Method and system for controlling automatic landing of shipborne unmanned rotorcraft in specified deck area

Abstract

The invention discloses a control method and system for automatic landing of a shipborne unmanned rotorcraft in a specified deck area, and belongs to the technical field of automatic control of unmanned rotorcrafts. The method comprises the following steps: step 1, planning an ideal landing line of the unmanned rotorcraft based on the position of the unmanned rotorcraft and the position of a ship deck; step 2, obtaining a position error of the rotor unmanned aerial vehicle based on the ideal landing line; step 3, predicting the operation attitude of the ship to obtain a ship attitude prediction result; and step 4, generating a predicted ideal landing line of the unmanned rotorcraft based on the ship attitude prediction result, and performing trajectory tracking flight control on the unmanned rotorcraft based on the position error of the unmanned rotorcraft to complete automatic landing of the unmanned rotorcraft in the specified deck area. According to the invention, the automatic landing task of the shipborne unmanned rotorcraft in the designated area on the ship can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic control of rotary-wing UAVs, and in particular relates to a method and system for automatic landing control of a ship-borne rotary-wing UAV in a designated deck area. Background Art

[0002] As my country continues to advance its strategy of building a strong maritime nation, offshore platforms are playing an increasingly important role in military, scientific research, and rescue operations. Ship-borne rotary-wing drones, as efficient and flexible aerial platforms, provide three-dimensional airspace support for ships performing missions at sea, and have broad application prospects. However, the complex maritime environment and the significant impact of wind and waves on ship platforms have posed a pressing challenge: how to safely land rotary-wing drones on ship platforms.

[0003] Research on the coordinated control of ships and drones is relatively limited. For example, in their article "Several Key Technologies for Coordinated Autonomous Landing of UAVs / Submarines" published in Volume 61 (Supplement 1) of China Shipbuilding (August 2020), pages 156-162, Zhao Liangyu, Cheng Zhekun, Gao Fengjie, and Li Dan introduced guidance techniques based on airborne positioning and computer vision systems, as well as basic methods for estimating and compensating deck motion. However, they did not propose a detailed design method for the drone's posture control. Currently, no researchers have proposed a highly reliable control algorithm for the automated landing of shipborne rotorcraft drones in designated areas on a ship. Summary of the Invention

[0004] The present invention aims to address the deficiencies of the prior art and proposes a method for controlling the automatic landing of a shipborne rotary-wing UAV in a designated deck area, comprising the following steps:

[0005] Step 1: Plan the ideal landing route of the rotary-wing UAV based on the position of the rotary-wing UAV and the position of the ship deck;

[0006] Step 2: Based on the ideal landing path, obtain the position error of the rotary-wing UAV;

[0007] Step 3: Predict the ship's running attitude and obtain the ship's attitude prediction result;

[0008] Step 4: Generate a predicted ideal landing path for the rotorcraft drone based on the ship attitude prediction result, and perform trajectory tracking flight control on the rotorcraft drone based on the position error of the rotorcraft drone to complete automatic landing of the rotorcraft drone in the designated deck area.

[0009] Further preferably, the position error includes: a position error in the tracking descent phase and a position error in the vertical landing phase;

[0010] For a rotorcraft in the world coordinate system, the coordinates are ,The calculation method of the position error in the tracking descent phase includes:

[0011] ;

[0012] ;

[0013] ;

[0014] ;

[0015] Where, Indicates the coordinates of the tracking target point of the rotary-wing UAV in the world coordinate system; Indicates the coordinates of the floating point in the world coordinate system; The starting position of the rotorcraft in the coordinate system Axis coordinates, is the desired landing rate of the UAV, is the time interval from the start of landing to the current moment, 、 They represent the ideal landing path and Plane angle and Plane angle; is the lateral deviation; is the longitudinal deviation; is the vertical deviation;

[0016] The calculation method of the position error during the vertical landing phase includes:

[0017] When the rotor UAV is in the ideal landing area, the tracking target point of the rotor UAV is the origin of the landing coordinate system. The world coordinate system of the origin of the landing coordinate system is , the lateral deviation is: , the longitudinal deviation is: , the vertical deviation is: .

[0018] Further preferably, in step three, the KOA-LSTM model is used to predict the motion posture of the ship;

[0019] Prediction methods include:

[0020] S31, collecting actual ship data, and preprocessing the actual ship data to obtain ship attitude data;

[0021] S32. Initialize KOA parameters: number of planets , maximum number of iterations Tmax, hyperparameters: learning rate, upper and lower bounds of the number of neurons, control parameters 、 、 ;in, represents the gravitational constant; represents the distance attenuation coefficient; represents the orbital period;

[0022] S33, initializing the parameters in step S32 using random positions, orbital eccentricities, and orbital periods, and evaluating the fitness value of the initial population;

[0023] S34. Mark the global optimal solution as the position of the sun and obtain the current hyperparameters;

[0024] S35. Calculate the Euclidean distances and gravitational forces between the Sun and all celestial bodies, and calculate the velocities of all celestial bodies;

[0025] S36. Update the distance between the object and the sun or the new position of the object;

[0026] S37. Calculate and compare the fitness values ​​of all celestial bodies and the sun, and update the global optimal solution;

[0027] S38. After the iteration, save the global optimal solution, which is the optimal parameter of the LSTM network;

[0028] S39. Input the ship attitude data into the LSTM network with optimal parameters to obtain the ship attitude prediction result.

[0029] Further preferably, in step 4, the method of trajectory tracking flight control includes: performing trajectory tracking flight control on the rotary wing UAV using a closed-loop controller;

[0030] The input of the closed-loop controller is the desired position and the desired yaw angle , the position controller passes the desired position in the world coordinate system , actual location and actual speed Get the expected pulling force in the body coordinate system , desired roll angle and the desired pitch angle , the desired pitch angle , desired roll angle , desired yaw angle And the actual Euler angles and the actual body angular velocity Input to the attitude controller to obtain the desired three-axis torque ; Control the dispenser according to the desired pulling force , desired three-axis torque Get the desired speed ; The motor controller adjusts the speed according to the desired Generate the desired throttle command .

[0031] Further preferably, the design method of the posture controller includes: angle loop design and angular velocity loop design;

[0032] Methods for angle ring design include:

[0033] ;

[0034] Expand to get:

[0035] ;

[0036] Where, Indicates the output of the desired angular velocity in the body coordinate system; The proportional gain representing the angle error; Indicates the angle error; 、 、 Respectively represent the 、 、 Angular velocity in the roll, pitch, and yaw directions; 、 、 They are roll angle, pitch angle, and yaw angle respectively; 、 、 Respectively represent the angle 、 、 Proportional gain coefficients in the three directions of the axis;

[0037] Methods for angular velocity loop design include:

[0038] ;

[0039] in,

[0040] ;

[0041] Where, Indicates the integral gain of angular velocity error; Represents the differential gain of angular velocity error; represents the angular velocity error; Indicates the actual angular velocity of the input; represents the derivative of the angular velocity error.

[0042] Further preferably, the design method of the position controller includes: a horizontal channel controller and a height channel controller;

[0043] The horizontal channel controller includes a position loop design and a speed loop design;

[0044] The method for designing the position loop includes:

[0045] ;

[0046] Where, Indicates the expected horizontal velocity of the output; Respectively 、 Proportional gain coefficient of direction;

[0047] The method for designing the speed loop includes:

[0048] ;

[0049] get ,in , ;

[0050] Then we get:

[0051] ;

[0052] in, ;

[0053] ;

[0054] Where, express direction of the acceleration vector; Indicates the mass of the rotary wing UAV; Indicates the lift of the UAV in equilibrium state in the body coordinate system; represents the gravitational constant; express The desired acceleration vector in the direction; represents the proportional gain of the horizontal velocity error; Indicates the integral gain of the horizontal velocity error; represents the differential gain of the horizontal velocity error; Indicates horizontal velocity error; superscript -1 indicates inversion operation; superscript Represents the transpose of a matrix; represents the derivative of the horizontal velocity error;

[0055] The altitude channel controller includes: altitude loop design and altitude speed loop design;

[0056] The height ring design method includes:

[0057] ;

[0058] Where, Indicates the expected vertical speed of the output; Represents the proportional gain of the error in the vertical direction;

[0059] The method for designing the altitude speed loop includes:

[0060] ;

[0061] Depend on replace get:

[0062] ;

[0063] ;

[0064] Where, express Acceleration in the axial direction; 、 、 They represent the proportional gain of the velocity error in the vertical direction, the integral gain of the velocity error in the vertical direction, and the differential gain of the velocity error in the vertical direction respectively; Indicates the velocity error in the vertical direction; express The derivative of Rotary wing drone The acceleration in the direction of the axis.

[0065] The present invention also provides a shipborne rotary-wing UAV designated deck area automatic landing control system, comprising:

[0066] Trajectory planning module, used to plan the ideal landing path of the rotary-wing UAV based on the position of the rotary-wing UAV and the position of the ship deck;

[0067] an error calculation module, configured to obtain a position error of the rotary-wing UAV based on the ideal landing path;

[0068] The ship attitude prediction module is used to predict the ship's operating attitude and obtain the ship attitude prediction result;

[0069] The landing control module is used to generate a predicted ideal landing path for the rotor UAV based on the ship attitude prediction result, and to perform trajectory tracking flight control on the rotor UAV based on the position error of the rotor UAV to complete the automatic landing of the rotor UAV in the designated deck area.

[0070] Compared with the prior art, the present invention has the following beneficial effects:

[0071] This invention utilizes the KOA-LSTM model to predict the ship's motion, proactively understanding the ship's dynamic trends and effectively compensating for the ship's six-degree-of-freedom motion. This significantly improves the landing reliability of drones in windy and choppy conditions. Furthermore, this invention proposes a two-stage position error calculation method (descent phase and vertical landing phase). By specifically correcting lateral, longitudinal, and vertical position deviations, this method achieves more refined control, mitigates stability issues associated with unified control throughout the entire process, and enhances landing safety. Furthermore, this invention provides a mechanism for determining go-around conditions, further improving landing safety and fault tolerance. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0073] Figure 1 Schematic diagram of the relevant coordinate system in an embodiment of the present invention;

[0074] Figure 2 : The ideal landing route diagram of the rotary-wing UAV in an embodiment of the present invention; wherein (a) is a side view of the ideal landing route of the rotary-wing UAV; (b) is a top view of the ideal landing route of the rotary-wing UAV;

[0075] Figure 3 This is a schematic diagram of the position error calculation principle of the rotary-wing UAV in an embodiment of the present invention;

[0076] Figure 4 This is a flow chart of the KOA-LSTM prediction method in an embodiment of the present invention;

[0077] Figure 5 This is a diagram showing the roll prediction effect in an embodiment of the present invention;

[0078] Figure 6 This is a pitch prediction effect diagram in an embodiment of the present invention;

[0079] Figure 7 This is a heave prediction effect diagram in an embodiment of the present invention;

[0080] Figure 8 This is a schematic diagram of the closed-loop controller structure of a rotary-wing UAV in an embodiment of the present invention;

[0081] Figure 9 This is a structural diagram of a digital simulation system in an embodiment of the present invention;

[0082] Figure 10Schematic diagrams of the heave, pitch, and roll curves of a ship under the simulated working conditions in an embodiment of the present invention; wherein (a) is a schematic diagram of the heave curve; (b) is a schematic diagram of the pitch curve; and (c) is a schematic diagram of the roll curve;

[0083] Figure 11 Schematic diagram of the longitudinal deviation curve of a rotary-wing UAV under simulated working conditions in an embodiment of the present invention;

[0084] Figure 12 Schematic diagram of the lateral deviation curve of a rotary-wing UAV under simulated working conditions in an embodiment of the present invention;

[0085] Figure 13 Schematic diagram of the yaw angle curve of a rotary-wing UAV under simulated working conditions in an embodiment of the present invention;

[0086] Figure 14 Schematic diagram of a pitch angle curve of a rotary-wing UAV under simulated working conditions in an embodiment of the present invention;

[0087] Figure 15 Schematic diagram of a roll angle curve of a rotary-wing UAV under simulated working conditions in an embodiment of the present invention;

[0088] Figure 16 Schematic diagram of the heave, pitch, and roll curves of a ship under the second simulation working condition in an embodiment of the present invention; wherein (a) is a schematic diagram of the heave curve; (b) is a schematic diagram of the pitch curve; and (c) is a schematic diagram of the roll curve;

[0089] Figure 17 Schematic diagram of the longitudinal deviation curve of the lower rotor UAV under the second simulation working condition in an embodiment of the present invention;

[0090] Figure 18 Schematic diagram of the lateral deviation curve of the lower rotor UAV under the second simulation working condition in an embodiment of the present invention;

[0091] Figure 19 Schematic diagram of the yaw angle curve of the lower rotor UAV under the simulated working condition II in an embodiment of the present invention;

[0092] Figure 20 Schematic diagram of the pitch angle curve of the lower rotor UAV under the simulated working condition 2 in an embodiment of the present invention;

[0093] Figure 21 Schematic diagram of the roll angle curve of the rotor UAV under the second simulation working condition in an embodiment of the present invention. DETAILED DESCRIPTION

[0094] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0095] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0096] First, the relevant coordinate system is explained. Figure 1 As shown, it includes: world coordinate system, ship body coordinate system, landing coordinate system, and involved world coordinate system.

[0097] (1) World coordinate system :

[0098] The origin of the world coordinate system is located at a certain point on the earth. The positive direction of the axis points to the north. The positive direction of the axis points to the east. The positive direction of the axis is perpendicular to the sea level and points downward.

[0099] (2) Ship body coordinate system :

[0100] The origin of the ship's coordinate system is located at the ship's swing center. The positive direction of the axis points to the bow, The positive direction of the axis points to the starboard side of the ship. The positive direction of the axis is perpendicular to the deck and points towards the seabed.

[0101] (3) Landing coordinate system :

[0102] The origin of the landing coordinate system is located at the geometric center of the rectangular landing area. The positive direction of the axis points to the bow, The positive direction of the axis points to the starboard side of the ship. The positive direction of the axis is perpendicular to the deck and points towards the seabed.

[0103] (4) Involving the world coordinate system :

[0104] origin The point at a certain distance above the origin of the landing coordinate system is the horizontal floating point. Figure 2 The directions of the three coordinate axes in the ideal landing path of the aircraft are consistent with the directions of the three coordinate axes in the world coordinate system.

[0105] (5) Body coordinate system :

[0106] The origin of the rotorcraft coordinate system Set at the center of mass of the drone. The positive direction of the axis points to the nose of the drone, that is, directly in front of the drone; The positive direction of the axis points to the right side of the drone; The positive direction of the axis is vertically downward, pointing to the ground.

[0107] Example 1:

[0108] Step 1: Plan the ideal landing route for the rotary-wing UAV based on the UAV and the ship deck.

[0109] In this embodiment, the landing area of ​​the rotor UAV is the upper surface of the rectangular parallelepiped on the ship deck. The ideal landing point of the ship-borne rotor UAV during the landing process is the geometric center of the upper surface of the rectangular parallelepiped. The UAV lands according to the preset glide angle. When the UAV descends to a certain height above the landing area, it lands vertically in the designated landing area to complete the recovery mission. The ideal landing route of the rotor UAV in this embodiment is as follows: Figure 2 (a) and Figure 2 (b)

[0110] like Figure 2 As shown in (b), during the landing process, the rotor UAV approaches the ideal landing point from the left rear of the ship, and descends vertically until it stops above the ideal landing point. Figure 2 In (a), this embodiment defines the ideal landing path and landing coordinate system Axis angle =30 degrees, Figure 2 In (b), this embodiment defines the angle between the ideal landing path and the horizontal plane as =45 degrees, distance above the ideal landing point = 5 meters. In addition, the present embodiment is designed to fly the rotor UAV to a position about 50 meters behind the tail of the ship and prepare for the landing mission.

[0111] Step 2: Calculate the position error of the rotorcraft based on the ideal landing path.

[0112] In this embodiment, the landing process of the rotary-wing UAV is divided into two stages according to the ideal landing path: the tracking descent stage and the vertical landing stage. The position error of the rotary-wing UAV is calculated in each stage. The calculation method is as follows:

[0113] Step 1: Position error calculation method during tracking descent phase.

[0114] In the descent phase of the rotor UAV tracking, in order to enable the rotor UAV to accurately track the ideal descent line, it is necessary to obtain the tracking points on the ideal descent line tracked by the rotor UAV in real time. The position error calculation principle of the rotor UAV during landing in this embodiment is as follows: Figure 3 As shown, the ideal landing route in this embodiment is expressed as , which is the same as The plane angle is ,and The plane angle is . Assume that the starting position of the rotor UAV is Point, whose coordinates in the implicate world coordinate system are The target point to be tracked always remains on the designed ideal glide path and moves at a constant rate. Decline. Figure 3 Point A in the middle. Let the coordinates of the floating point in the world coordinate system be , then the coordinates of point A in the world system are:

[0115] ; (1)

[0116] Where, Indicates the coordinates of the tracking target point of the rotary-wing UAV in the world coordinate system; is the desired landing rate of the UAV; is the time interval from the start of landing to the current moment; is the lateral deviation; is the longitudinal deviation; is the vertical deviation.

[0117] Assume that the coordinates of the rotorcraft in the world coordinate system are , then the lateral deviation is: , the longitudinal deviation is: , the vertical deviation is: .

[0118] Step 2: Position error calculation method during vertical landing phase.

[0119] Above the rotorcraft reaches the ideal landing point =5 meters, the following situations are classified and handled accordingly: If the lateral and longitudinal positions of the rotorcraft are not within the ideal landing area, the rotorcraft performs a go-around. If the lateral and longitudinal positions of the rotorcraft are within the ideal landing area, the rotorcraft is made to drop vertically into the recovery cabin to complete the landing operation.

[0120] If the UAV is in the ideal landing area, its tracking target point is the origin of the landing coordinate system, and the world coordinate system of the origin of the landing coordinate system is , then the lateral deviation is: , the longitudinal deviation is: , the vertical deviation is: .

[0121] Step 3: Predict the ship's motion posture and obtain the ship's posture prediction result.

[0122] Specifically, the KOA-LSTM model is used to predict the ship's motion posture. First, the actual ship data is collected, and the data on the roll, pitch, and heave motion posture of the actual ship are collected every 0.05 seconds. A total of 20,000 data points need to be collected, that is, 1,000 seconds of data. The collected data is then processed: the ship's motion posture is converted into an input-output data pair with a clear time correlation to form a supervised learning format suitable for LSTM neural network training. The design task of this embodiment is to use the data of the past 50 time steps to predict the ship's posture in the next 5 seconds, so each sample needs to contain posture data of 50 historical time steps and 100 future time steps. The posture data of the three types of motion are divided into training set, test set, and validation set according to the ratio of 6:2:2, and are standardized to eliminate the dimensional effect. Finally, the data is reconstructed into a three-dimensional structure including the number of samples, time steps, and number of features required by the LSTM network to obtain the ship's posture data.

[0123] When forecasting the time series of ship posture, the selection of hyperparameters plays a decisive role in the forecast accuracy of the LSTM network. This embodiment combines the Kepler Optimization Algorithm (KOA) with LSTM to construct a KOA-LSTM model. The structure of the KOA-LSTM model is as follows: Figure 4 The specific process is as follows:

[0124] S31. Prepare ship attitude data according to the above method, use the training set and validation set to train and validate the KOA-LSTM model, and use the test set to perform prediction test on the KOA-LSTM model.

[0125] S32. Initialize KOA parameters: number of planets , maximum number of iterations Tmax, upper and lower bounds of hyperparameters (learning rate, number of neurons), control parameters 、 、 .in, Represents the gravitational constant, which controls the update step size and convergence speed; Represents the distance attenuation coefficient, which is used to adjust the balance between exploration and convergence; Represents the orbit period, which is used to determine the flexibility and robustness of the search trajectory.

[0126] S33. Initialize the celestial body population with random positions, orbital eccentricities, and orbital periods (i.e., the parameters in step S32), and evaluate the fitness value of the initial population, using the root mean square error (RMSE) as the fitness function.

[0127] S34. Mark the global optimal solution as the position of the sun, that is, the current hyperparameter selection.

[0128] S35. Calculate the Euclidean distances and gravitational forces between the Sun and all celestial bodies, and calculate the velocities of all celestial bodies.

[0129] S36. Update the distance between the object and the sun or the new position of the object.

[0130] S37. Calculate, compare and evaluate the fitness values ​​of all celestial bodies and the sun, and update the global optimal solution.

[0131] S38. After the iteration, the global optimal solution is saved, which is the optimal parameter selection of the LSTM network.

[0132] S39. Input the ship attitude data into the LSTM network with optimal parameters to obtain the ship attitude prediction result.

[0133] like Figure 5 、 Figure 6 、 Figure 7 The following table shows the prediction results for the ship roll, pitch, and heave motion test data. The RMSE and MAE for roll prediction are 8.29% and 6.28% respectively; the RMSE and MAE for pitch prediction are 2.85% and 2.31% respectively; and the RMSE and MAE for heave prediction are 2.19% and 1.73% respectively.

[0134] Step 4: Generate a predicted ideal landing path for the rotorcraft drone based on the predicted state of the ship, and perform trajectory tracking flight control on the rotorcraft drone based on its position error to complete the automatic landing of the rotorcraft drone in the designated deck area.

[0135] In this embodiment, the flight control algorithm of the rotor UAV is mainly divided into two parts: position control and attitude control. The closed-loop controller structure of the rotor UAV is as follows: Figure 8 As shown in the overall block diagram of the closed-loop controller, the input given is the desired position and the desired yaw angle , the position controller passes the desired position in the world coordinate system , actual location and actual speed Find the expected pulling force in the body coordinate system , desired roll angle and the desired pitch angle ,Will 、 、 , the actual Euler angle and the actual body angular velocity Input to the attitude controller to obtain the desired three-axis torque . Control the dispenser according to the desired pulling force , desired three-axis torque Find the expected speed The motor controller controls the desired speed. Generate the desired throttle command .

[0136] In order to design a closed-loop controller, it is necessary to linearize it near the equilibrium point. When the rotor drone is hovering, since all states do not change, it is an equilibrium point. At this time, the Euler angle (except ) are close to 0, so: .in, Indicates the mass of the rotary wing UAV; represents the gravitational constant; Represents the body angular velocity and Euler angle conversion matrix; Represents the 3D identity matrix; 、 、 They are roll angle, pitch angle, and yaw angle respectively; It represents the lift of the UAV in the equilibrium state in the body coordinate system. Therefore, the following rotor UAV model can be established:

[0137] ; (2)

[0138] ; (3)

[0139] ; (4)

[0140] ; (5)

[0141] Where, express The derivative of Indicates the speed of the drone in the world coordinate system; Represents the acceleration of the drone in the world coordinate system; represents the Euler angular rate; Indicates the actual angular velocity of the input; It represents the total torque provided by the rotor in the body coordinate system; Represents the inertia matrix in the body coordinate system; Indicates the angular acceleration of the rotorcraft in the body coordinate system.

[0142] The attitude controller design method includes: in this embodiment, the attitude controller adopts cascade PID control, the outermost part is the PID for adjusting the angle, generally using P control, and the inner part is the PID control link for adjusting the angular velocity.

[0143] (1) Angle loop: The input is the angular error of the three Euler angles, and the output is the desired angular velocity in the body coordinate system. Table 1 shows the symbols for the angle loop.

[0144] Table 1 Angle ring symbol description

[0145]

[0146] In this embodiment, the angle loop adopts proportional control, as shown in the following formula:

[0147] . (6)

[0148] Expanding formula (6) into matrix form is:

[0149] ; (7)

[0150] Where, 、 、 Respectively represent the 、 、 Angular velocity in the roll, pitch, and yaw directions; 、 、 Respectively represent the angle 、 、 The proportional gain coefficients in the three axis directions reflect the angular error response capability in each direction.

[0151] (2) Angular velocity loop: The input is the desired angular velocity, and the output is the desired three-axis torque. Table 2 shows the symbols for the angular velocity loop.

[0152] Table 2 Symbols of angular velocity loop

[0153]

[0154] The angular velocity loop uses PID control, with the following formula:

[0155] ; (8)

[0156] Where, represents the derivative of the angular velocity error.

[0157] The design method of the position controller includes: the design of the position controller adopts cascade PID control, the outer loop controls the position and only adopts P control, and the inner loop controls the speed and adopts PID control.

[0158] According to the model of the rotary-wing UAV (i.e., formula (2)-formula (5)), it can be seen that and The dynamic equations of direction are related to the three Euler angles, and Axes do not contain Euler angles, so they are designed separately. and A set of controllers for direction, Direction independent design controller, and The direction controller is also called the horizontal channel controller. The direction controller is also called the altitude channel controller.

[0159] (1) Horizontal channel controller: The input is expected in the world coordinate system 、 The output is the desired roll angle and the desired pitch angle .

[0160] ① Position ring. Table 3 is the symbol description of the horizontal position ring.

[0161] The position loop adopts proportional control, and the formula is as follows:

[0162] ; (9)

[0163] Where, Respectively 、 Proportional gain coefficient of direction; is the desired horizontal velocity of the output.

[0164] ② Speed ​​loop. Table 3 shows the symbols for the horizontal speed loop.

[0165] Table 3 Symbols of horizontal velocity loop

[0166]

[0167] The horizontal velocity has the following relationship:

[0168] . (10)

[0169] make , have:

[0170] . (11)

[0171] so,

[0172] . (12)

[0173] Where, express direction of the acceleration vector; express The desired acceleration vector in the direction; the superscript -1 indicates the inversion operation.

[0174] The speed loop uses PID control, with the following formula:

[0175] ; (13)

[0176] Where, represents the derivative of the horizontal velocity error.

[0177] Then according to formula (12) we can get , that is, the desired roll angle and the desired pitch angle .

[0178] (2) Height channel controller: The height channel input is the desired vertical height, the actual vertical height and the actual vertical direction. The output of the axis direction speed is the expected pulling force of the drone.

[0179] ① Height ring design: Table 4 is the height ring symbol description.

[0180] Table 4 Altitude ring symbol description

[0181]

[0182] Similarly, the vertical position loop also uses proportional control, and the output of the position loop is the desired vertical speed. :

[0183] . (14)

[0184] ② Altitude speed loop design. Table 5 shows the symbols for the vertical speed loop.

[0185] Table 5 Symbols for vertical velocity loop

[0186]

[0187] The input is the desired vertical velocity, and the output is the desired pull:

[0188] ; (15)

[0189] Where, Rotary wing drone The acceleration in the direction of the axis.

[0190] When designing the controller, Replace with Then, the following formula is established:

[0191] ; (16)

[0192] ; (17)

[0193] Where, express The derivative of .

[0194] Through the above method, the design of position controller and attitude controller is completed.

[0195] Control the distributor according to the desired force output by the position controller And the desired torque output by the attitude controller Adjust the speed of each rotor of the drone .

[0196] The relationship between the UAV speed, force and torque is as follows:

[0197] ; (18)

[0198] Where, , , , is the rotation speed of different rotors, , , They are exist , , The component moment in the positive direction of the axis, is the lift coefficient of the rotor, is the vertical distance from the rotor centerline to the center of mass of the UAV, is the torque coefficient of the rotor.

[0199] The motor controller generates the motor throttle command according to the rotor speed output by the control distributor , where the motor model is as follows:

[0200] ; (19)

[0201] ; (20)

[0202] Where, is the steady-state speed of the motor, is the speed parameter, is the speed constant.

[0203] Can get throttle command The steady-state speed of the motor The relationship is:

[0204] ; (twenty one)

[0205] Thus we can get:

[0206] . (twenty two)

[0207] Example 2:

[0208] This embodiment designs a ship-borne rotor UAV automatic landing simulation system. The digital simulation system structure is as follows: Figure 9 As shown in the figure, the digital simulation system includes: aircraft motion module (UAV dynamics model, UAV kinematics model), ship motion module, prediction module, sea condition setting module, initial parameter setting module, guidance law module (inputs the ideal position of the UAV and the actual position of the UAV obtained by radar into the guidance law computer and outputs guidance instructions) and flight control module (autopilot instrument), etc.

[0209] The ship motion module includes the hull, waterjet module, wave module, wind module, flow module, viscous force module, and inertial force module. These modules drive the ship's motion by applying forces and torques to the hull, thereby outputting the ship's position, attitude, and six-degree-of-freedom state. Based on this information, the prediction module and coordinate transformation module generate the ship's ideal landing point and ideal landing path in the world coordinate system based on the state information from the ship motion module. The guidance law module converts the ideal landing point and ideal landing path into lateral, longitudinal, and vertical position deviations for the rotorcraft. The flight control algorithm calculates the aircraft's control variables based on these state deviations to eliminate the rotorcraft's tracking deviation.

[0210] Simulation condition 1: Level 4 sea condition, the ship speed is 6 knots, sailing into the waves, irregular waves are used to simulate waves, and the ship motion simulation curve is as follows Figure 10 (a) Figure 10 (b) Figure 10As shown in (c), the simulation diagram (heave, pitch, and roll) shows the typical 6-DOF motion characteristics of a ship under the action of waves and wind in sea state 4. In this sea state, the ship exhibits large-scale periodic oscillations (the pitch angle can reach up to 8°). The position and attitude deviation curve of the rotorcraft during landing is shown in Figure 11-Figure 15 As shown in the figure. The lateral deviation and longitudinal deviation show the dynamic position deviation curve of the UAV when tracking the target point in the ideal landing area of ​​the ship. Although the ship moves violently, the deviation remains within the controllable range, proving that the proposed flight control algorithm has excellent real-time response and dynamic compensation capabilities. From the simulation results, it can be seen that the UAV can generate a dynamically adapted desired trajectory based on the ship state prediction results and track it in real time, effectively responding to the irregular movement of the ship. Especially during the landing process, the UAV can quickly adjust its own motion state to ensure precise landing operations under the uncertainty of the ship deck movement, demonstrating high adaptability and high robustness.

[0211] Simulation condition 2: Level 4 sea condition, the ship speed is 10 knots, sailing into the waves, irregular waves are used to simulate waves, and the ship motion simulation curve is as follows Figure 16 (a) Figure 16 (b) Figure 16 As shown in (c), the ship's motion frequency and amplitude increased significantly compared to the simulation at 6 knots under this sea condition, simulating more stringent landing conditions. Figures 17-21 As shown in the figure, although the violent movement of the ship deck brought greater dynamic disturbances, the UAV deviation curve remained stable and the fluctuations were controlled, which fully demonstrated the strong adaptability and real-time compensation capability of the flight control algorithm. The attitude deviation curve shows that the UAV attitude responds quickly and has good convergence. Although the interference amplitude generated by the ship increases at higher speeds, the UAV attitude can always respond quickly and tend to be stable, indicating that the control system has excellent robustness and fast convergence. Overall, the simulation results prove that the control algorithm based on ship state prediction and flight error coupling compensation proposed in the present invention can achieve high-precision tracking control of the UAV track and attitude at higher speeds and more complex sea conditions, and has significant engineering adaptability and safety advantages.

[0212] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A method for controlling the automatic landing of a shipborne rotary-wing UAV in a designated deck area, characterized in that: The following steps are involved: Step 1: Plan the ideal landing route of the rotary-wing UAV based on the position of the rotary-wing UAV and the position of the ship deck; Step 2: Based on the ideal landing path, obtain the position error of the rotary-wing UAV; Step 3: Predict the ship's running attitude and obtain the ship's attitude prediction result; Step 4: Generate a predicted ideal landing path for the rotorcraft drone based on the ship attitude prediction result, and perform trajectory tracking flight control on the rotorcraft drone based on the position error of the rotorcraft drone to complete automatic landing of the rotorcraft drone in the designated deck area.

2. The method for controlling the automatic landing of a shipborne rotary-wing UAV in a designated deck area according to claim 1, characterized in that: The position error includes: the position error in the tracking descent phase and the position error in the vertical landing phase; For a rotorcraft in the world coordinate system, the coordinates are ,The calculation method of the position error in the tracking descent phase includes: ； ； ； ； Where, Indicates the coordinates of the tracking target point of the rotary-wing UAV in the world coordinate system; Indicates the coordinates of the floating point in the world coordinate system; The starting position of the rotorcraft in the coordinate system Axis coordinates, is the desired landing rate of the UAV, is the time interval from the start of landing to the current moment, 、 They represent the ideal landing path and Plane angle and Plane angle; is the lateral deviation; is the longitudinal deviation; is the vertical deviation; The calculation method of the position error during the vertical landing phase includes: When the rotor UAV is in the ideal landing area, the tracking target point of the rotor UAV is the origin of the landing coordinate system. The world coordinate system of the origin of the landing coordinate system is , the lateral deviation is: , the longitudinal deviation is: , the vertical deviation is: .

3. The method for controlling the automatic landing of a shipborne rotary-wing UAV in a designated deck area according to claim 1, characterized in that: In step 3, the KOA-LSTM model is used to predict the ship's motion posture; Prediction methods include: S31, collecting actual ship data, and preprocessing the actual ship data to obtain ship attitude data; S32. Initialize KOA parameters: number of planets , maximum number of iterations Tmax, hyperparameters: learning rate, upper and lower bounds of the number of neurons, control parameters 、 、 ;in, represents the gravitational constant; represents the distance attenuation coefficient; represents the orbital period; S33, initializing the parameters in step S32 using random positions, orbital eccentricities, and orbital periods, and evaluating the fitness value of the initial population; S34. Mark the global optimal solution as the position of the sun and obtain the current hyperparameters; S35. Calculate the Euclidean distances and gravitational forces between the Sun and all celestial bodies, and calculate the velocities of all celestial bodies; S36. Update the distance between the object and the sun or the new position of the object; S37. Calculate and compare the fitness values ​​of all celestial bodies and the sun, and update the global optimal solution; S38. After the iteration, save the global optimal solution, which is the optimal parameter of the LSTM network; S39. Input the ship attitude data into the LSTM network with optimal parameters to obtain the ship attitude prediction result.

4. The method for controlling the automatic landing of a shipborne rotary-wing UAV in a designated deck area according to claim 2, characterized in that: In step 4, the trajectory tracking flight control method includes: using a closed-loop controller to perform trajectory tracking flight control on the rotary wing UAV; The input of the closed-loop controller is the desired position and the desired yaw angle , the position controller passes the desired position in the world coordinate system , actual location and actual speed Get the expected pulling force in the body coordinate system , desired roll angle and the desired pitch angle , the desired pitch angle , desired roll angle , desired yaw angle And the actual Euler angles and the actual body angular velocity Input to the attitude controller to obtain the desired three-axis torque ; Control the dispenser according to the desired pulling force , desired three-axis torque Get the desired speed ; The motor controller adjusts the speed according to the desired Generate the desired throttle command .

5. The method for controlling automatic landing of a shipborne rotary-wing UAV in a designated deck area according to claim 4, characterized in that: The design method of the posture controller includes: angle loop design and angular velocity loop design; Methods for angle ring design include: ； Expand to get: ； Where, Indicates the output of the desired angular velocity in the body coordinate system; The proportional gain representing the angle error; Indicates the angle error; 、 、 Respectively represent the 、 、 Angular velocity in the roll, pitch, and yaw directions; 、 、 They are roll angle, pitch angle, and yaw angle respectively; 、 、 Respectively represent the angle 、 、 Proportional gain coefficients in the three directions of the axis; Methods for angular velocity loop design include: ； in, ； Where, Indicates the integral gain of angular velocity error; Represents the differential gain of angular velocity error; represents the angular velocity error; Indicates the actual angular velocity of the input; represents the derivative of the angular velocity error.

6. The method for controlling automatic landing of a shipborne rotary-wing UAV in a designated deck area according to claim 5, characterized in that: The design method of the position controller includes: a horizontal channel controller and a height channel controller; The horizontal channel controller includes a position loop design and a speed loop design; The method for designing the position loop includes: ； Where, Indicates the expected horizontal velocity of the output; Respectively 、 Proportional gain coefficient of direction; The method for designing the speed loop includes: ； get ,in , ; Then we get: ； in, ; ； Where, express direction of the acceleration vector; Indicates the mass of the rotary wing UAV; Indicates the lift of the UAV in equilibrium state in the body coordinate system; represents the gravitational constant; express The desired acceleration vector in the direction; represents the proportional gain of the horizontal velocity error; Indicates the integral gain of the horizontal velocity error; represents the differential gain of the horizontal velocity error; Indicates horizontal velocity error; superscript -1 indicates inversion operation; superscript Represents the transpose of a matrix; represents the derivative of the horizontal velocity error; The altitude channel controller includes: altitude loop design and altitude speed loop design; The height ring design method includes: ； Where, Indicates the expected vertical speed of the output; Represents the proportional gain of the error in the vertical direction; The method for designing the altitude speed loop includes: ； Depend on replace get: ； ； Where, express Acceleration in the axial direction; 、 、 They represent the proportional gain of the velocity error in the vertical direction, the integral gain of the velocity error in the vertical direction, and the differential gain of the velocity error in the vertical direction respectively; Indicates the velocity error in the vertical direction; express The derivative of Rotary wing drone The acceleration in the direction of the axis.

7. A shipborne rotary-wing UAV automatic landing control system for a designated deck area, the control system being used to implement the method according to any one of claims 1 to 6, characterized in that: include: Trajectory planning module, used to plan the ideal landing path of the rotary-wing UAV based on the position of the rotary-wing UAV and the position of the ship deck; an error calculation module, configured to obtain a position error of the rotary-wing UAV based on the ideal landing path; The ship attitude prediction module is used to predict the ship's operating attitude and obtain the ship attitude prediction result; The landing control module is used to generate a predicted ideal landing path for the rotor UAV based on the ship attitude prediction result, and to perform trajectory tracking flight control on the rotor UAV based on the position error of the rotor UAV to complete the automatic landing of the rotor UAV in the designated deck area.

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