduce its formation size when approaching narrow underwater obstacle spaces and restore its formation size according to the original mission formation configuration after passing through the narrow underwater obstacle spaces.

[0057] Implementation Method 3, in conjunction with Appendix Figure 1-4 This embodiment describes the technical solution provided above in further detail through specific examples. Specifically: This implementation proposes a second-order formation controller based on the relative orientation between neighbors under conditions of external interference and time-varying formation speed. It can realize the formation control of unmanned swarms traversing narrow underwater obstacle spaces under conditions of time-varying external interference and time-varying formation movement requirements.

[0058] The motion model of the unmanned swarm individuals in this implementation is a typical second-order integrator motion model. (Follower underwater unmanned vehicle) The motion model of the second-order integrator is shown below: (1) in, , , as well as These are follower underwater unmanned vehicles. Position information, velocity information, control input information, and external time-varying disturbances.

[0059] Similarly, the leader underwater unmanned vehicle The motion model of the second-order integrator is shown below: (2) in, , as well as These are the leader drones The location information, speed information, and control input information are recorded. Note: All leader underwater unmanned vehicles in this embodiment have the same speed and control input.

[0060] If the upper limit of external disturbances is known, then the follower underwater unmanned vehicle The design of the interference suppression module is shown below: (3) in, It is a follower underwater unmanned vehicle Estimated link The upper bound of the disturbance, and These are follower underwater unmanned vehicles. and follower underwater unmanned vehicle The relative displacement difference vector and the relative velocity difference vector between them For underwater unmanned vehicles and underwater unmanned vehicles Target orientation matrix between For the identity matrix, the function It is a symbolic function.

[0061] Combined with follower underwater unmanned vehicle Interference suppression module (1), follower underwater unmanned vehicle The formation controller is shown below: (4) (5) (6) in, and It is a fixed parameter for controlling gain.

[0063] If the maximum upper bound of external disturbances is unknown, follower underwater unmanned vehicle The adaptive interference suppression module is shown below: (7) Combined with follower underwater unmanned vehicle The adaptive interference suppression module (1) of the follower underwater unmanned vehicle The formation controller is shown below: (8) (9) like Figure 1 This implementation mainly designs a mission formation control algorithm for navigating narrow underwater obstacle environments. The algorithm flow is as follows: Step 1: Initialize the initial positions of all underwater unmanned vehicles and set the control parameters of the formation controller as well as the communication and orientation constraints between the underwater unmanned vehicles; Step 2: Detect the presence of obstacles, i.e., the narrow obstacle space in this embodiment. If an obstacle is detected, the formation as a whole achieves obstacle avoidance by adjusting the target positions of all leaders. The control law for leaders to track the target position after the formation change can be (10); Step 3: If all follower underwater unmanned vehicles know the maximum upper bound of external time-varying disturbances, then use the formation controller of (4); otherwise, use the formation controller of (8). Step 4: Update the status information of all underwater unmanned vehicles, and then calculate the orientation information between neighboring underwater unmanned vehicles; Step 5: Compare the bearings of neighboring underwater drones with the target bearing. If the bearings of all neighboring underwater drones are equal to the target bearings of all neighboring underwater drones, then formation control has been achieved; otherwise, proceed to step 2.

[0065] Note: For the narrow underwater obstacle space in this embodiment, from Figure 4 As can be seen, adjusting the leader target position in step 2 can reduce the distance between the target positions of the two leader underwater drones. After adjusting the leader target position in step 2, a tracking controller for the leader to track the target position needs to be designed. For the leader underwater drone... Its tracking controller can be designed as follows: (10) (11) in, , as well as These are the Leader underwater unmanned vehicles. Position information, speed information, and control input information; and It is the adjusted leader underwater unmanned vehicle The target position and target speed.

[0066] This embodiment also includes: 1. For the interference suppression module (3), the symbol Representative of the follower underwater unmanned vehicle All the neighbors underwater Unmanned vehicle assembly, matrix For underwater unmanned vehicles and underwater unmanned vehicles The target orientation constraint matrix between them. Note: When the orientation constraints between individual underwater unmanned vehicles in the formation all meet the target orientation constraints, it means that the formation configuration is complete, that is, the convergence of the control system is achieved.

[0067] 2. For the azimuth Laplace matrix , can be represented as The block matrix, each matrix block is The matrix. If And underwater unmanned vehicles and underwater unmanned vehicles If there is no communication link between them, then the matrix The Line number The block matrix of columns is ;if And underwater unmanned vehicles and underwater unmanned vehicles If there is a communication link between the matrix, then... The Line number The block matrix of columns is ;if Then the matrix The Line number The block matrix of columns is Then, the azimuth Laplace matrix... Dividing the data into blocks based on the number of leader underwater drones and the number of follower underwater drones, we can obtain... .in, .

[0068] 3. For formation control methods based on neighbor-to-neighbor orientation constraints, it is necessary to ensure that the target orientation constraints among neighbors are consistent. matrix It is a positive definite real symmetric matrix.

[0069] 4. The external time-varying disturbances and the leader's acceleration addressed in this embodiment are both time-varying bounded functions.

[0070] Here, the time-varying bounded function can be a continuous function or a discontinuous piecewise function.

[0071] 5. Target-based formation Figure 2 The number of underwater unmanned vehicles is 8, and the orientation constraints between the underwater unmanned vehicles in the corresponding target formation are set as follows: , , , , , .

[0072] The above description of several specific embodiments further details the technical solution provided by the present invention in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the above-described specific embodiments are not intended to limit the present invention. Any reasonable modifications and improvements to the present invention, combinations of embodiments, and equivalent substitutions based on the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A formation control method for time-varying disturbance underwater unmanned swarm missions based on orientation constraints, characterized in that, include: The steps include: acquiring the status information, communication relationships, and target orientation constraints of each underwater unmanned vehicle in an underwater unmanned swarm, and determining the neighbor constraint information of each follower underwater unmanned vehicle based on the communication relationships and target orientation constraints; The steps are as follows: determining the target state of the leader underwater unmanned vehicle based on mission environment information, generating leader control input based on the state information of the leader underwater unmanned vehicle and the target state, and updating the state information of the leader underwater unmanned vehicle. The step of generating neighbor state deviation information that characterizes the deviation between the actual neighbor relationship and the target orientation constraint based on the state information of the follower underwater unmanned vehicle, the state information of the corresponding neighbor underwater unmanned vehicle, and the neighbor constraint information. The step of performing interference suppression processing on the neighbor state deviation information based on whether the external time-varying interference information contains a known upper bound of interference to obtain the interference suppression amount; The steps are as follows: generating the control input of the follower underwater unmanned vehicle and updating the status information of the follower underwater unmanned vehicle based on the neighbor state deviation information, the interference suppression amount and the control input information of the neighbor underwater unmanned vehicle; The process involves calculating the actual position information between neighboring underwater unmanned vehicles (UUVs) based on the updated status information of each UUV, and then determining whether to continue updating the control input or output of the underwater UUV swarm task formation control results based on the comparison between the actual position information and the target position constraints.

2. The method for formation control of time-varying underwater unmanned swarm missions based on orientation constraints according to claim 1, characterized in that, The neighbor constraint information includes the set of neighboring underwater unmanned vehicles (UUVs) of the follower UUV, and the target orientation constraint matrix between the follower UUV and its corresponding neighboring UUVs.

3. The method for formation control of time-varying interference underwater unmanned swarm missions based on orientation constraints according to claim 1, characterized in that, When determining the target state of the leader underwater unmanned vehicle based on the mission environment information, if the mission environment information indicates the presence of a narrow underwater obstacle space, the target position relationship between the leader underwater unmanned vehicles is adjusted, and the adjusted target position and target velocity are taken as the target state.

4. The method for formation control of time-varying interference underwater unmanned swarm missions based on orientation constraints according to claim 1, characterized in that, The neighbor state deviation information is generated based on the relative displacement difference vector, relative velocity difference vector, and target orientation constraint between the follower underwater unmanned vehicle and the corresponding neighbor underwater unmanned vehicle.

5. The method for formation control of time-varying interference underwater unmanned swarm missions based on orientation constraints according to claim 1, characterized in that, When performing interference suppression processing on the neighbor state deviation information, if the external time-varying interference information contains a known upper limit of interference, the interference suppression amount is generated based on the known upper limit of interference, the target orientation constraint, and the neighbor state deviation information.

6. The method for formation control of time-varying interference underwater unmanned swarm missions based on orientation constraints according to claim 1, characterized in that, When performing interference suppression processing on the neighbor state deviation information, if the external time-varying interference information does not contain a known upper limit of interference, the adaptive interference suppression amount is updated according to the change in the neighbor state deviation information after the target orientation constraint is applied, and the adaptive interference suppression amount is used as the interference suppression amount.

7. A formation control device for time-varying interference underwater unmanned swarm missions based on orientation constraints, characterized in that, include: A module for acquiring the status information, communication relationships, and target orientation constraints of each underwater unmanned vehicle in an underwater unmanned swarm, and determining the neighbor constraint information of each follower underwater unmanned vehicle based on the communication relationships and target orientation constraints; The module determines the target state of the leader underwater unmanned vehicle based on the mission environment information, and generates leader control input based on the state information of the leader underwater unmanned vehicle and the target state, so as to update the state information of the leader underwater unmanned vehicle. A module that generates neighbor state deviation information, representing the deviation between the actual neighbor relationship and the target orientation constraint, is generated based on the state information of the follower underwater unmanned vehicle, the state information of the corresponding neighbor underwater unmanned vehicle, and the neighbor constraint information. Based on whether the external time-varying interference information contains a known upper bound, the module performs interference suppression processing on the neighbor state deviation information to obtain the interference suppression amount. The module that generates the control input of the follower underwater unmanned vehicle and updates the status information of the follower underwater unmanned vehicle based on the neighbor state deviation information, the interference suppression amount, and the control input information of the neighbor underwater unmanned vehicle; The module calculates the actual position information between neighboring underwater unmanned vehicles based on the updated status information of each underwater unmanned vehicle, and determines whether to continue updating the control input or output of the underwater unmanned swarm mission formation control results based on the comparison result of the actual position information and the target position constraint.

8. A computer storage medium for storing computer programs, characterized in that, When the computer program is read by the computer, the computer executes the method of claim 1.

9. A computer, comprising a processor and a storage medium, characterized in that, When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 1.

10. A computer program product, as a computer program, is characterized by: When the computer program is executed, it implements the method of claim 1.

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