Four-rotor unmanned aerial vehicle hoisting control method based on feedback linearization sliding mode control

Abstract

The invention discloses a four-rotor unmanned aerial vehicle hoisting control method based on feedback linearization sliding mode control, and belongs to the technical field of four-rotor unmanned aerial vehicle hoisting control. The method comprises the following steps: firstly, performing dynamic feedback linearization on a mathematical model by utilizing differential flatness of the system, constructing a positioning anti-swing controller of the four-rotor unmanned aerial vehicle hoisting system by combining with sliding mode control, and performing positioning on the four-rotor unmanned aerial vehicle hoisting system through a given smooth positioning expected track; and finally, the controller enables the four-rotor unmanned aerial vehicle hoisting system to be capable of accurately tracking and positioning and effectively eliminating the residual swing angle. Experiments prove that the robustness of the controller is high, and the method can effectively improve the reliability and safety of the four-rotor unmanned aerial vehicle hoisting system, so that the transportation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of hoisting control of a quad-rotor unmanned aerial vehicle, and in particular relates to a hoisting control method of a quad-rotor unmanned aerial vehicle based on feedback linearization sliding mode control. Background Art

[0002] Quad-rotor drones are widely used in various fields due to their simple structure, vertical take-off and landing, strong flexibility and low cost. Load capacity is one of the core capabilities of quad-rotor drones. Compared with other load methods, the hanging load has strong adaptability, convenient transportation, and ensures the safety and flexibility of the drone's posture operation. Therefore, the drone hanging transportation system has attracted extensive attention from domestic and foreign researchers. The quad-rotor transportation system is a strongly coupled, under-driven nonlinear system. Its transportation efficiency and suppression of swing angle oscillation are usually contradictory, and the load swing often poses a safety hazard during transportation. Therefore, it is necessary to consider the control of trajectory positioning and load swing angle at the same time to meet the requirements of efficient and safe transportation.

[0003] The differential flatness method is an effective method for dealing with underdriven nonlinear systems and provides a method for feedback linearization of nonlinear systems. If a nonlinear system is differentially flat, then it can achieve dynamic feedback linearization and the system is controllable. The main disadvantage of feedback linearization is its high dependence on the accuracy of the mathematical model of the system and its inability to overcome the uncertainty of the actual system parameters. Therefore, it is generally necessary to combine other robust control strategies when applying it.

[0004] Sliding mode control has strong robustness. Once the system is in sliding mode, the dynamic performance of the system is determined by the sliding surface. At present, one of the research directions of sliding mode control technology is the combination with other control theories, such as adaptive sliding mode control, fuzzy sliding mode control, feedback linearization sliding mode control, etc., mainly using the ability of sliding mode control to deal with uncertain factors to enhance the robustness of the overall control system. Summary of the invention

[0005] The purpose of the present invention is to provide a quad-rotor UAV lifting control method based on feedback linearization sliding mode control, which can solve the load swing problem caused by it while ensuring the precise positioning of the system, thereby improving the safety and reliability of transportation.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] The hoisting control method of a quadrotor UAV based on feedback linearization sliding mode control includes the following steps:

[0008] S1. Construct a two-dimensional mathematical model of a dual-mass quad-rotor UAV lifting system connected by a lifting rope with load swing effect;

[0009] S2. Analyze the differential flatness of the quadrotor UAV lifting system and linearize the mathematical model with dynamic feedback;

[0010] S3. Based on the model after feedback linearization, the dynamic feedback linearization strategy is combined with the sliding mode control to design a sliding mode controller with the control objectives of system tracking positioning and load swing elimination;

[0011] S4. Select a smooth S-shaped curve as the desired positioning trajectory and realize the control of the UAV through the sliding mode controller.

[0012] Furthermore, in S1, the two-dimensional mathematical model is:

[0013] Where x and z are the position coordinates of the center of mass O of the quadrotor UAV lifting system in the XOZ coordinate system. are the second-order derivatives of x and z, respectively, and F x 、F z are the components of the combined lift of the quadrotor UAV lifting system in the x-axis and z-axis directions, m is the overall mass of the UAV, the lifting rope and the load, and m 1 is the mass of the drone, l is the length of the suspension rope, g is the acceleration of gravity, β is the swing angle of the load, is the second-order derivative of β, S β = sinβ,C β =cosβ.

[0014] Furthermore, in S2, the differential flatness analysis uses the load position trajectory as the flat output, and obtains a fourth-order linear system through feedback linearization.

[0015] Furthermore, in S3, the sliding surface function of the sliding mode controller is:

[0016] In the formula, s 1 、s 2 are the sliding surface functions in the x-axis and z-axis directions, e 1 (3) , are the third-order, second-order, and first-order derivatives of the trajectory tracking error in the x-axis direction, are the third-order, second-order, and first-order derivatives of the trajectory tracking error in the z-axis direction, c 11 、c 12 、c 13 and λ 1 is the coefficient to be selected, c 21 、c 22 、c 23 and λ 2is the coefficient to be selected, β is the swing angle of the load;

[0017] The tracking error of the positioning trajectory is expressed as:

[0018] In the formula, e 1 is the tracking error of the x-axis positioning trajectory, e 2 is the tracking error of the positioning trajectory in the z-axis direction, x 2 、z 2 They are the actual output trajectories in the x-axis and z-axis directions respectively. are the desired trajectories given in the x-axis and z-axis directions respectively.

[0019] Furthermore, the sliding mode controller selects the reaching law of the exponent as:

[0020] Where S is s 1 and 2 The overall expression of is the first-order derivative of S, K and ε are adjustment parameters.

[0021] Furthermore, the sliding mode controller is:

[0022] In the formula, v 1 and v 2 is the control input of the linear feedback system, Respectively represent the fourth-order derivative of the actual output trajectory of the load in the x-axis and z-axis directions, They represent the fourth-order derivatives of the desired trajectory of the load in the x-axis and z-axis directions, respectively. They represent the j-order derivatives of the actual output trajectory of the load in the x-axis and z-axis directions, They represent the j-order derivative of the desired trajectory of the load in the x-axis and z-axis directions, respectively, and c 1j 、c 2j , 1 , 2 is the coefficient to be selected, β is the swing angle of the load, S is s 1 and 2 The overall expression of , K and ε are adjustment parameters.

[0023] Furthermore, in S4, the expression for positioning the expected trajectory is as follows:

[0024] In the formula, is the expected trajectory of the load at time t, The expected trajectory of the load in the x-axis and z-axis directions at time t, px 、p z are the displacements of the desired trajectory in the x-axis and z-axis directions, ε is the initial acceleration adjustment parameter, and k 1x , k 2x , k 1z , k 2z For gain.

[0025] The present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned four-rotor unmanned aerial vehicle lifting control method based on feedback linearization sliding mode control is implemented.

[0026] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned four-rotor unmanned aerial vehicle lifting control method based on feedback linearization sliding mode control is implemented.

[0027] The beneficial effects of the above scheme are:

[0028] (1) The quad-rotor UAV lifting positioning and anti-sway control method of the present invention can better replace the experience operation of technicians, reduce the errors caused by human factors, solve the shortcomings of manual control methods that cannot cope with harsh environments, and solve the problem of load swing generated during the flight of the UAV. It can realize accurate positioning and anti-sway angle of the UAV during transportation, and improve the safety and reliability of transportation.

[0029] (2) Based on a smooth desired trajectory, the present invention utilizes the differential flatness of the system to linearize the system dynamic feedback, combines dynamic feedback linearization with sliding mode control, and constructs a positioning and anti-sway controller for the lifting system, so that the UAV lifting system has the characteristics of precise positioning and anti-sway control. Compared with traditional PID control and dynamic feedback control methods, the present invention enables the lifting system to reach the specified position faster and track the desired trajectory more stably; it can effectively suppress the load swing angle during the UAV lifting process, achieve precise positioning of the system, eliminate residual load swing, and improve transportation efficiency and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 A schematic diagram of a three-dimensional model of a dual-mass quad-rotor UAV lifting system connected by a lifting rope;

[0031] Figure 2 A schematic diagram of a two-dimensional model of a dual-mass quad-rotor UAV lifting system connected by a lifting rope;

[0032] Figure 3 is the load position change curve in the x-axis direction;

[0033] Figure 4is the load position change curve in the z-axis direction;

[0034] Figure 5 is the variation curve of load swing angle β;

[0035] Figure 6 is the trajectory tracking error curve of the load in the x-axis direction;

[0036] Figure 7 is the trajectory tracking error curve of the load in the z-axis direction;

[0037] Figure 8 It is the trajectory tracking error curve of the load in the x-axis and z-axis directions when the system parameters change;

[0038] Fig. 9 It is the load swing angle β variation curve when the system parameters change. DETAILED DESCRIPTION

[0039] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0040] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0041] A method for hoisting a quad-rotor UAV based on feedback linearized sliding mode control comprises the following steps:

[0042] S1. Construct a two-dimensional mathematical model of a dual-mass quad-rotor UAV lifting system connected by a lifting rope with load swing effect;

[0043] S2. Analyze the differential flatness of the quadrotor UAV lifting system and linearize the mathematical model with dynamic feedback;

[0044] S3. Based on the model after feedback linearization, the dynamic feedback linearization strategy is combined with the sliding mode control to design a sliding mode controller with the control objectives of system tracking positioning and load swing elimination;

[0045] S4. Select a smooth S-shaped curve as the desired positioning trajectory and realize the control of the UAV through the sliding mode controller.

[0046] Embodiment 1:

[0047] This embodiment provides a quadrotor UAV lifting control method based on feedback linearized sliding mode control. First, the hardware structure of the quadrotor UAV lifting system with load swing effect is built; Figure 1As shown, the hardware structure is mainly composed of the drone body, the suspension rope between the drone and the load, and the load. Specifically, the quad-rotor drone uses an F450 quad-rotor drone with a wheelbase of 450mm, the suspension rope uses a rigid lightweight rope, and the load is a 3D printed ball.

[0048] Based on the dynamic model of the UAV lifting system with load swing effect, the mathematical expressions of the positions of the UAV and the load are listed; then the differential flatness of the UAV lifting system is analyzed, and the mathematical model is linearized with dynamic feedback; according to the model after feedback linearization, the dynamic feedback linearization strategy is combined with the sliding mode control, and a sliding mode controller with system tracking and positioning and load swing elimination as control objectives is designed; a smooth S-shaped curve is selected as the desired positioning trajectory, and the UAV control is realized through the sliding mode controller, so that the UAV lifting system has the advantages of stable tracking, precise positioning and load swing elimination.

[0049] The following is a detailed description of each step:

[0050] Step S1, construct a two-dimensional mathematical model of a dual-particle quad-rotor UAV lifting system connected by a lifting rope with a load swing effect, and the specific construction process is as follows:

[0051] like Figure 1 As shown in the figure, in the three-dimensional model of the quadrotor UAV lifting system, the center of mass O of the double-mass quadrotor UAV lifting system is selected as the origin, and a motion coordinate system OXYZ is established in the same direction as the ground coordinate system. 1 、m 2 are the masses of the quadrotor drone and the payload, respectively, and l 1 , l 2 are the distances from the drone and the payload to the center of mass O, g is the acceleration of gravity, F is the total lift of the system, and F x 、F y 、F z are the components of the resultant lift in the x-axis, y-axis, and z-axis directions respectively. 1 is the position trajectory of the UAV, X is the position trajectory of the center of mass of the lifting system, and X 2 is the load position trajectory.

[0052] When the rope is tightened, the center of mass of the system is located at a certain point on the rope. Its position can be defined by the center of mass. At this time, a position constraint is added, and the degree of freedom of the system is 5. The generalized coordinates q(x, y, z, θ x ,θ y ), where X = [x, y, z] T ∈R 3 is the position of the center of mass O in the ground system, θ x is the angle between the rope and the YOZ plane, indicating the swing angle of the rope in the x-axis direction, θ yIt is the angle between the projection of the OQ end of the rope on the YOZ plane and the positive direction of the OZ axis, indicating the swing angle of the rope in the y-axis direction, Q is m 1 The position of the center of mass. The dynamic model of the system is established by Lagrange equations:

[0053] The above variables are expressed as: S j = sinθ j (j=x,y), C j = cosθ j (j=x,y) (2)

[0054] In the formula, F x 、F y 、F z are the components of the combined lift of the quadrotor UAV lifting system in the x-axis, y-axis, and z-axis directions, respectively; x, y, and z are the position coordinates of the center of mass O of the quadrotor UAV lifting system in the OXYZ coordinate system. are the second-order derivatives of x, y, and z, respectively.

[0055] When the system is near the equilibrium point, the state variables of the above system dynamics equation can be linearized, and we have:

[0056] From formula (3), we can get two swing angles θ x ,θ y Affected by the x-axis and y-axis force components respectively, and also by the z-axis force component at the same time, the motion on the x-axis and y-axis is in a completely decoupled state, and the motion of the three-dimensional model can be decomposed into a two-dimensional model with the same independent motion in the x-axis or y-axis direction.

[0057] Therefore, we only need to study the motion on one of the two-dimensional planes, and the motion on the other plane has the same control law. Then, in the hanging model of the quadcopter based on the XOZ plane, the state change in the y-axis direction is zero, that is, Then formula (1) can be simplified as follows:

[0058] The mathematical model of the quadcopter UAV lifting system is built on the XOZ plane, such as Figure 2 As shown, β is the swing angle of the load, and F is the total lift force on the system.

[0059] According to the Lagrangian dynamics model, the two-dimensional mathematical model of the dual-particle quadrotor UAV lifting system with load swing effect is established as follows:

[0060] Where x and z are the position coordinates of the center of mass O of the quadrotor UAV lifting system in the XOZ coordinate system. are the second-order derivatives of x and z, respectively, and F x 、F z are the components of the combined lift of the quadrotor UAV lifting system in the x-axis and z-axis directions, m is the overall mass of the UAV, the lifting rope and the load, and m 1 is the mass of the drone, l is the length of the suspension rope, g is the acceleration of gravity, β is the swing angle of the load, is the second-order derivative of β, S β = sinβ,C β =cosβ.

[0061] Since the dynamic models of the system established in the XOZ plane and the YOZ plane are similar, the present application designs a tracking and positioning and anti-sway controller for the mathematical model (Formula 5) of the quadcopter lifting system on the XOZ plane.

[0062] By constructing a two-dimensional mathematical model, the controller design is simpler and parameter adjustment is easier, which provides a guarantee for precise real-time control and improves computing efficiency and system stability.

[0063] Step S2: Analyze the differential flatness of the quadrotor UAV lifting system and perform dynamic feedback linearization on the mathematical model.

[0064] For dynamic feedback linearization, the quadrotor UAV lifting system model is firstly subjected to differential flatness analysis to determine that the flat output is the load position trajectory.

[0065] Where, X 2 is the load position trajectory, x 2 、z 2 are the actual trajectories of the load on the x and z coordinates, respectively. x is the actual trajectory of the center of mass O on the x coordinate, z is the actual trajectory of the center of mass O on the z coordinate, and l 2 is the distance from the load to the center of mass O of the lifting model, S β = sinβ,C β =cosβ.

[0066] For a nonlinear system with flat outputs, if a set of system outputs can be found so that all state variables and input variables can be represented by this set of outputs and their finite-order derivatives, then the system is a differentially flat system.

[0067] In the formula, is the unit vector in the direction of gravity.

[0068] A system with differential flatness has a dynamic internal feedback that makes the original system differentially homeomorphic to a linear controllable system. From equations (8) and (9), we can see that the highest order of the system state and control variables with respect to the flat output function is 4, so the equivalent linear feedback system is 4th order. There is dynamic internal feedback and variable substitution to transform the system (Equation 5) into the following closed-loop system:

[0069] In the formula, They represent the fourth-order derivatives of the actual output trajectory of the load in the x-axis and z-axis directions, respectively. 1 and v 2 is the control input of the linear feedback system.

[0070] The 1st to 4th order derivatives of the flat output are calculated as follows: make: Then we have: Thus we get:

[0071] By transforming formula (14), we can get:

[0072] From equations (5), (12), and (15), we can obtain:

[0073] Where η 1 , η 2 A new state variable for the system, which is about v 1 , v 2 and β, so once v 1 ,v 2 Determine, then η 1 , η 2 Dynamic determination of F x , F z .

[0074] In summary, formula (5)(10)(16) is composed of v 1 , v 2 The new closed-loop system with control input, Equation (16) constitutes internal feedback, which can be expressed as Formula (5) and (16) add the state variable η 1 , η 2 The expansion system. x , F zSubstituting into formula (5) we get v 1 , v 2 , and v 1 , v 2 It is also the control input of the linear system (10), that is, it completes the feedback linearization of the original nonlinear system.

[0075] Step S3: According to the model after feedback linearization, the dynamic feedback linearization strategy is combined with the sliding mode control to design a sliding mode controller with system tracking positioning and load swing elimination as control objectives;

[0076] Define tracking error:

[0077] In the formula, e 1 is the tracking error of the x-axis positioning trajectory, e 2 is the tracking error of the positioning trajectory in the z-axis direction, e 3 is the error of the swing elimination, x 2 、z 2 They are the actual output trajectories in the x-axis and z-axis directions respectively. are the desired trajectories given in the x-axis and z-axis directions respectively, and β is the swing angle of the load.

[0078] The sliding surface function of the sliding mode controller is designed as:

[0079] In the formula, s 1 、s 2 are the sliding surface functions in the x-axis and z-axis directions, e 1 (3) , are the third-order, second-order, and first-order derivatives of the trajectory tracking error in the x-axis direction, are the third-order, second-order, and first-order derivatives of the trajectory tracking error in the z-axis direction, c 11 、c 12 、c 13 and λ 1 is the coefficient to be selected, c 21 、c 22 、c 23 and λ 2 is the coefficient to be selected, and β is the swing angle of the load.

[0080] The reaching law of the selected exponent is:

[0081] Where S is s 1 and 2 The overall expression of is the first-order derivative of S, K and ε are adjustment parameters.

[0082] Compared with the traditional single-dimensional or simple combination sliding surface function design, the sliding surface function designed in the present invention can more comprehensively and accurately reflect the tracking state of the system, thereby making the sliding mode controller more targeted and effective in the control process.

[0083] Combine dynamic feedback linearization with sliding mode control. Derivative (18) and combining (10) and (19) yield the designed sliding mode controller:

[0084] In the formula, v 1 and v 2 is the control input of the linear feedback system, Respectively represent the fourth-order derivative of the actual output trajectory of the load in the x-axis and z-axis directions, They represent the fourth-order derivatives of the desired trajectory of the load in the x-axis and z-axis directions, respectively. They represent the j-order derivatives of the actual output trajectory of the load in the x-axis and z-axis directions, They represent the j-order derivative of the desired trajectory of the load in the x-axis and z-axis directions, respectively, and c 1j 、c 2j , λ1, λ2 are the coefficients to be selected, β is the swing angle of the load, S is s 1 and 2 The overall expression of , K and ε are adjustment parameters.

[0085] In this embodiment, the control input signal v 1 、v 2 Driven by the robot, the dual goals of tracking and positioning of the quad-rotor UAV lifting system and eliminating load sway are achieved.

[0086] Step S4: select a smooth S-shaped curve as the desired positioning trajectory and realize the control of the UAV through the sliding mode controller.

[0087] The expression of the desired positioning trajectory is as follows:

[0088] In the formula, in the formula, is the expected trajectory of the load at time t, The expected trajectory of the load in the x-axis and z-axis directions at time t, p x 、p z are the displacements of the desired trajectory in the x-axis and z-axis directions, ε is the initial acceleration adjustment parameter, and k 1x , k 2x , k 1z , k 2z For gain.

[0089] In this embodiment, px =8, p z =8 as the displacement of the desired trajectory in the x-axis and z-axis directions, ε=3.5, k 1x =1.2,k 2x =0.48,k 1z =1.2,k 2z =0.48.

[0090] The positioning desired trajectory satisfies the following constraints:

[0091] (1) As time goes by, the positioning trajectory converges to the specified position, that is:

[0092] (2) Must be bounded and should satisfy:

[0093] (3) The initial condition of X2 is zero, that is:

[0094] In the formula, Indicates displacement, velocity, acceleration and impact in the x-axis direction; Indicates the displacement, velocity, acceleration, and impact in the z-axis direction.

[0095] The present invention selects a smooth S-curve as the desired positioning trajectory, which can better meet the requirements for the stability of the movement of the quadcopter during the actual lifting process, avoid the sudden change of physical quantities such as speed and acceleration, reduce the system impact, and help improve the safety and stability of the lifting. At the same time, clear constraints are proposed for the positioning reference trajectory, such as convergence to a specified position over time, boundedness, and specific initial conditions. These constraints further optimize the design of the desired trajectory and ensure the rationality and feasibility of the control process.

[0096] In order to verify the effectiveness and superiority of the quadrotor UAV lifting control method based on feedback linearization sliding mode control described in the present invention, the following experiments were conducted:

[0097] The simulation model of quad-rotor UAV lifting was built using the matlab / simulink experimental simulation platform, and the positioning and anti-sway performance of the system were analyzed through numerical simulation; the main parameters of the simulation model are: m 1 =0.5kg, m 2 =0.1kg, l 1 =0.2m,l 2 =0.8m, g=9.8m / s 2 , ε=3.5.

[0098] Positioning trajectory displacement p x =8m and p z =8m; expected trajectory gain k 1x =1.2, k 2x =0.48, k 1z =1.2, k 2z =0.48; the controller gain c proposed by the present invention 11 =320, c 12 =150, c 13 =4, c 21 =520, c 22 =240, c 23 =3,λ=10,ε=1,K 1 =35, K 2 =40.

[0099] The experimental results are as follows Figures 3 to 7 As shown. It can be seen from the comparison curves in the figure that compared with the traditional PID control and dynamic feedback control methods, this method can enable the drone to reach the specified position faster and better track the desired trajectory of positioning. In terms of anti-sway, the traditional PID swing angle has a higher swing frequency, a larger swing amplitude and a longer anti-sway time; compared with the dynamic feedback control method, the anti-sway time of the present invention is more than 2s faster, which can achieve faster and better anti-sway control.

[0100] like Figures 8 to 9 As shown, the control method proposed in the present invention has strong robustness and can still ensure that the system can stably track the positioning trajectory and complete the transportation task of positioning and eliminating sway under the condition of model uncertainty.

[0101] Embodiment 2:

[0102] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the quad-rotor unmanned aerial vehicle lifting control method based on feedback linearized sliding mode control described in Example 1 is implemented.

[0103] Embodiment 3:

[0104] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the quad-rotor drone lifting control method based on feedback linearized sliding mode control described in Example 1 is implemented.

[0105] The present invention can dynamically adjust the control input according to the real-time status of the system and the expected trajectory. Compared with the traditional method, this control law based on the fusion of two advanced control technologies has stronger adaptability and robustness, and can better cope with the uncertainty factors in the lifting system of the quad-rotor drone, such as load mass changes, air resistance and other interference, thereby improving the control performance of the entire lifting system. Experiments show that the present invention can effectively improve the reliability and safety of the lifting system of the quad-rotor drone, thereby improving transportation efficiency.

[0106] Finally, it should be noted that the parts of the present invention that are not described in detail are all prior art. Those of ordinary skill in the art can understand that the above are only preferred examples of the invention and are not intended to limit the invention. Although the invention is described in detail with reference to the aforementioned examples, those of ordinary skill in the art can still modify the technical solutions recorded in the aforementioned examples, or replace some of the technical features therein with equivalents. Any modifications, equivalent replacements, etc. made within the spirit and principles of the invention should be included in the scope of protection of the invention.

Claims

1. A quadrotor UAV lifting control method based on feedback linearization sliding mode control, characterized in that: The following steps are involved: S1. Construct a two-dimensional mathematical model of a dual-mass quad-rotor UAV lifting system connected by a lifting rope with load swing effect; S2. Analyze the differential flatness of the quadrotor UAV lifting system and linearize the mathematical model with dynamic feedback; S3. Based on the model after feedback linearization, the dynamic feedback linearization strategy is combined with the sliding mode control to design a sliding mode controller with the control objectives of system tracking positioning and load swing elimination; S4. Select a smooth S-shaped curve as the desired positioning trajectory and realize the control of the UAV through the sliding mode controller.

2. The method for hoisting a quadrotor drone based on feedback linearized sliding mode control according to claim 1, characterized in that: In S1, the two-dimensional mathematical model is: Where x and z are the position coordinates of the center of mass O of the quadrotor UAV lifting system in the XOZ coordinate system. are the second-order derivatives of x and z, respectively, and F x 、F z are the components of the combined lift of the quadrotor UAV lifting system in the x-axis and z-axis directions, m is the overall mass of the UAV, the lifting rope and the load, m1 is the mass of the UAV, l is the length of the lifting rope, g is the acceleration of gravity, β is the swing angle of the load, is the second-order derivative of β, S β = sinβ,C β =cosβ.

3. The quad-rotor UAV lifting control method based on feedback linearization sliding mode control according to claim 2 is characterized in that: In S2, the differential flatness analysis uses the load position trajectory as the flat output, and obtains a fourth-order linear system after feedback linearization.

4. The quad-rotor UAV lifting control method based on feedback linearization sliding mode control according to claim 1 or 3, characterized in that: In S3, the sliding surface function of the sliding mode controller is: Where s1 and s2 are sliding surface functions in the x-axis and z-axis directions respectively, e1 (3) , are the third-order, second-order, and first-order derivatives of the trajectory tracking error in the x-axis direction, are the third-order, second-order, and first-order derivatives of the trajectory tracking error in the z-axis direction, c 11 、c 12 、c 13 and λ1 are the coefficients to be selected, c 21 、c 22 、c 23 and λ2 are the coefficients to be selected, and β is the swing angle of the load; The tracking error of the positioning trajectory is expressed as: Where, e1 is the tracking error of the positioning trajectory in the x-axis direction, e2 is the tracking error of the positioning trajectory in the z-axis direction, x2 and z2 are the actual output trajectories in the x-axis and z-axis directions respectively. are the desired trajectories given in the x-axis and z-axis directions respectively.

5. The method for hoisting and controlling a quad-rotor UAV based on feedback linearized sliding mode control according to claim 4 is characterized in that: The sliding mode controller selects the reaching law of the exponent as: Where S is the overall expression of s1 and s2, is the first-order derivative of S, K and ε are adjustment parameters.

6. The method for hoisting control of a quad-rotor UAV based on feedback linearized sliding mode control according to claim 5, characterized in that: The sliding mode controller is: Where v1 and v2 are the control inputs of the linear feedback system, They represent the fourth-order derivatives of the actual output trajectory of the load in the x-axis and z-axis directions, They represent the fourth-order derivatives of the desired trajectory of the load in the x-axis and z-axis directions, respectively. They represent the j-order derivatives of the actual output trajectory of the load in the x-axis and z-axis directions, They represent the j-order derivative of the desired trajectory of the load in the x-axis and z-axis directions, respectively, and c 1j 、c 2j , λ1, λ2 are the coefficients to be selected, β is the swing angle of the load, S is the overall expression of s1 and s2, and K and ε are adjustment parameters.

7. The method for hoisting control of a quad-rotor UAV based on feedback linearized sliding mode control according to claim 6, characterized in that: In S4, the expression for positioning the expected trajectory is as follows: In the formula, is the expected trajectory of the load at time t, The expected trajectory of the load in the x-axis and z-axis directions at time t, p x 、p z are the displacements of the desired trajectory in the x-axis and z-axis directions, ε is the initial acceleration adjustment parameter, and k 1x , k 2x , k 1z , k 2z For gain.

8. An electronic device, characterized in that: The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the quad-rotor unmanned aerial vehicle lifting control method based on feedback linearized sliding mode control as described in any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the quad-rotor unmanned aerial vehicle lifting control method based on feedback linearization sliding mode control described in any one of claims 1 to 7 is implemented.

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