Double-unmanned-ship towing control method based on optimal force distribution and cooperative control strategy

Abstract

The invention discloses a double unmanned ship towing control method based on optimal force distribution and a cooperative control strategy, and the method comprises the following steps: (1) building a comprehensive dynamic model of a towing control system according to position movement and stress analysis; (2) aiming at towing and pushing operation of the tugboat of the double unmanned boats, decomposing a towing and pushing task into stress planning of a barge and trajectory tracking control of the tugboat, and providing an optimal force distribution method to distribute expected force so as to distribute required force and determine a towing angle and a pushing angle; and (3) based on the comprehensive dynamical model, a novel collaborative model predictive control strategy is provided to control the barge to arrive at a designated position. Compared with the prior art, the problem of complex multi-ship cooperative operation is effectively solved, the overall control time of the double unmanned ships is shortened, the control efficiency of the system is greatly improved, and technical support is provided for development of a new-generation water unmanned tugboat system.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned boats, and in particular relates to a dual unmanned boat towing control method based on optimal force distribution and collaborative control strategy. Background Art

[0002] With the booming global shipping industry and the rapid increase in navigation density, towing business has also ushered in an unprecedented busy period. In this context, the trend of larger ships has significantly increased the difficulty of maneuvering in special working conditions such as entering and leaving ports and berthing and leaving docks, and tugboat assistance is urgently needed to achieve efficient and safe navigation. In addition, towing operations also play a vital role in the sea rescue of barges without self-propulsion capabilities, ships that have lost their self-propulsion capabilities, and the transfer of offshore drilling platforms.

[0003] However, the traditional manual towing operation has gradually failed to meet the growing demand for towing business due to its cumbersome procedures, complex operations, high risks and low efficiency. In this context, the rapid development of artificial intelligence technology has brought innovative possibilities to towing operations. Unmanned intelligent bodies such as drones, unmanned ships, and unmanned cars have been widely used in industry and people's lives, and unmanned tugboats, as one of them, have also begun to show their unique advantages and potential.

[0004] Traditional towing operations mainly rely on the on-site judgment and experience of the captain and pilot. This method is difficult to achieve accuracy in route setting and control, and there are certain safety hazards. At the same time, the way in which the pilot sends instructions to multiple tugboat captains through the pager has delays and uncertainties in information transmission, which can easily cause accidents in busy routes and ports. The development of a collaborative towing operation system for unmanned tugboat clusters has great practical significance and far-reaching strategic significance for overcoming the various drawbacks of traditional manual towing operations and improving the efficiency and safety of towing operations. This not only greatly promotes the development of the shipping industry and marine engineering, but also provides useful reference and inspiration for the future application of unmanned intelligent technology in more fields. Summary of the invention

[0005] In order to overcome the shortcomings of the prior art, the present invention provides a dual unmanned boat towing control method based on optimal force distribution and collaborative control strategy, the method comprising the following steps: (1) Based on position motion and force analysis, a comprehensive dynamic model of the towing control system is established; (2) For the towing and pushing operation of the dual unmanned boat tugboat, the towing and pushing task is decomposed into the force planning of the barge and the trajectory tracking control of the tugboat, and an optimal force distribution method is proposed to distribute the desired force to distribute the required force and determine the towing angle and the pushing angle; (3) Based on the comprehensive dynamic model, a new collaborative model predictive control strategy is proposed to control the barge to reach the specified position. Compared with the prior art, the present invention effectively solves the complex multi-vessel collaborative operation problem, shortens the overall control time of the dual unmanned boat, greatly improves the control efficiency of the system, and provides technical support for the development of a new generation of unmanned tugboat systems on the water.

[0006] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0007] Step 1: Establish a comprehensive dynamic model of the unmanned tugboat autonomously maneuvering barge system;

[0008] Step 2: Construct the real-time dynamic allocation method of the optimal maneuvering force of the barge;

[0009] Step 3: Construct a predictive control strategy for the dual tugboat collaborative model.

[0010] Preferably, the step 1 is specifically:

[0011] Using the catenary model, the horizontal tension F of the towing cable is calculated. T ;

[0012] Rubber fenders are installed around the tugboat to cushion the impact of the collision between the tugboat and the barge during propulsion. The elastic potential energy of the rubber is calculated based on the force transmission relationship to obtain the deformation of the rubber, and the thrust F of the barge is obtained through the empirical formula. P ;

[0013] The Fossen wind-wave disturbance model is introduced to obtain the moment τ of wind and surge on the system. wind , τ wave ;

[0014] The speed and position information of the forward tugboat, the stern pusher tugboat and the barge are taken as reference quantities, that is, v T 、v P , and η T , η P ,

[0015] The force analysis of the ship is carried out and the dynamic model of the barge is established as follows:

[0016]

[0017] The dynamic model of the forward tugboat is as follows:

[0018]

[0019] The dynamic model of the stern pusher tugboat is as follows:

[0020]

[0021] Among them, M T 、M P , are the mass matrices of the forward tugboat, stern pusher tugboat and barge, respectively, O T , O P , are the Coriolis-centripetal matrices of the forward tugboat, the stern pusher tugboat and the barge, respectively, Z T , Z P , Denote the damping matrices of the forward tugboat, stern pusher tugboat and barge, respectively, and F T 、F P They represent the drag force of the forward tugboat and the thrust of the stern tugboat, R T , R P are the configuration matrices of the forward tugboat and the stern pusher tugboat, τ T , τ P are the moments of the forward tugboat and the stern pusher tugboat on the barge, are the towing angles β of the forward tugboat and the stern pusher tugboat respectively T (t), β P (t) configuration matrix;

[0022] The barge position vector Barge towing angle α T (t) and the barge thrust angle α P (t) is the reference vector, and the position reference vectors of the forward tugboat and the stern pusher tugboat are expressed as:

[0023]

[0024]

[0025] Among them l T , l P are the distances from the barge's center of gravity to the barge's towing point and contact point, respectively, f is the distance between the tugboat and the barge, and are the distances from the center of gravity of the forward tugboat to its towing point and from the center of gravity of the stern pusher tugboat to its contact point, Q P (t), QT (t), T T (t), T p (t) is the transfer matrix, β P (t) is the thrust angle of the stern pusher.

[0026] Preferably, the step 2 is specifically:

[0027] Set the following prediction model:

[0028]

[0029] in is the pulling force on the barge, is the thrust on the barge, function f(·) is the kinematic and dynamic model of the ship, is the attitude and speed state of the barge, is the initial state of the barge;

[0030] Convert the position and speed information of the barge into control input to form a control space Substitute the control input of the input space into the prediction model for iteration to predict the moment of the barge in the future and form the state space The maximum tensile force and maximum elastic force of the rope, the barge towing angle and the maximum rate of change of the corresponding force are constrained to obtain a smooth reference trajectory of the barge; the moment that satisfies the constraints in the state space is substituted into the following optimization objective function:

[0031]

[0032] in represents the objective function of the barge, is the phase cost function, is the cost function;

[0033] The sequential quadratic programming algorithm is used to solve the optimal problem, find the sequence that minimizes the objective function, and obtain the pulling force and thrust required to operate the barge;

[0034] Drag angle β T (t) and thrust angle β P (t) can be determined by the heading angle ψ of the forward tugboat, stern pusher tugboat and barge. T (t),ψ P (t) And the drag and thrust angles of the barge are calculated:

[0035]

[0036]

[0037] Preferably, the step 3 is specifically:

[0038] Set the following prediction model:

[0039]

[0040] where ξ T (z), ξ P (z) is the attitude and speed state of the forward tugboat and the stern pusher tugboat, T is the sampling interval, ξ P0 , T0 is the initial state of the two ships;

[0041] The position and speed information of the forward tugboat and the stern pusher tugboat are converted into control inputs to form a control space Substitute the control input of the input space into the prediction model for iteration to predict the future forces and moments on the forward tugboat and the stern tugboat, forming the state space Substitute the moment in the state space into the following formula to optimize the objective function:

[0042]

[0043]

[0044] where h T (ξ(t),τ T (t)) represents the objective function of the forward tugboat, h P (ξ(t),τ P (t)) represents the objective function of the stern pusher; l T (ξ(t),τ(t)),l P (ξ(t),τ(t)) is the stage cost function of the two ships, L T (ξ(t)),L P (ξ(t)) is the terminal cost function of the two ships;

[0045] The sequential quadratic programming algorithm is used to solve the optimization problem and find the sequence that minimizes the objective function, that is, the optimal control torque of the tugboat. The current position and speed information of the tugboat and barge are calculated through the comprehensive dynamic model. The current position and speed information of the tugboat and barge are input, and the model estimation error is calculated. The model prediction error is used to make the error less than the set value, and the model prediction value is corrected to obtain the predicted value of the future output, which is transmitted to the central control system, and the central control system guides the two tugboats to control the barge to enter the specified position.

[0046] The beneficial effects of the present invention are as follows:

[0047] (1) Based on the dual tugboat towing dynamics model, the present invention considers the force applied by the physical cable, the elasticity of the rubber fender, and environmental interference factors such as wind and wave forces in turbulent sea conditions, so that the unmanned tugboat can accurately control the barge in a complex environment;

[0048] (2) The present invention decomposes the tug-pushing task into the force planning of the barge and the trajectory tracking of the tugboat, effectively solving the complex multi-vessel coordinated operation problem. According to the specified speed and position, an optimal force allocation method is used to allocate the desired force, and the required traction force and traction angle are planned for the barge, effectively solving the complex multi-vessel coordinated operation problem.

[0049] (3) The present invention proposes a novel collaborative model predictive control strategy, which can quickly control the barge to reach the specified location while maintaining the expected heading and speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a motion relationship diagram of the unmanned boat tugboat and barge of the present invention;

[0051] Figure 2 This is a diagram for explaining the centralized control framework of the present invention;

[0052] Figure 3 It is a schematic diagram of the trajectory of the unmanned boat tugboat towing and propelling the barge in the experimental example of the present invention;

[0053] Figure 4 It is a schematic diagram of the force results of the barge in the experimental example of the present invention;

[0054] Figure 5 Schematic diagram of the barge towing angle result in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0056] The present invention develops a dual unmanned boat tugboat towing and maneuvering system based on precise dynamic modeling, optimal force distribution and rapid collaborative control strategy.

[0057] (1) Based on the processing of environmental detection information, a comprehensive dynamic model of the towing and maneuvering system is established through force analysis. The model includes two operation modes: pushing by a pusher ship and towing by a tugboat. The barge displacement is achieved through the coordination of towing and pushing by two ships.

[0058] Based on the double tugboat towing dynamics model, the environmental interference factors such as the force exerted by the physical cable, the elasticity of the rubber fender, and the wind and wave forces in turbulent sea conditions are taken into account, so that the unmanned boat tugboat can accurately control the barge in a complex environment.

[0059] (2) according to the specified speed and position, a rolling optimal force distribution method is used to distribute the desired force and plan the required traction force and traction angle for the barge;

[0060] According to the moving target of the barge, the objective function is designed, constraints are added, the position and posture of the barge are predicted, and the sequential quadratic programming algorithm is used to solve the optimal problem, and the target drag and thrust that minimize the objective function are found. The results are transmitted to the upper overall controller, such as Figure 1 As shown, the expected position information and pulling force and thrust are transmitted to the tugboat controller via the upper overall controller, and the actions of the two tugboats are controlled by the tugboat controller. The data is continuously updated according to the changes in the position of the barge, and the barge is controlled to arrive along the expected path.

[0061] (3) The towing problem is converted into a tugboat trajectory tracking problem, and a new collaborative model predictive control strategy is proposed to quickly control the barge to the designated location.

[0062] According to the kinematic and dynamic models of the unmanned boat, a predictive control method is designed to set the input state space of the position, speed, angle, etc. of the two tugboats. The control quantity of the input space is input into the predictive control model and iterated to predict the position and posture state of the forward tugboat and the stern pusher tugboat to form a state space.

[0063] The posture state in the state space is substituted into the optimization objective function, and the sequential quadratic programming algorithm is used to solve the optimal problem. The controlled variable that minimizes the objective function is found and passed to the controllers of the two tugboats. The tugboat controller transmits the position and speed information to the two tugboats to guide the barge into the predetermined position.

[0064] Example:

[0065] like Figure 2 As shown, taking two unmanned boat tugboats towing an unpowered barge sideways as an example, the specific implementation steps of the present invention are unfolded, and the implementation method of the scheme of the present invention is described in detail in conjunction with the accompanying drawings.

[0066] The present invention proposes a dual unmanned boat tugboat towing and control system based on precise dynamic modeling, optimal force distribution and rapid collaborative control strategy. The method includes three major steps.

[0067] Step 1: Collect the tonnage, speed, position information and other environmental interference forces of the tugboat and barge, establish the dynamic and kinematic models of the towing control system, and calculate the reference trajectories of the barge and tugboat.

[0068] Step 2: According to the specified speed and position, the required traction force and traction angle are planned for the barge, and the reference trajectory values ​​such as the position and heading of the two unmanned boat tugboats are calculated through geometric analysis.

[0069] Step 3: According to the traction force on the barge, calculate the control force that the tugboat needs to exert, and control the unmanned boat tugboat to track the reference trajectory.

[0070] The final solution of the tugboat and barge motion trajectories in this embodiment is as follows: Figure 3 As shown in the figure, the force and traction angle changes during the barge movement are as follows: Figure 4 , Figure 5 shown.

[0071] The present invention takes into account environmental interference factors such as the force exerted by physical cables, the elasticity of rubber fenders, and wind and wave forces in turbulent sea conditions on the basis of a dual-tugboat towing and pushing dynamics model, so that the unmanned tugboat can accurately control the barge in a complex environment; the towing and pushing task is decomposed into barge force planning and tugboat trajectory tracking, effectively solving the complex multi-ship collaborative operation problem; an optimal force distribution method is used to distribute the desired force, and the required traction force and traction angle are planned for the barge; and a new collaborative model predictive control strategy is designed to manipulate the unmanned boat tugboat to quickly control the barge to reach the specified position.

Claims

1. A dual unmanned boat towing control method based on optimal force distribution and coordinated control strategy, characterized in that: The steps include: Step 1: Establish a comprehensive dynamic model of the unmanned tugboat autonomously maneuvering barge system; Step 2: Construct the real-time dynamic allocation method of the optimal maneuvering force of the barge; Step 3: Construct a predictive control strategy for the dual tugboat collaborative model.

2. The dual unmanned boat towing control method based on optimal force distribution and coordinated control strategy according to claim 1 is characterized in that: The step 1 is specifically as follows: Using the catenary model, the horizontal tension F of the towing cable is calculated. T ; Rubber fenders are installed around the tugboat to cushion the impact of the collision between the tugboat and the barge during propulsion. The elastic potential energy of the rubber is calculated based on the force transmission relationship to obtain the deformation of the rubber, and the thrust F of the barge is obtained through the empirical formula. P ; The Fossen wind-wave disturbance model is introduced to obtain the moment τ of wind and surge on the system. wind , τ wave ; The speed and position information of the forward tugboat, the stern pusher tugboat and the barge are taken as reference quantities, that is, v T 、v P , and η T , η P , The force analysis of the ship is carried out and the dynamic model of the barge is established as follows: The dynamic model of the forward tugboat is as follows: The dynamic model of the stern pusher tugboat is as follows: Among them, M T 、M P , are the mass matrices of the forward tugboat, stern pusher tugboat and barge, respectively, O T , O P , are the Coriolis-centripetal matrices of the forward tugboat, the stern pusher tugboat and the barge, respectively, Z T , Z P , Denote the damping matrices of the forward tugboat, stern pusher tugboat and barge, respectively, and F T 、F P They represent the drag force of the forward tugboat and the thrust of the stern tugboat, R T , R P are the configuration matrices of the forward tugboat and the stern pusher tugboat, τ T , τ P are the moments of the forward tugboat and the stern pusher tugboat on the barge, are the towing angles β of the forward tugboat and the stern pusher tugboat respectively T (t), β P (t) configuration matrix; The barge position vector Barge towing angle α T (t) and the barge thrust angle α P (t) is the reference vector, and the position reference vectors of the forward tugboat and the stern pusher tugboat are expressed as: Among them l T , l P are the distances from the barge's center of gravity to the barge's towing point and contact point, respectively, f is the distance between the tugboat and the barge, and are the distances from the center of gravity of the forward tugboat to its towing point and from the center of gravity of the stern pusher tugboat to its contact point, Q P (t), Q T (t), T T (t), T p (t) is the transfer matrix, β P (t) is the thrust angle of the stern pusher.

3. The dual unmanned boat towing control method based on optimal force distribution and cooperative control strategy according to claim 2 is characterized in that: The step 2 is specifically as follows: Set the following prediction model: in is the pulling force on the barge, is the thrust on the barge, function f(·) is the kinematic and dynamic model of the ship, is the attitude and speed state of the barge, is the initial state of the barge; Convert the position and speed information of the barge into control input to form a control space Substitute the control input of the input space into the prediction model for iteration to predict the moment of the barge in the future and form the state space The maximum tensile force and maximum elastic force of the rope, the barge towing angle and the maximum rate of change of the corresponding force are constrained to obtain a smooth reference trajectory of the barge; the moment that satisfies the constraints in the state space is substituted into the following optimization objective function: in represents the objective function of the barge, is the phase cost function, is the cost function; The sequential quadratic programming algorithm is used to solve the optimal problem, find the sequence that minimizes the objective function, and obtain the pulling force and thrust required to operate the barge; Drag angle β T (t) and thrust angle β P (t) can be determined by the heading angle ψ of the forward tugboat, stern pusher tugboat and barge. T (t),ψ P (t) And the drag and thrust angles of the barge are calculated:

4. The dual unmanned boat towing control method based on optimal force distribution and cooperative control strategy according to claim 3 is characterized in that: The step 3 is specifically as follows: Set the following prediction model: where ξ T (z), ξ P (z) is the attitude and speed state of the forward tugboat and the stern pusher tugboat, T is the sampling interval, ξ P0 , T0 is the initial state of the two ships; The position and speed information of the forward tugboat and the stern pusher tugboat are converted into control inputs to form a control space Substitute the control input of the input space into the prediction model for iteration to predict the future forces and moments on the forward tugboat and the stern tugboat, forming the state space Substitute the moment in the state space into the following formula to optimize the objective function: where h T (ξ(t),τ T (t)) represents the objective function of the forward tugboat, h P (ξ(t),τ P (t)) represents the objective function of the stern pusher; l T (ξ(t),τ(t)),l P (ξ(t),τ(t)) is the stage cost function of the two ships, L T (ξ(t)),L P (ξ(t)) is the terminal cost function of the two ships; The sequential quadratic programming algorithm is used to solve the optimization problem and find the sequence that minimizes the objective function, that is, the optimal control torque of the tugboat. The current position and speed information of the tugboat and barge are calculated through the comprehensive dynamic model. The current position and speed information of the tugboat and barge are input, and the model estimation error is calculated. The model prediction error is used to make the error less than the set value, and the model prediction value is corrected to obtain the predicted value of the future output, which is transmitted to the central control system, and the central control system guides the two tugboats to control the barge to enter the specified position.

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