A ship-borne unmanned aerial vehicle side arm recovery docking control method based on LADRC

Abstract

The application discloses a shipborne unmanned aerial vehicle side arm recovery docking control method based on LADRC, first, an unmanned aerial vehicle 6DOF nonlinear dynamics model reflecting the influence of various complex airflow disturbance is established, on the basis, an unmanned aerial vehicle back hook affine nonlinear dynamics model is constructed based on the vector relationship between the unmanned aerial vehicle centroid and the back hook position; the strong external interference such as ship wake flow and atmospheric turbulence suffered by the unmanned aerial vehicle is regarded as a lumped disturbance, a linear extended state observer is designed to accurately reconstruct the unmeasurable unknown dynamics item in the system and compensate the controller in advance; finally, combined with the shipborne side arm motion compensation instruction, a side arm recovery high anti-interference docking control method based on linear active disturbance rejection technology is designed to realize the docking control of the unmanned aerial vehicle and the side arm rope under complex disturbance. The application realizes the safe docking of the slow dynamic unmanned aerial vehicle and the fast dynamic side arm arresting cable under multiple complex disturbances, and effectively improves the docking precision and safety of the shipborne side arm recovery.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle offshore surface landing recovery, and mainly designs a shipborne unmanned aerial vehicle side arm recovery docking method based on LADRC. BACKGROUND

[0002] The shipborne unmanned aerial vehicle refers to an unmanned aerial vehicle specially designed for an aircraft carrier, a cruiser, a destroyer and an amphibious landing craft and other surface warships, which has the functions of intelligence collection, monitoring, reconnaissance, search and rescue, and striking in some cases. Meanwhile, the shipborne unmanned aerial vehicle has the functions of long endurance, long-range control and reliable communication and data link to transmit real-time task critical data to a warship or a command center. The design should also ensure perfect integration with other systems and facilities of the warship, and cooperation with the personnel on the warship and other aircraft to expand and enhance the combat capability and tactical diversity of the warship.

[0003] The safe landing and recovery of the shipborne unmanned aerial vehicle is the prerequisite for maintaining the sustained combat capability of the warship. The current shipborne unmanned aerial vehicle landing recovery often faces three difficult problems: first, compared with the land-based landing, the shipborne unmanned aerial vehicle landing often faces a much smaller space, only one tenth of the land-based runway. Second, due to uncertain external disturbances such as ship wake flow and atmospheric turbulence, the performance of the shipborne unmanned aerial vehicle landing recovery control system usually does not meet the requirements. Third, due to the characteristics of the undulating deck of the warship being much faster than the dynamic response of the unmanned aerial vehicle, that is, the tracking lag of the unmanned aerial vehicle in tracking the fast dynamic deck of the warship. Therefore, a shipborne unmanned aerial vehicle side arm recovery docking method based on LADRC is proposed to realize stable recovery control of the unmanned aerial vehicle and improve the accuracy of the unmanned aerial vehicle side arm recovery, which is of great significance for the recovery of unmanned aerial vehicles on medium and small warships. SUMMARY

[0004] The present application aims to solve the problem of unmanned aerial vehicle recovery docking control on medium and small warships under the influence of near-surface ship wake flow and atmospheric turbulence, and proposes a shipborne unmanned aerial vehicle side arm recovery docking control method based on LADRC, which specifically includes the following steps:

[0005] Step one, construct a 6DOF affine nonlinear dynamic model of the unmanned aerial vehicle which can fully represent the influence of the landing wind field;

[0006] Step two, according to the relationship between the unmanned aerial vehicle back hook and the unmanned aerial vehicle centroid position vector, establish a dynamic model of the unmanned aerial vehicle back hook based on the unmanned aerial vehicle motion model in step one;

[0007] Step three, in the 6DOF affine nonlinear model for control design of the unmanned aerial vehicle established in step two, as a system disturbance, construct a linear extended observer to observe the system disturbance and the flight state V x , X iThe accurate estimation of i=2, 3, 4 is carried out and a feedforward compensation for the controller is provided;

[0008] Step four, according to the principle of stationary random process, the expected disturbance on the docking point is represented by the ship translation motion and angular motion, and the disturbance obtained in step six is combined with the motion of the ship in the inertial coordinate system to obtain the expected docking point motion trajectory.

[0009] Step five, the disturbance estimation compensation value obtained in step three is combined with the model built in steps one and two to design a linear active disturbance rejection nonlinear controller for the back hook of the unmanned aerial vehicle;

[0010] Step six, combining the docking instruction in step four and the channel and loop controller in step five, the LADRC-based shipborne unmanned aerial vehicle side arm recovery docking control method is designed.

[0011] Compared with the prior art, the present application has the following obvious advantages:

[0012] (1) A LADRC-based shipborne unmanned aerial vehicle side arm recovery docking control method, which establishes an affine nonlinear complex disturbance model of the unmanned aerial vehicle back hook motion.

[0013] (2) A LADRC-based shipborne unmanned aerial vehicle side arm recovery docking control method, which effectively improves the active anti-disturbance ability of the shipborne unmanned aerial vehicle docking control system to the influence of uncertain strong external disturbance.

[0014] (3) A LADRC-based shipborne unmanned aerial vehicle side arm recovery docking control method, which reduces the tracking lag caused by the rapid fluctuation of the shipborne side arm. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A shipborne unmanned aerial vehicle side arm recovery schematic diagram is provided for the present application;

[0016] Figure 2 A LADRC-based shipborne unmanned aerial vehicle side arm recovery docking control flowchart is provided for the present application;

[0017] Figure 3 A back hook and center of mass position vector relationship diagram of a shipborne unmanned aerial vehicle is provided for the present application;

[0018] Figure 4 A two-dimensional docking trajectory result diagram of the unmanned aerial vehicle under different initial positions in the example of the present application is provided;

[0019] Figure 5 A three-dimensional docking trajectory result diagram of the unmanned aerial vehicle under different initial positions in the example of the present application is provided; DETAILED DESCRIPTION

[0020] For the convenience of those skilled in the art to understand and implement the present application, the present application is further described in detail below with reference to the accompanying drawings.

[0021] The application discloses a ship-borne unmanned aerial vehicle side arm recovery docking control method based on LADRC, first, a ship wake and atmospheric turbulence model reflecting the ship-boarding environment is established, and a 6DOF nonlinear model of the unmanned aerial vehicle fully reflecting the influence of complex disturbance is established; on this basis, according to the relationship between the unmanned aerial vehicle centroid and the back hook position vector, an unmanned aerial vehicle back hook affine nonlinear dynamics model is constructed; further, the strong external disturbance such as the ship wake and atmospheric turbulence suffered by the unmanned aerial vehicle is regarded as a lumped disturbance, a linear extended state observer is designed to accurately reconstruct the unobservable unknown dynamics items in the system and compensate for the controller in advance; then, combined with the ship-borne side arm motion compensation instruction, a high anti-interference docking control method of the side arm recovery based on the linear active disturbance rejection technology is designed to realize the docking control of the unmanned aerial vehicle and the side arm rope under complex disturbance.

[0022] In this example, as shown in Figure 1 , it is assumed that during the side arm recovery process, the ship moves forward at a constant speed, the speed is 15 m / s, the initial relative distance between the unmanned aerial vehicle and the ship is 800 m, the unmanned aerial vehicle is decelerated when it is 200 m away from the ship, the selected parameters of the unmanned aerial vehicle are: the mass is 92.1 kg, the wing span is 4.29 m, the flight parameters are: the flight height H = 30 m, the initial flight speed V = 35 m / s, and the relative docking speed is 10 m / s.

[0023] As shown in Figure 2 , it is a flow chart of the side arm recovery docking control method of the ship-borne unmanned aerial vehicle based on LADRC, and specifically includes the following steps:

[0024] Step one, a 6DOF affine nonlinear dynamics model of the unmanned aerial vehicle fully reflecting the influence of the near-sea surface landing wind field is constructed, specifically:

[0025] Firstly, on the basis of the conventional fixed-wing unmanned aerial vehicle motion model, the continuous influence of the ship wake and atmospheric turbulence disturbance on the unmanned aerial vehicle is analyzed, and an equivalent mathematical transformation method is used to construct a 6DOF affine nonlinear dynamics model of the unmanned aerial vehicle fully reflecting the influence of the near-sea surface landing wind field. In addition, the 6DOF affine nonlinear model of the unmanned aerial vehicle is further decomposed into a forward velocity subsystem and a trajectory subsystem by using the time scale separation principle, and the state variables (including forward velocity V x , side vertical position vector X1, side vertical velocity vector X2, airflow angle vector X3, angular rate vector X4 and rudder deflection vector U act ) are defined as shown below, and the mathematical model is as follows:

[0026]

[0027] The forward velocity loop equation is:

[0028]

[0029] Where V0 is the ship's constant forward speed; δ T For throttle opening; y, z and V y V z δ represents the vertical position and velocity components of the UAV in the inertial frame, respectively; φ, β, and α represent the roll angle, sideslip angle, and angle of attack of the UAV, respectively; a ,δ e ,δ r These are the aileron deflection angle, elevator deflection angle, and rudder deflection angle of the UAV, respectively. H represents an unmeasurable, unknown, nonlinear term within the system. i ,i=2,3,4 is the model auxiliary matrix composed of easily obtainable state information within the system; B Vx B i ,i=2,3,4 is the system control coefficient matrix.

[0030] Step Two: Given that the drone's hook motion can be achieved not only through translational motion of the drone's center of mass but also through rotational motion around its center of mass, relying solely on the drone's center of mass motion to indirectly control the hook position during side arm recovery cannot effectively improve recovery docking accuracy and response speed. Therefore, based on the relationship between the drone's hook and its center of mass position vector, as follows... Figure 3 As shown, based on the UAV motion model in step one, the UAV back hook dynamic model is established as follows:

[0031]

[0032] Among them, X H =[x H y H , z H ] T For the position of the UAV's dorsal hook in the inertial frame, X cg-hook R is the position vector between the UAV's center of mass and the dorsal hook. I / B This is the transformation matrix from machine system coordinates to inertial coordinates.

[0033] Step 3: For the affine nonlinear model of UAV motion in Step 1 and the affine nonlinear model of UAV back hook in Step 2, determine the unmeasurable unknown nonlinear quantities within the system. As the total disturbance, the Linear Extended Observer (LESO) is used to estimate the total disturbance, and the estimated value of the total disturbance term is then fed forward to each loop controller for compensation. The specific steps are as follows:

[0034] Step 301, taking the lateral vertical velocity loop as an example, a linear extended observer is designed to estimate and compensate the lateral vertical velocity X2 and the total disturbance term F2, and the observer is specifically designed as follows:

[0035]

[0036] wherein, is the estimated value of X2, is the estimated value of the total disturbance term F2, and

[0037] J 21 = diag(2w 21 ,2w 22 ), J 21 ,J 22 are the design parameters of the linear extended observer, w 21 , w 22 are the bandwidths of the linear extended state observer of the lateral vertical velocity channel, and w 21 = w 22 = 5 through repeated debugging of the example.

[0038] Step 302, as in step 301, linear extended observers are respectively designed to estimate and compensate the states and total disturbances of the angle of attack loop, the angular rate loop and the forward velocity loop, as follows:

[0039] The linear extended state observer is designed for the angle of attack loop:

[0040]

[0041] wherein, is the estimated value of X3, is the estimated value of the total disturbance term F3, and

[0042] J 31 = diag(2w 31 ,2w 32 ,2w 33 ), J 31 ,J 32 are the design parameters of the linear extended observer, w 31 , w 32 , w 33 are the bandwidths of the linear extended state observer of the angle of attack channel, and w 31 = w 32 = u 33 = 10 through repeated debugging of the example.

[0043] The linear extended state observer is designed for the angular rate loop:

[0044]

[0045] wherein, is an estimate of X4, is an estimate of the total interference term F4, and

[0046] J 41 = diag(2w 41 ,2w 42 ,2w 43 ), J 41 ,J 42 are design parameters of the linear extended observer, w 41 is the forward velocity channel linear extended state observer bandwidth, which is repeatedly tuned in this example to be w 42 = 20. 43 41 = u 42 = w 43 = 20.

[0047] A linear extended state observer is designed for the forward velocity loop as follows:

[0048]

[0049] wherein, is an estimate of V x , is an estimate of the total interference term F Vx , and J Vx1 = 2w Vx , J Vx1 , J Vx2 are design parameters of the linear extended observer, w Vx is the forward velocity channel linear extended state observer bandwidth, which is repeatedly tuned in this example to be w Vx = 10.

[0050] Step four, according to the principle of stationary random process, the disturbance expected to be suffered by the docking point is expressed by the translational motion and angular motion of the ship, and the disturbance obtained in step six is combined with the motion of the ship in the inertial coordinate system to obtain the motion trajectory of the expected docking point, and the specific steps are as follows:

[0051] Step 401, according to the principle of stationary random process, the disturbance expected to be suffered by the docking point of the shipborne side arm is expressed by the translational motion and angular motion of the ship, as follows:

[0052]

[0053] wherein, Δx s , Δy s , Δz s ​are the ship's sway, surge and heave motions, respectively s , Ψ s are the ship's roll, pitch and yaw angles, respectively. Δx1, Δy1, Δz1 are the disturbances caused by the ship's translational motion in the inertial frame, and Δx2, Δy2, Δz2 are the disturbances caused by the ship's angular motion in the inertial frame. x ,l y ,l z is the desired relative distance between the ship's center and the docking point of the side arm, in this example, [l x ,l y ,l z ] T =[-30,20,15] T .

[0054] Step 402, combine the disturbances obtained in step 501 with the ship's motion in the inertial coordinate system to obtain the desired trajectory of the docking point of the ship's side arm as follows:

[0055]

[0056] where V0 is the constant forward speed of the ship; Ψ s is the heading angle; Ψ0 is the angle between the ship's speed and the centerline of the deck; x s0 , y s0 , z s0 are the coordinates of the ship's center of gravity, in this example, the heading angle Ψ s = 0, Ψ0 = 0, [x s0 , y s0 , z s0 ] T =[0,0,15] T .

[0057] Step five, based on the disturbance estimation compensation value obtained in step three, the unmanned aerial vehicle affine nonlinear model is built according to steps one and two, and the linear active disturbance rejection controller of each channel of the unmanned aerial vehicle back hook is designed by using the backstepping control theory and the active disturbance rejection control method, and the specific steps are as follows:

[0058] Step 501, define the instructions of each loop and the corresponding tracking error, including the following formula:

[0059]

[0060] where u1, u2, u3 are the virtual control quantities of the side vertical position, side vertical speed, airflow angle and angular rate loops, respectively, generated by the active disturbance rejection controller of each loop; X 1c =[x Hc , y Hc , z Hc ] TThe desired unmanned aerial vehicle back hook docking position command is obtained in step 402; X 2c , X 3c , X 4c The desired lateral vertical, lateral vertical velocity, airflow angle and angular rate docking commands are obtained; The desired docking forward velocity command is obtained; e1, e2, e3, e4 are tracking errors of the lateral vertical position loop, the lateral vertical velocity loop, the airflow angle loop and the angular rate loop respectively;

[0061] Step 502, on the basis of step 501 and combined with the estimated compensation value of the interference observed in step three The self-disturbance controller of each loop is designed as follows:

[0062]

[0063] Wherein, k1=diag(k y , k z ), k2=diag(k Vy , k vz ), k3=diag(k φ , k β , k α ), k4=diag(k p , k q , k r ) and k Vx are unmanned aerial vehicle back hook lateral vertical position, lateral vertical velocity, airflow angle, angular rate loop and forward velocity controller parameters respectively.

[0064] After repeated debugging, appropriate parameters are selected so that the designed loop controller has good tracking expected command ability, and finally the selected loop controller parameters are: k y =k z =0.5, k V＝ k Vz =1, k φ =k β =k α =3, k p =k q =k r =6, k Vx =2

[0065] Step six, combine LESO in step three and each channel loop controller in step four, and take the expected docking point motion in step five as the expected recovery longitudinal and lateral position commands and forward velocity command of the unmanned aerial vehicle back hook, to complete the compound control strategy design of the unmanned aerial vehicle back hook direct dynamics control and the shipborne side arm motion compensation command.

[0066] ​In this example, the UAV flies to the ship with an initial relative position distance of 800 m, and when the relative distance reaches the set ship motion compensation distance of 200 m, the motion compensation is added.

[0067] As shown in Figure 4 , it is a two-dimensional docking trajectory result graph of the UAV in four different initial positions in this example. It can be observed that the lateral and vertical position tracking errors of the UAV are small, which meets the expected tracking effect.

[0068] As shown in Figure 5 , it is a three-dimensional docking trajectory result graph of the UAV in four different initial positions in this example. The inertial system coordinates of case 1 are [800, 35, -15], the inertial system coordinates of case 2 are [800, 35, -45], the inertial system coordinates of case 3 are [800, 5, -45], and the inertial system coordinates of case 4 are [800, 5, -15]. According to the simulation results, the UAV can successfully dock with the arresting cable under the control of the designed controller in different initial positions, and the docking trajectory is relatively smooth, which verifies that the LADRC docking control method of the application still has good stability under the influence of complex disturbances.

[0069] The shipborne UAV side arm recovery docking control method based on LADRC provided by the application is constructed according to the actual offshore landing scene, the actual docking state and the actual ship motion, improves the flight stability of the UAV under the influence of the ship wake and atmospheric turbulence, effectively reduces the tracking lag of the UAV to the rapid fluctuation of the ship deck motion, and ensures the safety of direct docking; the UAV back hook dynamics model built also improves the recovery docking accuracy and the dynamic response speed of the UAV to a certain extent. Through the above mathematical analysis and simulation verification, it is fully proved that the shipborne UAV side arm recovery docking control method based on LADRC is effective in the anti-interference control of UAV offshore landing flight.

[0070] The above is only a preferred embodiment of the application, and does not limit the scope of the application. Without departing from the principles of the application, several improvements and refinements can be made, which should also be considered as the protection scope of the application.

Claims

1. A control method for the recovery and docking of a shipborne unmanned aerial vehicle (UAV) side arm based on LADRC, wherein the control method is implemented based on a shipborne side arm recovery device, the device including a mechanical side arm installed on the stern deck, the end of the mechanical side arm being connected to a fixed slide rail, and an interception cable and an interception net being installed on the fixed slide rail, the docking control method being used to safely dock the UAV with the interception cable, characterized in that... The control method includes the following steps; Step 1: Construct a 6DOF affine nonlinear dynamic model of the UAV to represent the impact of the landing wind field; First, based on the conventional fixed-wing UAV motion model, the continuous impact of ship wake and atmospheric turbulence on the UAV is analyzed, and an equivalent mathematical transformation method is used to construct a 6DOF affine nonlinear dynamic model of the UAV to characterize the impact of the near-sea landing wind field. The UAV 6DOF affine nonlinear model is decomposed into a forward velocity subsystem and a trajectory subsystem using the time-scale separation principle. The state variables are defined as follows, including the forward velocity V. x Lateral vertical position vector X1, lateral vertical velocity vector X2, airflow angle vector X3, angular rate vector X4, and rudder deflection vector U act The mathematical model is as follows: The forward velocity loop equation is: Where V0 is the ship's constant forward speed; δ T For throttle opening; y, z and V y V z φ, β, and α represent the vertical position and velocity components of the UAV in the inertial frame, respectively; φ, β, and α represent the roll angle, sideslip angle, and angle of attack of the UAV, respectively; δ a δ e δ r These are the aileron deflection angle, elevator deflection angle, and rudder deflection angle of the UAV, respectively. H represents an unmeasurable, unknown, nonlinear term within the system. i i = 2, 3, 4 are the model auxiliary matrices formed by readily available state information within the system; B Vx Bi, i = 2, 3, 4 is the system control coefficient matrix; Step 2: Based on the relationship between the UAV's back hook and the UAV's center of mass position vector, establish a dynamic model of the UAV's back hook based on the UAV motion model in Step 1; Step 3: Treat the unmeasurable unknown nonlinear quantities in the 6DOF affine nonlinear model of the UAV as system disturbances, construct a linear extended observer to accurately estimate the disturbances within the system and the flight state of the UAV, and provide feedforward compensation for the controller. Step 4: Input the desired trajectory of the docking point of the shipborne side arm as the command for the UAV's hook position and forward speed to compensate for the ship's deck motion. Step 5: Combine the interference estimation compensation value obtained in Step 3 with the model built in Steps 1 and 2 to design a linear active disturbance rejection nonlinear controller for the UAV back hook motion. The active disturbance rejection nonlinear controller includes lateral vertical position, lateral vertical velocity, airflow angle, angular rate loop and forward velocity controller. Step 6: Based on the docking instructions in Step 4 and the channel and loop controllers in Step 5, complete the design of the shipborne UAV side arm recovery docking control process based on LADRC.

2. The method for controlling the recovery and docking of the side arm of a shipborne UAV based on LADRC according to claim 1, characterized in that: The dynamic model of the UAV back hook is as follows: Among them, X H =[x H y H , z H ] T For the position of the UAV's dorsal hook in the inertial frame, X cg-hook R is the position vector between the UAV's center of mass and the dorsal hook. I / B This is the transformation matrix from machine system coordinates to inertial coordinates.

3. The method for controlling the recovery and docking of the side arm of a shipborne UAV based on LADRC according to claim 2, characterized in that: In step three, the following linear expansion state observers are designed for the lateral vertical velocity loop, airflow angle loop, angular rate loop, and forward velocity loop, which reflect the effects of external disturbances: in, For X2, X3, X4, V respectively x The estimated value, These are respectively the total interference terms F2, F3, F4, and F Vx The estimated value of J, and J 21 =diag(2w 21 2w 22 ), J 31 =diag(2w 31 2w 32 2w 33 ), J 41 =diag(2w 41 2w 42 2w 43 ), JV x1 =2w Vx , w 21 ,w 22 The bandwidth of the linearly extended state observer for the lateral vertical velocity channel; w 31 ,w 32 ,w 33 The bandwidth of the linear expansion state observer for the airflow angle channel; w 41 ,w 42 ,w 43 The bandwidth of the linearly extended state observer for the angular rate channel; w Vx The bandwidth of the forward velocity channel linear expansion state observer.

4. The method for controlling the recovery and docking of the side arm of a shipborne UAV based on LADRC according to claim 2, characterized in that, The specific process of step four is as follows: Step 401: Based on the principle of stationary random processes, the disturbance expected to occur at the docking point of the ship's side arm is represented by the ship's translation and rotation, as shown in the following equation: Where, Δx s ,Δy s ,Δz s These refer to the ship's swaying, pitching, and heaving motions, respectively. These represent the ship's roll, pitch, and bow angles, respectively; Δx1, Δy1, and Δz1 are the disturbances caused by the ship's translational motion in its inertial frame, and Δx2, Δy2, and Δz2 are the disturbances caused by the ship's angular motion in its inertial frame. x ,l y ,l z The relative distance between the desired docking point and the center of the ship; Step 402: Combine the disturbance obtained in step 401 with the motion of the ship in the inertial coordinate system to obtain the desired motion trajectory of the shipborne side arm docking point as follows: Where V0 is the ship's constant forward speed; Ψ s Ψ0 is the heading angle; x is the angle between the ship's speed and the centerline of the deck. s0 ,y s0 ,z s0 These are the coordinates of the ship's center of gravity.

5. The method for controlling the recovery and docking of the side arm of a shipborne UAV based on LADRC according to claim 4, characterized in that, The specific process of step five is as follows: Step 501: Define the commands for each loop and the corresponding tracking errors, as follows: Where u1, u2, and u3 are the virtual control quantities for the lateral vertical position, lateral vertical velocity, airflow angle, and angular rate loops, respectively, generated by the active disturbance rejection controller of each loop; X 1c =[x Hc ,y hc ,z Hc ] T The desired UAV dorsal hook docking position command obtained in step 402; X 2c ,X 3c ,X 4c The desired lateral vertical velocity, airflow angle, and angular rate are used for docking commands; The expected forward velocity command is given; e1, e2, e3, and e4 represent the tracking errors of the lateral vertical position loop, lateral vertical velocity loop, airflow angle loop, and angular rate loop, respectively. Step 502: Based on step 501 and combined with the interference observed in step 3. Estimated compensation value The active disturbance rejection controller for each loop is designed as follows: Where, k1 = diag(k y ,k z ),k2=diag(k Vy ,k Vz ),k3=diag(k φ k β k α ), k4 = diag(k p k q k r ) and k Vx These are the parameters for the UAV's dorsal hook side vertical position, side vertical velocity, airflow angle, angular rate loop, and forward velocity controller.

6. The method for controlling the recovery and docking of the side arm of a shipborne UAV based on LADRC according to claim 4, characterized in that, Step six is ​​as follows: The expected docking point motion of the shipborne side arm in step four is used as the vertical position command and forward velocity command of the expected recovery side of the UAV hook. By combining the LESO in step three and the channel loop controllers in step five, a composite control strategy of direct dynamic control of the UAV hook and motion compensation command of the shipborne side arm is proposed, and the design of the shipborne UAV side arm recovery docking control method based on LADRC is completed.

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