A power buoy self-positioning control method based on an MPC algorithm and a power buoy

Abstract

The present application relates to the technical field of power buoy, in particular to a power buoy self-positioning control method based on MPC algorithm and a power buoy. First, the kinematic model of the buoy is established and converted into a continuous state space model, then the continuous time system equation is established according to the kinematic model, then the continuous state space model is discretized, then the state transition matrix and the input influence matrix in the continuous state space model are discretized according to the continuous time system equation, then the objective function is established, and the control parameters in the kinematic model are constrained, finally the optimal solution of the objective function is solved in the constraint range by using the linear quadratic programming function, the optimal control parameters are obtained, and the optimal positioning and navigation control are realized. The present application is equipped with a positioning control system and a power propulsion system, can quickly and autonomously adjust the attitude and position of the buoy itself, and greatly improves the adaptability and flexibility of the buoy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power buoys, in particular to a power buoy self-positioning control method based on an MPC algorithm and a power buoy. BACKGROUND

[0002] As a navigation mark floating on the water, the buoy is widely used, and is usually set in a place where it is difficult or inappropriate to set a fixed navigation mark. Its function is to mark the shoal or obstacle that endangers navigation safety. The buoy equipped with a lamp is called a light buoy, which is used for navigation in day and night navigation areas as a signal buoy.

[0003] However, the traditional buoy is a fixed buoy, that is, it is anchored at a specified position and cannot be adjusted in position according to user needs. After the installation of the buoy is completed, the process of secondary movement is relatively cumbersome, and the cost of secondary movement is high, which is not suitable for application in dynamic environments or situations where the position needs to be frequently adjusted, and the flexibility is poor. At the same time, most of the traditional buoys are fixed by anchor chains, and the positioning accuracy is easily affected by natural conditions such as water flow and wind force. In particular, in deep water or strong current areas, the fixed position of the buoy will deviate, and the positioning accuracy is low. Therefore, in view of the above problems, it is necessary to design a power buoy capable of realizing self-positioning function and a control method for self-positioning of the power buoy. SUMMARY

[0004] The purpose of the present application is to provide a power buoy self-positioning control method based on an MPC algorithm and a power buoy to solve the problems in the prior art that the traditional buoy cannot be flexibly adjusted in position according to user needs, is not suitable for application in dynamic environments or situations where the position needs to be frequently adjusted, and has poor flexibility, and the positioning accuracy of the buoy is easily affected by natural conditions such as water flow and wind force, and the positioning accuracy is low.

[0005] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0006] A power buoy self-positioning control method based on an MPC algorithm comprises the following steps:

[0007] Step 1: Establish a kinematic model of the buoy and convert it into a continuous state space model.

[0008] Step 2: Establish a continuous-time system equation according to the kinematic model.

[0009] Step 3: Discretize the continuous state space model.

[0010] Step 4: Discretize the state transition matrix and input influence matrix in the continuous state space model according to the continuous-time system equation.

[0011] Step five, establish the objective function and constraint the control parameters in the kinematic model.

[0012] Step six, solve the optimal solution of the objective function in the constraint range by using the linear quadratic programming function, obtain the optimal control parameters, and realize the optimal positioning and navigation control.

[0013] Further, in the step one, the kinematic model of the buoy is:

[0014]

[0015] The kinematic model of the buoy is converted into a continuous state space model as follows:

[0016]

[0017] The state space thereof is:

[0018]

[0019] wherein, is the longitude of the buoy, is the latitude of the buoy, is the heading of the buoy, is the angular velocity of the buoy in the sky, is the angular acceleration of the buoy in the sky, is the surge velocity of the buoy, is the surge acceleration of the buoy, is the sway velocity of the buoy, is the sway acceleration of the buoy.

[0020] The input variable is:

[0021]

[0022] wherein, is the thrust of the th propeller.

[0023] Further, in the step two, the continuous time system equation is established as:

[0024]

[0025] Further, in the step three, the discrete form of the continuous state space model is:

[0026]

[0027] wherein, is a state transition matrix, is an input influence matrix.

[0028] Further, in the step four, the discretization equation of the state transition matrix is:

[0029]

[0030] The discretization equation of the input influence matrix is:

[0031]

[0032] Further, in the step five, the objective function is:

[0033]

[0034] wherein,

[0035]

[0036] wherein, is a state error weight matrix, is a control input weight matrix.

[0037] The constraint condition is established as:

[0038]

[0039] wherein, is a longitude minimum value, is a longitude maximum value, is a latitude minimum value, is a latitude maximum value, is a surge speed minimum value, is a surge speed maximum value, is a sway speed minimum value, is a sway speed maximum value, is a heading angle speed minimum value, is a heading angle speed maximum value, is a thruster thrust minimum value, is a thruster thrust maximum value.

[0040] A dynamic buoy controlled by the above control method, comprising a main float, an auxiliary float and an autopilot for controlling dynamic positioning and planning navigation of the buoy, four thrusters are fixedly arranged on the bottom of the main float at intervals of 90° along the center of the buoy, and the thrusters are electrically connected with the autopilot;

[0041] The autopilot comprises a longitude measuring device, a latitude measuring device, a heading measuring device, a surge speed measuring device and a sway speed A dual-antenna GNSS attitude measurement system for measuring the buoy's angular velocity in the sky. oscillation acceleration and sway acceleration The MEMS inertial measurement unit, the communication module for data transmission between the buoy and the host computer, and the lithium iron phosphate battery pack.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] This invention incorporates an autopilot and four spaced-apart thrusters at the bottom of the buoy. Through a dual-antenna GNSS attitude measurement system and a MEMS inertial measurement unit, it acquires the buoy's position and attitude in real time. Simultaneously, it automatically adjusts the thrust and direction of the thrusters based on the acquired real-time data to ensure the buoy's stability and positioning accuracy. This invention is equipped with a positioning control system and a propulsion system. By adjusting the thrust and direction of each thruster, the buoy can achieve precise motion control in different directions, enabling translational movement in any direction. Under complex external conditions, the buoy can quickly respond to environmental changes and adjust its attitude and position, greatly improving its adaptability and flexibility. Attached Figure Description

[0044] Fig. 1 A schematic diagram of the overall structure of a powered buoy provided by the present invention;

[0045] Fig. 2 A bottom view of a powered buoy provided by the present invention.

[0046] The attached figures are labeled as follows:

[0047] 1. Main buoy; 2. Auxiliary buoy; 3. Autopilot; 4. Thruster. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0049] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to that other component.

[0050] It should be understood that the terms "length", "width", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate directions or positions based on the directions or positions shown in the drawings and are used for convenience in describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be construed as limiting the present application.

[0051] In addition, the terms "first", "second", "third", etc. are used only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined with "first", "second", etc. can explicitly or implicitly include one or more of the features.

[0052] For ease of understanding, please refer to Figs. 1-2 The embodiment provides a power buoy self-positioning control method based on an MPC algorithm and a power buoy, which comprises a main float 1, an auxiliary float 2 and an autopilot 3. The main float 1 is a ring-shaped hollow structure, which is used for providing buoyancy for the whole buoy to support the whole buoy to float above the sea surface. The auxiliary float 2 is fixedly connected to the upper portion of the main float 1 and is a spherical hollow structure, which is used for assisting the main float 1 to support the whole buoy to float above the sea surface, and the spherical structure of the auxiliary float 2 is convenient for workers to determine the position of the buoy. The autopilot 3 is fixedly connected to the middle portion of the main float 1. The autopilot 3 can be regarded as a controller of the whole buoy, and a power buoy self-positioning control method based on an MPC algorithm is used to control the dynamic positioning and planning navigation of the buoy. The power buoy self-positioning control method comprises a double-antenna GNSS attitude measurement system, a MEMS inertial measurement assembly, a communication module and a lithium iron phosphate battery pack. The double-antenna GNSS attitude measurement system is used to measure the longitude , latitude , heading , surge speed and sway speed of the buoy. The MEMS inertial measurement assembly is used to measure the angular velocity , surge acceleration and sway acceleration The communication module is used for receiving control instructions of the upper computer and feeding back the state information of the buoy to the upper computer, so as to realize the data transmission function between the buoy and the upper computer. The lithium iron phosphate battery pack is used to provide power supply for the electronic components installed on the buoy, and the lithium iron phosphate battery pack includes a lithium iron phosphate rechargeable battery and a solar panel, so as to support long-term self-power supply and self-operation of the buoy. The volume of the auxiliary floating body is greater than that of the main floating body, so that the buoy center of buoyancy is higher than the center of gravity, so as to realize the function of automatic resetting after the buoy is tilted. Four direct-current brushless thrusters 4 are fixed at the bottom of the main floating body 1 along the center of the buoy at intervals of 90°, and the four thrusters 4 are marked as T1, T2, T3 and T4 respectively. The thrusters 4 are electrically connected with the autopilot 3. Further, the double-antenna GNSS attitude measurement system includes a helical satellite antenna, which is especially suitable for the application scene of double-antenna attitude measurement at sea due to its special polarization mode and high sensitivity characteristics.

[0053] The power buoy self-positioning control method based on the MPC algorithm includes:

[0054] Step one, establish the kinematic model of the buoy and convert it into a continuous state space model.

[0055] The kinematic model of the buoy is:

[0056]

[0057] wherein, is the mass of the buoy, is the position vector of the buoy, is the drag coefficient, is the thrust of the th thruster, is the moment of inertia of the buoy, is the diameter of the buoy (i.e. the distance between the two thrusters 4 located at the diagonal positions respectively).

[0058] The kinematic model of the buoy is converted into a continuous state space model, and the continuous state space model of the buoy is:

[0059]

[0060] The state space is:

[0061]

[0062] wherein, is the longitude of the buoy, is the latitude of the buoy, is the heading of the buoy, is the angular velocity of the buoy, is the angular acceleration of the buoy, surge velocity of the buoy, surge acceleration of the buoy, sway velocity of the buoy, sway acceleration of the buoy.

[0063] The input variable of the system is the thrust of the four thrusters 4 fixedly installed at the bottom of the buoy, i.e. the input variable is:

[0064]

[0065] Under the condition of dynamic positioning of the buoy, the relationship between the thrust of the thrusters 4 and the rotating speed of the propellers of the thrusters 4 can be linearly approximated by a coefficient, i.e. .

[0066] Then

[0067]

[0068] wherein, is the input control vector, is the rotating speed of the propeller of the i-th thruster. Step two, establish the continuous-time system equation according to the kinematic model.

[0069] The continuous-time system equation established according to the kinematic model is:

[0070]

[0071] Step three, discretize the continuous state space model.

[0072] After discretizing the continuous state space model, we obtain:

[0073]

[0074] wherein,

[0075] is the state transition matrix, is the input influence matrix. Step four, discretize the state transition matrix and the input influence matrix according to the continuous-time system equation.

[0076] According to the continuous-time system equation, the state transition matrix A is discretized by the zero-order holder method, and we obtain:

[0077]

[0078] Similarly, according to the continuous-time system equation, the input influence matrix B is discretized by the zero-order holder method, and we obtain:

[0079] ​​After discretization, we get:

[0080]

[0081] where, is the installation angle of the thruster, is the distance between the left and right thrusters, is the distance between the front and back thrusters.

[0082] Step five, establish the objective function and constrain the parameters of the buoy in the kinematic model.

[0083] Based on the control objectives of the optimal track, heading error, and minimum energy consumption, the control objective function is established as:

[0084]

[0085] where,

[0086]

[0087] where, is the state error weight matrix, is the control input weight matrix.

[0088] The longitude, latitude, surge velocity, sway velocity, angular velocity, and thruster thrust of the buoy in the kinematic model are constrained, i.e., the constraint conditions are established as:

[0089]

[0090] where, is the minimum longitude, is the maximum longitude, is the minimum latitude, is the maximum latitude, is the minimum surge velocity, is the maximum surge velocity, is the minimum sway velocity, is the maximum sway velocity, is the minimum angular velocity, is the maximum angular velocity, is the minimum thruster thrust, is the maximum thruster thrust.

[0091] Step six, use linear quadratic programming function to solve the optimal solution of the objective function within the constraint range, get the optimal control parameters, and realize the optimal positioning and navigation control.

[0092] The objective function J is a quadratic function, the constraint condition is a linear constraint condition, and a linear quadratic programming (LQP) function is used to solve the optimal solution of the objective function J within the constraint range of the constraint condition That is, the state vector and the target value and the sequence of control quantities are brought into the objective function J, and the minimum value is solved, so as to obtain the thrust of each thruster 4 , which is converted into the rotation speed of the corresponding propeller of each thruster 4 , and the control quantity is fed back and output to adjust the rotation speed of the corresponding propeller of the four thrusters T1, T2, T3 and T4, so as to realize optimal positioning and navigation control.

[0093] The above process is repeated, and the dynamic positioning function of the buoy can be realized.

[0094] The present application can be used in the following aspects:

[0095] 1. Water sports:

[0096] Track marking: In sailing, racing, kayaking and other water competitions, the power buoy can be used to mark the competition route. Since the buoy can automatically maintain the predetermined position under the action of water flow and wind force, the accuracy and stability of the track marking are ensured, and the deviation problem easily occurring in traditional anchor buoy is effectively avoided.

[0097] Flexible adjustment: During the competition process, if it is necessary to adjust the racecourse according to weather or hydrological conditions, the dynamic positioning buoy can quickly move to a new position through the automatic pilot receiving the signal transmitted by the upper computer, thereby simplifying the work flow of racecourse adjustment.

[0098] 2. Ocean research:

[0099] Ocean observation: The power buoy can carry special loads and move to different positions according to the signal transmitted by the upper computer through the automatic pilot, and perform observation according to the plan.

[0100] Buoy array: A plurality of power buoys based on the power propulsion technology can form an accurate observation array to realize an observation network such as an acoustic long baseline array.

[0101] 3. Navigation and safety:

[0102] Channel identification: used to identify the channel or dangerous area, and provide high-precision position identification to ensure the safety of ship navigation.

[0103] Search and rescue: In an emergency, the power buoy can quickly reach the designated position through the automatic pilot receiving the signal transmitted by the upper computer, and provide rescue support or environmental monitoring.

[0104] 4. Anti-drowning in public bath

[0105] The power buoy can be equipped with intelligent cameras, searchlights, megaphones, sound and light alarm devices, and automatic throwing devices, etc., and cruise in public bathing water areas to automatically or manually assist in identifying fallen or drowning persons and provide buoyancy support or call for rescue on site.

[0106] The power buoy equipped with the MPC self-positioning control algorithm provides high mobility, high position accuracy, high pointing accuracy, and high stability through an advanced propulsion system and control system, and has wide application potential in the fields of ocean observation, water sports, drowning prevention, environmental monitoring, emergency response, channel indication, navigation safety, etc.

[0107] Although the present application has been described with reference to the preferred embodiments thereof, it is to be understood that the application is not limited to the embodiments described and that modifications or additions can be made thereto without departing from the spirit of the application.

Claims

1. A self-positioning control method for a powered buoy based on the MPC algorithm, characterized in that, Includes the following steps: Step 1: Establish the kinematic model of the buoy and convert it into a continuous state-space model; Step 2: Establish the continuous-time system equations based on the kinematic model; Step 3: Discretize the continuous state-space model; Step 4: Discretize the state transition matrix and input influence matrix in the continuous state-space model according to the continuous-time system equations; Step 5: Establish the objective function and constrain the control parameters in the kinematic model; Step 6: Solve the objective function using a linear quadratic programming function within the constraints to obtain the optimal control parameters and achieve optimal positioning and navigation control; In step one, four propellers are fixed at 90° intervals along the center circumference of the buoy at the bottom of the main buoy body. The kinematic model of the buoy is as follows: ； in, For the mass of the buoy, The buoy's position vector. The drag coefficient, For the first The thrust of each propeller Let the moment of inertia of the buoy be... The diameter of the buoy; The kinematic model of the buoy is converted into a continuous state-space model as follows: ； Its state space is: ； in, The longitude of the buoy. The latitude of the buoy. For the buoy's course, Let θ be the angular velocity of the buoy. Let θ be the angular acceleration of the buoy. Let be the sway speed of the buoy. The sway acceleration of the buoy. The sway speed of the buoy. The sway acceleration of the buoy; The input variables are: ； In step two, the equations for the continuous-time system are established as follows: ； in, The distance between the left and right thrusters. The distance between the front and rear thrusters. The mass of the buoy; In step three, the discrete form of the continuous state-space model is: ； in, It is the state transition matrix. It is the input influence matrix; In step four, the state transition matrix The discretization equation is: ； in, This is the drag coefficient; Input influence matrix The discretization equation is: ； in, For the installation angle of the thruster, The distance between the left and right thrusters. This represents the distance between the front and rear thrusters.

2. The self-positioning control method for a powered buoy based on the MPC algorithm according to claim 1, characterized in that, In step five, the objective function is: ； in, ； in, Here is the state error weight matrix. To control the input weight matrix; The constraints are as follows: ； in, The minimum longitude. The maximum longitude. The minimum latitude value, The maximum value of latitude. This represents the minimum oscillation velocity. The maximum oscillation velocity, This represents the minimum sway velocity. This represents the maximum sway speed. This represents the minimum angular velocity in the sky. This represents the maximum angular velocity in the sky. This is the minimum thrust of the thruster. This represents the maximum thrust of the thruster.

3. A powered buoy controlled by the control method described in claim 1, characterized in that, It includes a main float, an auxiliary float, and an autopilot for controlling the dynamic positioning and navigation planning of the buoy; the thrusters are electrically connected to the autopilot. The autopilot includes a device for measuring the longitude of the buoy. ,latitude ,course oscillation speed and sway speed A dual-antenna GNSS attitude measurement system for measuring the buoy's angular velocity in the sky. oscillation acceleration and sway acceleration The MEMS inertial measurement unit, the communication module for data transmission between the buoy and the host computer, and the lithium iron phosphate battery pack.

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