A method for unpowered ship multi-tug cooperative berthing control

Abstract

The application discloses a kind of unpowered ship multi-tug collaborative berthing control methods, belong to ship autonomous berthing and multi-agent collaborative technical field.It includes: design unpowered ship virtual finite time terminal sliding mode controller, generate the desired total thrust and torque required by unpowered ship;Establish multi-objective optimization function and constraint condition, by grey wolf optimization algorithm to the desired total thrust and torque multi-objective optimal control distribution, obtain the optimal thrust and azimuth angle of each tug;Based on leader-follower formation, obtain the desired trajectory that each tug needs to track;Design the finite time terminal sliding mode controller of each tug, obtain the thrust and torque of each tug;According to the thrust and torque obtained, each tug cooperatively controls unpowered ship berthing according to the desired trajectory.The present application uses the hierarchical collaborative control strategy of "task planning-intelligent allocation-accurate execution", realizes the high-precision, strong robustness, high-efficiency autonomous berthing control of multi-tug to unpowered ship.

Description

Technical Field

[0001] This invention relates to the field of autonomous berthing and multi-agent collaboration technology, and particularly to a method for controlling the collaborative berthing of multiple tugboats on a non-powered vessel. Background Technology

[0002] With the development of global economic integration, the shipping industry's supporting role in foreign trade and the national economy has become increasingly prominent, and port logistics efficiency has become a key factor affecting overall shipping efficiency. Ship entry, exit, and berthing are core aspects of port operations, and their operational efficiency and safety directly affect the stability of the entire logistics system. However, the trend towards larger ships has led to increased inertia and slower maneuvering responses, making berthing a challenge even for experienced crews in confined waters. Especially for large ships that have lost power due to malfunctions, safe berthing in narrow ports is even more difficult, requiring external assistance and becoming one of the most risky and technically complex scenarios in port operations.

[0003] Currently, tugboat assistance for berthing non-powered vessels is the primary operational method. Traditionally, tugboats assist non-powered vessels in berthing under the command of a dispatch center and the operation of crew members. However, this manual operation mode suffers from low efficiency, and the coordination process is susceptible to factors such as communication delays, human error, and environmental disturbances. Statistics show that over 70% of berthing accidents are caused by human error, highlighting the shortcomings of the traditional method in terms of safety and efficiency. Therefore, promoting the transformation of berthing operations towards automation and intelligence has become an urgent need for the industry.

[0004] In recent years, with the development of autonomous surface vessel technology, unmanned intelligent tugboats have shown broad application prospects in port operations. An intelligent collaborative system composed of multiple unmanned tugboats is expected to significantly enhance operational safety and economy while improving the berthing efficiency of unpowered vessels. Compared to traditional manual methods, unmanned tugboat systems offer potential advantages such as high operational precision, fast response speed, all-weather operation, and strong safety. Through multi-vessel information sharing and collaborative control, a global perception of the environment and target vessel status can be achieved, along with dynamic planning and synchronized execution of the power output of multiple tugboats, thereby enabling high-precision and robust control of the attitude and trajectory of unpowered vessels.

[0005] Of course, applying this to high-precision collaborative berthing of unpowered vessels still faces multiple challenges, such as constructing a control framework that can both unify the planning and collaborative command of multi-ship tasks and enable each tugboat to autonomously adjust based on its local environment; reliable control of high-precision and robust motion of multiple ships under complex disturbances; real-time and efficient issuance of general commands to each tugboat for execution; and overall energy consumption control. Therefore, conducting research on multi-agent hierarchical collaborative control of unmanned towing systems is of great significance for realizing autonomous berthing and the intelligent development of ports. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention utilizes a hierarchical collaborative control strategy. The top layer calculates the total control requirements based on the desired berthing trajectory of the unpowered vessel; the middle layer employs a multi-objective optimization algorithm to allocate the total requirements to each tugboat; and the bottom layer designs an anti-interference tracking controller for each tugboat to achieve precise maintenance of the desired formation. Through this three-layer collaborative control, high-precision, robust, and efficient autonomous berthing control of the unpowered vessel by multiple tugboats is achieved.

[0007] To achieve the above objectives, the present invention provides a method for coordinated berthing control of multiple tugboats on a non-powered vessel, comprising the following steps: (1) Based on the expected berthing trajectory and current state of the unpowered vessel, the dynamic model of the vessel, and the environmental disturbance value estimated by the finite-time disturbance observer of the unpowered vessel, design a virtual finite-time terminal sliding mode controller for the unpowered vessel to generate the expected total thrust and torque required by the unpowered vessel. (2) Establish a multi-objective optimization function and constraints, and use the gray wolf optimization algorithm to perform multi-objective optimal control allocation of the expected total thrust and torque to obtain the optimal thrust and azimuth of each tugboat; (3) Based on the optimal azimuth angle assigned to each tugboat, and using the leader-follower formation, the expected trajectory that each tugboat needs to follow is obtained; (4) Based on the optimal thrust allocated to each tugboat, design a finite-time terminal sliding mode controller for each tugboat to obtain the thrust and torque of each tugboat; (5) Each tugboat, based on the obtained thrust and torque, coordinates to control the unpowered vessel to berth according to the desired trajectory.

[0008] Furthermore, step (1) specifically includes: (1.1) The dynamic model of the unpowered ship is as follows: in: The attitude of an unpowered vessel in the Earth coordinate system; and These are the positions of the longitudinal and transverse sway, respectively; For heading angle; Let be the velocity of the unpowered vessel in the ship's coordinate system. and These are the sway and transverse velocities, respectively. The bow roll angular velocity; The mass matrix of an unpowered vessel; The damping matrix for an unpowered vessel; Control forces and moments for unpowered vessels, including longitudinal forces lateral force and bow roll torque ; Environmental disturbances, including lateral disturbances. Longitudinal disturbance and bow rocking disturbance ; This is the transformation matrix between the ship's coordinate system and the Earth's coordinate system; (1.2) Based on the finite-time disturbance observer of the unpowered ship, the estimated value of the environmental disturbance is obtained; The finite-time disturbance observer for unpowered ships is: in: This represents the velocity of an unpowered vessel in the hull coordinate system. The estimated value; and They represent interference respectively. and its derivative The estimated value; , , and These are appropriately selected positive numbers; The design estimation error is: The derivative of the estimation error is expressed as: Existing for a limited time , making when When selecting parameters , , and To ensure estimation error , and The small neighborhood that converges to the origin is now: (1.3) The design of the virtual finite-time terminal sliding mode controller for unpowered ships is as follows: The trajectory tracking error of an unpowered vessel is defined as: in: This represents the desired attitude of an unpowered vessel in the Earth coordinate system. According to the dynamics model of an unpowered ship, the second derivative of the trajectory tracking error is: The finite-time terminal sliding surface design is as follows: in: Represents the variable of the sliding surface; , These are weighting coefficients. The coefficient used to control logarithmic sensitivity; The threshold for segmented switching, To determine the finite-time convergence order; , The coefficient is used to ensure a smooth transition; ; Differentiating the above sliding surface yields: By utilizing the finite-time arctangent sliding mode approach rate, the convergence speed of the system can be accelerated; Based on the environmental disturbance values ​​estimated by the finite-time disturbance observer of the unpowered vessel and the sliding surface variables of the virtual finite-time terminal sliding mode controller of the unpowered vessel, the desired control input of the unpowered vessel is obtained as follows: in: The environmental disturbance value is estimated by a finite-time disturbance observer for unpowered vessels; These are the parameters that need to be adjusted; The total expected thrust and torque required for a non-powered vessel, including longitudinal force, lateral force and bow moment.

[0009] Furthermore, step (2) specifically involves: (2.1) By setting multi-objective control accuracy, energy consumption economy, equipment loss suppression, and singularity avoidance, a complete mathematical model for the multi-objective optimal control allocation problem is obtained: in: Indicates the first A tugboat, Represents the number of tugboats; vector The components represent the magnitude of the longitudinal thrust generated by each tugboat on the unpowered vessel; This indicates the resultant force and torque actually provided by the tugboat system; This represents the total thrust and torque generated by the virtual controller of the unpowered vessel. Indicates the current thrust angle. Indicates the angle of the previous thrust; This represents the tugboat thrust configuration matrix; This represents the weight matrix, used to adjust the importance of tracking errors in the three degrees of freedom: sway, roll, and pitch. This represents the weighting matrix for the changes in the steering angle of each tugboat; It is to avoid small positive numbers with a denominator of zero. These are weighting coefficients. The weight matrix is ​​such that when the system tends to be singular, i.e. This factor will increase dramatically, thus penalizing the allocation result; and These represent the maximum and minimum thrust values ​​that the tugboat can provide, respectively. This indicates the thrust value in the previous step. These represent the lower and upper limits of the rate of change of thrust, respectively. and These represent the maximum and minimum steering angle values ​​that each tugboat can provide, respectively. These represent the lower and upper limits of the rate of change of the steering angle, respectively. (2.2) The gray wolf optimization algorithm is introduced to solve the above mathematical model to obtain the optimal thrust and azimuth of each tugboat.

[0010] Furthermore, step (3) specifically involves: treating the unpowered vessel as a virtual pilot vessel, then the relationship between the unpowered vessel and each tugboat is equivalent to a tugboat formation problem; based on leader-follower formation, the first... The expected trajectory of the tugboat is determined by the current position of the virtual pilot ship. And the relative geometric relationships are generated in real time; in: In the ship's coordinate system, the first... A vector representing the fixed geometric relationship between a tugboat and a large ship. and The first The fixed lateral and longitudinal distances between the contact points of the tugboats and the center of gravity of the large ship. For the first The optimal bearing of the tugboat; The current course of the unpowered vessel The defined rotation matrix is ​​used to transform the above fixed geometric relationships to the Earth coordinate system; This represents the expected trajectory of each tugboat.

[0011] Furthermore, step (4) specifically involves: (4.1) According to Newton's third law, when a tugboat pushes a motionless vessel, the unpowered vessel exerts a reaction force on the tugboat that is equal in magnitude and opposite in direction. Therefore, the third law... The dynamic equations of a tugboat are expressed as follows: in, Indicates the first The control forces and moments of a tugboat, including longitudinal forces. lateral force and steering torque ; Indicates that the unpowered vessel is related to the first The reaction force of the tugboat To be assigned to the The optimal thrust of a tugboat; Indicates the first Mass matrix of the tugboats; Indicates the first Environmental disturbances to the tugboat, including lateral disturbances. Longitudinal disturbance and bow rocking disturbance ; Indicates the first Damping matrix of a tugboat; The attitude of the tugboat in the Earth coordinate system; and These are the positions of the longitudinal and transverse sway, respectively; For heading angle; For the first The speed of the tugboat in the ship's coordinate system; For the first Damping matrix of a tugboat; This is the transformation matrix between the ship's coordinate system and the Earth's coordinate system; (4.2) Based on the finite-time disturbance observers of each tugboat, the estimated values ​​of environmental disturbances for each tugboat are obtained; The finite-time disturbance observers for each tugboat are: in: Indicates the first The speed of the tugboat in the ship's coordinate system The estimated value; and They represent the first Interference from a tugboat and its derivative The estimated value; , , and These are appropriately selected positive numbers; The design estimation error is: The derivative of the estimation error is expressed as: Existing for a limited time , making when When selecting parameters , , and To ensure estimation error , and The region converges to a small neighborhood of the origin; at this point: (4.3) The finite-time terminal sliding mode controllers for each tugboat are designed as follows: The trajectory tracking error is defined as: in: This indicates the actual trajectory of each tugboat. This represents the expected trajectory of each tugboat; Based on the formula of the tugboat dynamics model, the second derivative of the trajectory tracking error can be derived as follows: The finite-time terminal slip surface of each tugboat is as follows: in: Represents the variable of the sliding surface; , These are weighting coefficients; The coefficient used to control logarithmic sensitivity; The threshold for segmented switching; To determine the finite-time convergence order; , The coefficient is used to ensure a smooth transition; ; Differentiating the above sliding surface yields: By utilizing the finite-time arctangent sliding mode approach rate, the convergence speed of the system can be accelerated; The expected force and torque calculated by each tugboat controller are written as follows: in: Indicates the first The control force and torque of a tugboat.

[0012] The present invention also provides a multi-tugboat cooperative berthing control system for unpowered vessels, comprising: The collaborative control layer is used to design a virtual finite-time terminal sliding mode controller for the unpowered vessel based on the desired berthing trajectory and current state of the unpowered vessel, the vessel's dynamic model, and the environmental disturbance values ​​estimated by the unpowered vessel's finite-time disturbance observer. This controller generates the desired total thrust and torque required by the unpowered vessel. A multi-objective optimization function and constraints are established, and the total thrust and torque are allocated using the Grey Wolf optimization algorithm to obtain the optimal thrust and azimuth angle for each tugboat. The tugboat control layer is used to obtain the desired trajectory that each tugboat needs to follow based on the leader-follower formation, according to the optimal azimuth angle assigned to each tugboat; and to design the finite-time terminal sliding mode controller for each tugboat based on the optimal thrust assigned to each tugboat, so as to obtain the thrust and torque of each tugboat. The control object layer is used by each tugboat to coordinately control the berthing of unpowered vessels according to the obtained thrust and torque and the desired trajectory.

[0013] The present invention also provides a storage medium comprising a stored program, wherein, when the program is executed, the non-powered vessel multi-tugboat cooperative berthing control method described above is performed.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described method for coordinated berthing control of multiple tugboats on a non-powered vessel through the computer program.

[0015] The beneficial effects of this invention are: 1. This invention proposes a three-layer collaborative control architecture of "task planning - intelligent allocation - precise execution", which constructs a systematic collaborative control system. The top-level virtual controller automatically generates the overall control command, the middle-level intelligent allocation algorithm automatically decomposes the task, and the bottom-level tugboat controller automatically and precisely executes the command, thereby realizing high-precision, robust, and efficient autonomous berthing control of multiple tugboats for unpowered vessels.

[0016] 2. This invention addresses the problem of relying heavily on manual experience for coordinated berthing of multiple tugboats by employing a multi-objective intelligent control allocation strategy based on the Grey Wolf optimization algorithm. This method can balance multiple indicators such as control accuracy, system energy consumption, and equipment wear in real time online, and quickly solve for the optimal thrust and azimuth commands for each tugboat that satisfy various physical constraints.

[0017] 3. This invention provides a finite-time nonsingular terminal sliding mode controller for ships, ensuring high-precision convergence of tracking errors within a finite time. Simultaneously, the designed finite-time disturbance observer enables rapid estimation and real-time compensation of time-varying disturbances in ports. The combination of these two technologies fundamentally improves the reliability of autonomous berthing under complex sea conditions. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the process for the coordinated berthing control method of multiple tugboats for unpowered vessels according to an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of a non-powered vessel-multiple tugboat formation configuration according to an embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of a typical berthing scenario of multiple tugboats working together for a non-powered vessel, according to an embodiment of the present invention.

[0021] Figure 4 This is a schematic diagram of the framework of the multi-tugboat cooperative berthing control system for unpowered vessels according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] like Figure 1 As shown in the figure, this invention provides a method for coordinated berthing control of multiple tugboats on a non-powered vessel. The formation configuration adopted by the non-powered vessel-multiple tugboat coordinated system is as follows. Figure 2 As shown, this embodiment of the invention employs a push-type formation configuration. Its purpose is to ensure effective mechanical contact and thrust transfer between each tugboat and the unpowered vessel, allowing single or multiple tugboats to coordinate and adjust their output, thereby ensuring the stability and controllability of the thrust system during berthing. A typical berthing scenario involving multiple tugboats coordinating with an unpowered vessel is illustrated in the diagram below. Figure 3 As shown.

[0024] The specific steps are as follows: S101. Based on the expected berthing trajectory and current state of the unpowered vessel, the vessel's dynamic model, and the environmental disturbance values ​​estimated by the unpowered vessel's finite-time disturbance observer, design a virtual finite-time terminal sliding mode controller for the unpowered vessel to generate the expected total thrust and torque required by the unpowered vessel.

[0025] (1) Construct a dynamic model of a non-powered ship.

[0026] Since unpowered vessels typically berth at low speeds, only three degrees of freedom are considered: pitch, sway, and yaw. The corresponding kinematic and dynamic models are as follows: in: The attitude of the unpowered vessel in the Earth coordinate system is XAOAYA. and These are the positions of the longitudinal and transverse sway, respectively; For heading angle; The velocity of the unpowered vessel in the XBOBYB hull coordinate system is given. and These are the sway and transverse velocities, respectively. The bow roll angular velocity; The mass matrix of an unpowered vessel; The damping matrix for an unpowered vessel; Control forces and moments for unpowered vessels, including longitudinal forces lateral force and bow roll torque ; Environmental disturbances, including lateral disturbances Longitudinal disturbance and bow rocking disturbance ; This is the transformation matrix between the ship's coordinate system and the Earth's coordinate system.

[0027] It is given by the following formula: (2) Based on the finite-time disturbance observer of the unpowered ship, the estimated value of environmental disturbance is obtained.

[0028] The finite-time disturbance observer for unpowered ships is: in: This represents the velocity of an unpowered vessel in the hull coordinate system. The estimated value; and They represent interference respectively. and its derivative The estimated value; , , and These are appropriately selected positive numbers.

[0029] The design estimation error is: The derivative of the estimation error is expressed as: Existing for a limited time , making when When selecting parameters , , and To ensure estimation error , and The small neighborhood that converges to the origin is now: (3) Design a virtual finite-time terminal sliding mode controller for unpowered ships.

[0030] The trajectory tracking error of an unpowered vessel is defined as: in: This represents the desired attitude of an unpowered vessel in the Earth coordinate system.

[0031] According to the dynamics model of an unpowered ship, the second derivative of the trajectory tracking error is: The finite-time terminal sliding surface design is as follows: in: Represents the variable of the sliding surface; , These are weighting coefficients. Controlling logarithmic sensitivity, It is the segmented switching threshold. Determine the finite-time convergence order. , Ensure a smooth transition. .

[0032] Differentiating the above sliding surface yields: To further accelerate the convergence speed of the system, this invention proposes a new finite-time arctangent sliding mode convergence rate, expressed as follows: Based on the environmental disturbance values ​​estimated by the finite-time disturbance observer of the unpowered vessel and the sliding surface variables of the virtual finite-time terminal sliding mode controller of the unpowered vessel, the desired control input of the unpowered vessel is obtained as follows: in: The environmental disturbance value is estimated by a finite-time disturbance observer for unpowered vessels; These are the parameters that need to be adjusted; The total expected thrust and torque required for a non-powered vessel, including longitudinal force, lateral force and bow moment.

[0033] In this embodiment of the invention, the unpowered vessel is propelled forward by tugboats. It is assumed that the contact surface between the large vessel and the tugboats can be simplified to a single point, and that each tugboat only provides its longitudinal thrust. Therefore, the control force and torque given by the above formulas... This can be considered as the resultant force provided by all the tugboats. This force can be defined as: Where: vector (This embodiment of the invention uses 4 tugboats, i.e.) The components of the matrix represent the magnitude of the longitudinal thrust exerted by each tugboat on the unpowered vessel. This is called the tugboat thrust configuration matrix.

[0034] Its definition is as follows: in: Indicates the first The thrust angle exerted by a tugboat on an unpowered vessel. Indicates the first The coordinates of the contact point between the tugboats are given, and all of the above parameters are defined based on the ship's coordinate system.

[0035] S102. Establish a multi-objective optimization function and constraints, and use the Grey Wolf optimization algorithm to perform multi-objective optimal control allocation of total thrust and torque to obtain the optimal thrust and azimuth angle of each tugboat.

[0036] (1) By setting multi-objective control accuracy, energy consumption economy, equipment loss suppression and singularity avoidance, a complete mathematical model of the multi-objective optimal control allocation problem is obtained (the following models are all introduced with 4 tugboats as an example).

[0037] Control accuracy: in: This represents the resultant force and torque actually provided by each tugboat; This represents the total expected force and torque generated by the controller of a non-powered ship. This represents the weight matrix.

[0038] Energy efficiency: Where: vector Each component represents the magnitude of the longitudinal thrust generated by each tugboat on the unpowered vessel.

[0039] Equipment loss suppression: in: This represents the weighting matrix for the changes in the steering angle of each tugboat. Indicates the current step thrust angle. This indicates the angle of the previous thrust.

[0040] System singularity avoidance: Where: ε is a small positive number to avoid a denominator of zero, and δ is a weighting coefficient. This is the weight matrix. When the system tends towards singularity, i.e. This item will increase dramatically, thus penalizing the allocation result.

[0041] Meanwhile, the optimization problem also needs to satisfy the amplitude and rate of change constraints of the tugboat thrust and steering angle.

[0042] Consider single-step time allocation and thrust rate of change limit, thrust The following adjustments need to be made dynamically: in: and These represent the maximum and minimum thrust values ​​that the tugboat can provide, respectively. This indicates the thrust value in the previous step. These represent the lower and upper limits of the thrust change rate, respectively.

[0043] Similarly, the tugboat steering angle It must also meet the requirements of dynamic change range: in: and These represent the maximum and minimum steering angle values ​​that each tugboat can provide, respectively. These represent the lower and upper limits of the rate of change of the steering angle, respectively.

[0044] In summary, the complete mathematical model for the thrust allocation optimization problem can be expressed as follows: in: Indicates the first A tugboat, Indicates the number of tugboats; This indicates the resultant force and torque actually provided by the tugboat system; This represents the total thrust and torque generated by the virtual controller of the unpowered vessel. Indicates the current thrust angle. Indicates the angle of the previous thrust; This represents the tugboat thrust configuration matrix; This represents the weight matrix, used to adjust the importance of tracking errors in the three degrees of freedom: sway, roll, and pitch. This represents the weighting matrix for the changes in the steering angle of each tugboat; It is to avoid small positive numbers with a denominator of zero. These are weighting coefficients. The weight matrix is ​​such that when the system tends to be singular, i.e. This factor will increase dramatically, thus penalizing the allocation result; and These represent the maximum and minimum thrust values ​​that the tugboat can provide, respectively. This indicates the thrust value in the previous step. These represent the lower and upper limits of the rate of change of thrust, respectively. and These represent the maximum and minimum steering angle values ​​that each tugboat can provide, respectively. These represent the lower and upper limits of the rate of change of the steering angle, respectively.

[0045] (2) Introduce the Grey Wolf Optimization Algorithm to achieve multi-objective optimal control allocation of total demand.

[0046] For this type of complex optimization problem, this embodiment of the invention employs the Gray Wolf Optimization Algorithm (GWO) for solution. As a swarm intelligence algorithm, GWO simulates the social hierarchy and cooperative hunting behavior of a wolf pack. Its leader-follower mechanism allows it to simultaneously conduct extensive exploration and fine-grained development in the solution space. This algorithm does not rely on gradient information, has stronger global search capabilities and robustness, and can effectively maintain population diversity and avoid premature convergence. Therefore, it is particularly suitable for handling the described nonlinear, multimodal, constrained multi-objective problems, and can generate optimal allocation instructions in real time that balance accuracy, energy consumption, and reliability.

[0047] S103. Based on the optimal azimuth angle assigned to each tugboat, and using the leader-follower formation, obtain the desired trajectory that each tugboat needs to follow.

[0048] To ensure effective thrust transfer, the four tugboats must maintain a constant contact point with the large ship. Therefore, this problem can be equivalent to a tugboat formation problem, where the tugboats follow the large ship in a fixed formation. If the tugboats deviate from this fixed formation, it may lead to thrust interruption or collisions between the hulls. A pilot-following method is used for formation control, with the formation structure consisting of a virtual pilot ship and four following tugboats. The trajectory of the virtual pilot ship is shown. The design is based on the posture of the large ship, and the first The expected trajectory of the tugboat is determined by the current position of the virtual pilot ship. The relative geometric relationships are generated in real time, and the specific expression is as follows: in: This represents a vector representing the fixed geometric relationship between each tugboat and the unpowered vessel in the ship's coordinate system, where and These are the fixed lateral and longitudinal distances of the tugboat's contact point relative to the ship's center of gravity, respectively. The thrust direction angle to which the thrust is distributed; The current course of the unpowered vessel The defined rotation matrix is ​​used to transform the above fixed geometric relationships to the Earth coordinate system.

[0049] S104. Based on the optimal thrust allocated to each tugboat, design a finite-time terminal sliding mode controller for each tugboat to obtain the thrust and torque of each tugboat.

[0050] (1) According to Newton's third law, when a tugboat pushes a motionless vessel, the unpowered vessel exerts a reaction force on the tugboat that is equal in magnitude and opposite in direction. Therefore, the third law... The dynamic equations of a tugboat are expressed as follows: in, Indicates the first The control forces and moments of a tugboat, including longitudinal forces. lateral force and steering torque ; Indicates that the unpowered vessel is related to the first The reaction force of the tugboat To be assigned to the The optimal thrust of a tugboat; Indicates the first Mass matrix of the tugboats; Indicates the first Environmental disturbances to the tugboat, including lateral disturbances. Longitudinal disturbance and bow rocking disturbance ; Indicates the first Damping matrix of a tugboat; The attitude of the tugboat in the Earth coordinate system; and These are the positions of the longitudinal and transverse sway, respectively; For heading angle; For the first The speed of the tugboat in the ship's coordinate system; For the first Damping matrix of a tugboat; This is the transformation matrix between the ship's coordinate system and the Earth's coordinate system.

[0051] (2) Based on the finite-time disturbance observers of each tugboat, the estimated values ​​of environmental disturbances for each tugboat are obtained; The finite-time disturbance observers for each tugboat are: in: Indicates the first The speed of the tugboat in the ship's coordinate system The estimated value; and They represent the first Interference from a tugboat and its derivative The estimated value; , , and These are appropriately selected positive numbers.

[0052] The design estimation error is: The derivative of the estimation error is expressed as: Existing for a limited time , making when When selecting parameters , , and To ensure estimation error , and The small neighborhood that converges to the origin is now: (3) The finite-time terminal sliding mode controllers for each tugboat are designed as follows: The trajectory tracking error is defined as: in: This indicates the actual trajectory of each tugboat. This represents the expected trajectory of each tugboat; Based on the formula of the tugboat dynamics model, the second derivative of the trajectory tracking error can be derived as follows: To improve the robustness and convergence speed of the system, the finite-time terminal sliding mode controller (FTSMC) is designed with the following degrees of freedom: in: Represents the variable of the sliding surface; , These are weighting coefficients; The coefficient used to control logarithmic sensitivity; The threshold for segmented switching; To determine the finite-time convergence order; , The coefficient is used to ensure a smooth transition; .

[0053] Differentiating the above sliding surface yields: To further accelerate the convergence speed of the system, the present invention also employs a finite-time arctangent sliding mode approach rate, expressed as follows: The expected force and torque calculated by each tugboat controller are written as follows: in: Indicates the first The control force and torque of a tugboat.

[0054] S105. Based on the obtained thrust and torque, each tugboat coordinates to control the berthing of the unpowered vessel according to the desired trajectory.

[0055] like Figure 4 As shown, this embodiment of the invention also provides a multi-tugboat cooperative berthing control system for unpowered vessels, including: The collaborative control layer is used to design a virtual finite-time terminal sliding mode controller for the unpowered vessel based on the desired berthing trajectory and current state of the unpowered vessel, the vessel's dynamic model, and the environmental disturbance values ​​estimated by the unpowered vessel's finite-time disturbance observer. This controller generates the desired total thrust and torque required by the unpowered vessel. A multi-objective optimization function and constraints are established, and the total thrust and torque are allocated using the Grey Wolf optimization algorithm to obtain the optimal thrust and azimuth angle for each tugboat.

[0056] The tugboat control layer is used to obtain the desired trajectory that each tugboat needs to follow based on the leader-follower formation, according to the optimal azimuth angle assigned to each tugboat; and to design a finite-time terminal sliding mode controller for each tugboat based on the optimal thrust assigned to each tugboat, so as to obtain the thrust and torque of each tugboat.

[0057] The control object layer is used by each tugboat to coordinately control the berthing of unpowered vessels according to the obtained thrust and torque and the desired trajectory.

[0058] This invention also provides a storage medium, which includes a stored program, wherein when the program is executed, it performs the non-powered vessel multi-tugboat cooperative berthing control method as described above.

[0059] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the non-powered vessel multi-tugboat cooperative berthing control method described above through the computer program.

[0060] Finally, it should be noted that the above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for coordinated berthing control of multiple tugboats on a non-powered vessel, characterized in that, Includes the following steps: (1) Based on the expected berthing trajectory and current state of the unpowered vessel, the dynamic model of the vessel, and the environmental disturbance value estimated by the finite-time disturbance observer of the unpowered vessel, design a virtual finite-time terminal sliding mode controller for the unpowered vessel to generate the expected total thrust and torque required by the unpowered vessel. (2) Establish a multi-objective optimization function and constraints, and use the gray wolf optimization algorithm to perform multi-objective optimal control allocation of the expected total thrust and torque to obtain the optimal thrust and azimuth of each tugboat; (3) Based on the optimal azimuth angle assigned to each tugboat, and using the leader-follower formation, the expected trajectory that each tugboat needs to follow is obtained; (4) Based on the optimal thrust allocated to each tugboat, design a finite-time terminal sliding mode controller for each tugboat to obtain the thrust and torque of each tugboat; (5) Each tugboat, based on the obtained thrust and torque, coordinates to control the unpowered vessel to berth according to the desired trajectory.

2. The method for coordinated berthing control of multiple tugboats for unpowered vessels according to claim 1, characterized in that, The specific steps (1) are as follows: (1.1) The dynamic model of the unpowered ship is as follows: in: The attitude of an unpowered vessel in the Earth coordinate system; and These are the positions of the longitudinal and transverse sway, respectively; For heading angle; Let be the velocity of the unpowered vessel in the hull coordinate system. and These are the sway and transverse velocities, respectively. The bow roll angular velocity; The mass matrix of an unpowered vessel; The damping matrix for an unpowered vessel; Control forces and moments for unpowered vessels, including longitudinal forces lateral force and bow roll torque ; Environmental disturbances, including lateral disturbances Longitudinal disturbance and bow rocking disturbance ; This is the transformation matrix between the ship's coordinate system and the Earth's coordinate system; (1.2) Based on the finite-time disturbance observer of the unpowered ship, the estimated value of the environmental disturbance is obtained; The finite-time disturbance observer for unpowered ships is: in: This represents the velocity of an unpowered vessel in the hull coordinate system. The estimated value; and They represent interference respectively. and its derivative The estimated value; , , and These are appropriately selected positive numbers; The design estimation error is: The derivative of the estimation error is expressed as: Existing for a limited time , making when When selecting parameters , , and To ensure estimation error , and The small neighborhood that converges to the origin is now: (1.3) The design of the virtual finite-time terminal sliding mode controller for unpowered ships is as follows: The trajectory tracking error of an unpowered vessel is defined as: in: This represents the desired attitude of an unpowered vessel in the Earth coordinate system. According to the dynamics model of an unpowered ship, the second derivative of the trajectory tracking error is: The finite-time terminal sliding surface design is as follows: in: Represents the variable of the sliding surface; , These are weighting coefficients. The coefficient used to control logarithmic sensitivity; The threshold for segmented switching, To determine the finite-time convergence order; , The coefficient is used to ensure a smooth transition; ; Differentiating the above sliding surface yields: By utilizing the finite-time arctangent sliding mode approach rate, the convergence speed of the system can be accelerated; Based on the environmental disturbance values ​​estimated by the finite-time disturbance observer of the unpowered vessel and the sliding surface variables of the virtual finite-time terminal sliding mode controller of the unpowered vessel, the desired control input of the unpowered vessel is obtained as follows: in: The environmental disturbance value is estimated by a finite-time disturbance observer for unpowered vessels; These are the parameters that need to be adjusted; The total expected thrust and torque required for a non-powered vessel, including longitudinal force, lateral force and bow moment.

3. The method for coordinated berthing control of multiple tugboats for unpowered vessels according to claim 1, characterized in that, Step (2) specifically involves: (2.1) By setting multi-objective control accuracy, energy consumption economy, equipment loss suppression, and singularity avoidance, a complete mathematical model for the multi-objective optimal control allocation problem is obtained: in: Indicates the first A tugboat, Represents the number of tugboats; vector The components represent the magnitude of the longitudinal thrust generated by each tugboat on the unpowered vessel; This indicates the resultant force and torque actually provided by the tugboat system; This represents the total thrust and torque generated by the virtual controller of the unpowered vessel. Indicates the current thrust angle. Indicates the angle of the previous thrust; This represents the tugboat thrust configuration matrix; This represents the weight matrix, used to adjust the importance of tracking errors in the three degrees of freedom: sway, roll, and pitch. This represents the weighting matrix for the changes in the steering angle of each tugboat; It is to avoid small positive numbers with a denominator of zero. These are weighting coefficients. The weight matrix is ​​such that when the system tends to be singular, i.e. This factor will increase dramatically, thus penalizing the allocation result; and These represent the maximum and minimum thrust values ​​that the tugboat can provide, respectively. This indicates the thrust value in the previous step. These represent the lower and upper limits of the thrust rate of change, respectively. and These represent the maximum and minimum steering angle values ​​that each tugboat can provide, respectively. These represent the lower and upper limits of the rate of change of the steering angle, respectively. (2.2) The gray wolf optimization algorithm is introduced to solve the above mathematical model to obtain the optimal thrust and azimuth of each tugboat.

4. The method for coordinated berthing control of multiple tugboats for unpowered vessels according to claim 1, characterized in that: The specific steps (3) are as follows: The unpowered vessel is used as a virtual pilot vessel, thus the relationship between the unpowered vessel and each tugboat is equivalent to a tugboat formation problem; based on leader-follower formation, the first... The expected trajectory of the tugboat is determined by the current position of the virtual pilot ship. And the relative geometric relationships are generated in real time; in: In the ship's coordinate system, the first... A vector representing the fixed geometric relationship between a tugboat and a large ship. and The first The fixed lateral and longitudinal distances between the contact points of the tugboats and the center of gravity of the large ship. For the first The optimal bearing of the tugboat; The current course of the unpowered vessel The defined rotation matrix is ​​used to transform the above fixed geometric relationships to the Earth coordinate system; This represents the expected trajectory of each tugboat.

5. The method for coordinated berthing control of multiple tugboats for unpowered vessels according to claim 4, characterized in that: Step (4) specifically involves: (4.1) According to Newton's third law, when a tugboat pushes a motionless vessel, the unpowered vessel exerts a reaction force on the tugboat that is equal in magnitude and opposite in direction. Therefore, the third law... The dynamic equations of a tugboat are expressed as follows: in, Indicates the first The control forces and moments of a tugboat, including longitudinal forces. lateral force and steering torque ; Indicates that the unpowered vessel is related to the first The reaction force of the tugboat To be assigned to the The optimal thrust of a tugboat; Indicates the first Mass matrix of the tugboats; Indicates the first Environmental disturbances to the tugboat, including lateral disturbances. Longitudinal disturbance and bow rocking disturbance ; Indicates the first Damping matrix of a tugboat; The attitude of the tugboat in the Earth coordinate system; and These are the positions of the longitudinal and transverse sway, respectively; For heading angle; For the first The speed of the tugboat in the ship's coordinate system; For the first Damping matrix of a tugboat; This is the transformation matrix between the ship's coordinate system and the Earth's coordinate system; (4.2) Based on the finite-time disturbance observers of each tugboat, the estimated values ​​of environmental disturbances for each tugboat are obtained; The finite-time disturbance observers for each tugboat are: in: Indicates the first The speed of the tugboat in the ship's coordinate system The estimated value; and They represent the first Interference from a tugboat and its derivative The estimated value; , , and These are appropriately selected positive numbers; The design estimation error is: The derivative of the estimation error is expressed as: Existing for a limited time , making when When selecting parameters , , and To ensure estimation error , and The region converges to a small neighborhood of the origin; at this point: (4.3) The finite-time terminal sliding mode controllers for each tugboat are designed as follows: The trajectory tracking error is defined as: in: This indicates the actual trajectory of each tugboat. This represents the expected trajectory of each tugboat; Based on the formula of the tugboat dynamics model, the second derivative of the trajectory tracking error can be derived as follows: The finite-time terminal slip surface of each tugboat is as follows: in: Represents the variable of the sliding surface; , These are weighting coefficients; The coefficient used to control logarithmic sensitivity; The threshold for segmented switching; To determine the finite-time convergence order; , The coefficient is used to ensure a smooth transition; ; Differentiating the above sliding surface yields: By utilizing the finite-time arctangent sliding mode approach rate, the convergence speed of the system can be accelerated; The desired force and torque calculated by each tugboat controller are written as follows: in: Indicates the first The control force and torque of a tugboat.

6. A multi-tugboat cooperative berthing control system for unpowered vessels, characterized in that, include: The collaborative control layer is used to design a virtual finite-time terminal sliding mode controller for the unpowered vessel based on its desired berthing trajectory and current state, the vessel's dynamic model, and the environmental disturbance values ​​estimated by the unpowered vessel's finite-time disturbance observer. This controller generates the desired total thrust and torque required by the unpowered vessel. A multi-objective optimization function and constraints are established, and the total thrust and torque are allocated using the Grey Wolf optimization algorithm to obtain the optimal thrust and azimuth angle for each tugboat. The tugboat control layer is used to obtain the desired trajectory that each tugboat needs to follow based on the leader-follower formation, according to the optimal azimuth angle assigned to each tugboat; and to design the finite-time terminal sliding mode controller for each tugboat based on the optimal thrust assigned to each tugboat, so as to obtain the thrust and torque of each tugboat. The control object layer is used by each tugboat to coordinately control the berthing of unpowered vessels according to the obtained thrust and torque and the desired trajectory.

7. A storage medium, characterized in that, The storage medium includes a stored program, wherein when the program is executed, it performs the non-powered vessel multi-tugboat cooperative berthing control method according to any one of claims 1 to 5.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the non-powered vessel multi-tugboat cooperative berthing control method according to any one of claims 1 to 5 through the computer program.

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