A tilt-rotor unmanned aerial vehicle transition state disturbance control system and method

Abstract

This invention discloses a disturbance rejection control system and method for the transition state of a tiltrotor unmanned aerial vehicle (UAV). Addressing the problems of model uncertainty, external disturbances, and mismatched disturbances in the transition flight phase of a tiltrotor UAV, an adaptive sliding mode observer is first designed to estimate the upper bound of the disturbance derivative online, achieving rapid and accurate estimation of complex disturbances. Based on this, a three-level recursive sliding surface structure is adopted, combined with a predetermined time performance function, to ensure that the tracking error converges to a preset accuracy within a finite time specified by the user and independent of the initial state. The upper bound of the error is estimated by an adaptive law-compensated observer. This invention does not require prior knowledge of the upper bound of the disturbance derivative, the convergence time can be pre-specified, and it exhibits strong robustness and smooth control output in the transition state.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) flight control technology, specifically relating to an anti-disturbance control system and method for a tiltrotor UAV in a transitional flight state. Background Technology

[0002] Tiltrotor UAVs (TUAVs), as a hybrid UAV configuration combining vertical takeoff and landing (VTOL) and high-speed cruise capabilities, have demonstrated great potential in reconnaissance and surveillance, emergency logistics, and urban transportation in recent years. Their core advantage lies in their ability to smoothly switch between helicopter and fixed-wing modes via a rotor tilting mechanism, enabling multimodal flight. However, the transitional flight phase is the most challenging flight state for TUAVs. Rotor tilting leads to drastic changes in aerodynamic characteristics, enhanced structural coupling, and significantly increased model uncertainty. Simultaneously, they face external disturbances such as wind interference, which can easily trigger attitude instability or even flight accidents.

[0003] Currently, various technical solutions have been proposed for the transition process control of tiltrotor unmanned aerial vehicles (UAVs). Related research mainly focuses on system design, aerodynamic characteristic analysis, dynamic modeling, and control strategy optimization. For example, high-fidelity dynamic models are established through rigid-flexible coupling co-simulation to study the coupling effect between the flight controller and the actuation system; wind tunnel experiments are used to analyze the influence of propeller tilt angle on the pressure distribution and flow characteristics of the wing surface; medium-fidelity numerical methods are employed to simulate the aerodynamic characteristics during the hovering-to-forward transition phase; and control allocation methods based on equal control sensitivity are used to reduce manipulation coupling and transient loads during the transition process.

[0004] In the field of flight control, sliding mode control (SMC) is widely used for controlling complex systems such as tiltrotor unmanned aerial vehicles (UAVs) due to its strong robustness to parameter perturbations and external disturbances. To further improve control performance, researchers have developed improved methods such as nonsingular terminal sliding mode (NTSM), recursive sliding mode, and recursive nonsingular terminal sliding mode to eliminate singularities, accelerate the convergence process, and suppress chattering. Meanwhile, adaptive sliding mode control (ASMC) enhances its adaptability to uncertainties and disturbances by adjusting the control gain online. Furthermore, sliding mode observer techniques have been introduced to estimate system uncertainties and external disturbances, with adaptive sliding mode observers enabling efficient estimation of complex disturbances without requiring precisely known upper bounds on the disturbances.

[0005] However, existing technologies still have the following shortcomings: Insufficient convergence time preset capability: Although existing fixed-time sliding mode control methods can ensure that the system convergence time is independent of the initial state, its upper limit of convergence time still depends on the selection of controller parameters and cannot be directly and explicitly specified by the user according to task requirements. This limitation is particularly prominent in task scenarios requiring precise synchronization or multi-machine collaboration. Imperfect disturbance estimation and compensation mechanisms: Most methods rely on the assumption that the upper bound of the disturbance or uncertainty is known or constant, or only adaptively estimate the disturbance amplitude, while paying insufficient attention to the upper bound estimation of the disturbance dynamics (such as derivatives). This may lead to performance degradation or even instability in high-frequency or rapidly changing disturbance environments. Insufficient integration of observer and controller: In the composite framework integrating observer and controller, the impact of observer estimation error on the controller is often not fully handled, and there is a lack of online adaptive mechanisms for the upper bound of estimation error, making it impossible to guarantee the robustness of the controller when the observation accuracy fluctuates. Limited Capabilities in Handling Complex Disturbances During Transition Phases: Existing research largely focuses on single-mode or simple disturbance scenarios, and the observation and compensation mechanisms for complex disturbances, mismatch uncertainties, and rapidly time-varying characteristics encountered by tiltrotor UAVs during transition phases remain insufficient. How to ensure rapid and accurate attitude tracking of tiltrotor UAVs during transition phases while achieving predetermined convergence independent of control parameters, and effectively handling complex disturbances and mismatch uncertainties, is a pressing technical problem to be solved in this field. Summary of the Invention

[0006] The present invention aims to solve the above-mentioned problems existing in the prior art, and provides a disturbance rejection control method, system and UAV for the transition state of tilt-rotor UAV, so as to achieve rapid and accurate estimation of unknown disturbances and ensure that the attitude tracking error converges within a predetermined time.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A disturbance rejection control method for the transition state of a tiltrotor unmanned aerial vehicle (UAV) includes the following steps:

[0009] S1. Establish a dynamic model of the tiltrotor UAV in the transition state and decouple it into an attitude loop subsystem containing lumped disturbances;

[0010] S2. Design an adaptive sliding mode observer to estimate the lumped disturbance contained in the attitude loop subsystem in step S1 in real time.

[0011] S3. Design a pre-time recursive non-singular terminal sliding mode controller and introduce a pre-time performance function to constrain the attitude tracking error;

[0012] S4. Feedforward compensation of the disturbance estimate obtained by the adaptive sliding mode observer in step S2 to the predetermined time recursive non-singular terminal sliding mode controller designed in step S3, and introduce an adaptive compensation mechanism to estimate the observer residual error online and generate virtual control torque command.

[0013] S5. Control the tiltrotor UAV using the virtual control torque command obtained in step S4.

[0014] Furthermore, the specific process of step S1 is as follows:

[0015] First, establish the relevant coordinate system for the tilt-rotor UAV, defining three coordinate systems:

[0016] Ground inertial coordinate system :origin For a fixed point on the ground, The axis points north geographically. The axis points eastward. The axis points vertically downwards towards the Earth's center.

[0017] Body coordinate system :origin Located at the center of mass of the drone, The shaft points towards the machine head along the longitudinal axis of the machine body. The axis points to the right side of the fuselage. The axis is perpendicular to the right-hand rule. The plane is facing downwards.

[0018] Rotor coordinate system :origin Located at the center of each rotor, for tilting rotors Its coordinate system tilts with the rotor; for a fixed rotor Its coordinate system is parallel to the body coordinate system.

[0019] S1-2. Establish the six-degree-of-freedom nonlinear dynamic equations of the tiltrotor UAV in the body coordinate system. Based on rigid body dynamics and the Newton-Euler equations, decouple the six-degree-of-freedom nonlinear dynamic equations into a position loop subsystem and an attitude loop subsystem. The specific process of step S1-2 is as follows:

[0020] The attitude of a drone is described by three Euler angles of the body coordinate system relative to the ground coordinate system: roll angle (around) (axis), pitch angle (around) (axis) and yaw angle (around) (axis). Transformation matrix from ground coordinate system to body coordinate system. for:

[0021]

[0022] in The transformation matrix from rotor coordinate system to body coordinate system is:

[0023]

[0024] The transformation matrix from the body coordinate system to the ground coordinate system is:

[0025]

[0026] in For Euler angles.

[0027] Based on the Newton-Euler equations, the translational and rotational dynamics of the six-degree-of-freedom UAV in the body coordinate system are as follows:

[0028]

[0029]

[0030] Among them, external force Including gravity Rotor thrust Harmony and Energy :

[0031]

[0032] in

[0033]

[0034]

[0035]

[0036] in, For the thrust of each rotor, The tensile coefficient, For the rotational speed of each rotor, For dynamic pressure, Airspeed, Where S is the air density and S is the wing reference area. , , These are the drag, lateral force, and lift coefficients, respectively.

[0037] The net external torque M includes the torque generated by the rotor system. and aerodynamic torque :

[0038]

[0039] Among them, rotor torque Torque generated by tension and counter torque constitute:

[0040]

[0041]

[0042]

[0043]

[0044] in, Let each rotor center be a position vector from its center of mass. The inverse torque coefficient is denoted as , where For wingspan, For the average aerodynamic chord length, , , These are the roll, pitch, and yaw moment coefficients, respectively.

[0045] S1-3. Simplifying the attitude loop subsystem, we obtain the form of a second-order subsystem containing Coriolis terms, gyroscopic effect terms, and unknown lumped perturbations:

[0046]

[0047] in Indicates the roll, pitch, and yaw angles of the aircraft. These are the components of roll, pitch, and yaw angular velocities along the airframe axis, respectively. , , , , , For rotational inertia, For virtual roll control torque, , To centralize interference, It refers to the unmodeled system dynamics (including model parameter uncertainties, gyroscopic effects, aerodynamic damping, etc.). It is an external disturbance.

[0048] Furthermore, the specific process of step S2 is as follows:

[0049] S2-1. Design a sliding mode observer structure to make preliminary estimates of attitude angular velocity and lumped disturbance.

[0050] S2-2. Design an adaptive law to learn the upper bound of the perturbation derivative online, and incorporate the upper bound of the perturbation derivative into the sliding mode gain to overcome the dependence of the traditional sliding mode observer on the known upper bound of the perturbation derivative.

[0051] S2-3. The adaptive sliding mode observer is constructed in the following form:

[0052]

[0053] in , For angular velocity estimation error, For sliding mode, It is the observer gain parameter. The upper bound of the derivative of adaptive disturbance, i.e. , , For rotor-related uncertainties, denoted as

[0054]

[0055] Furthermore, the specific process of step S3 is as follows:

[0056] S3-1. Design a predetermined time performance function to convert constrained attitude tracking error into unconstrained conversion error through error transformation;

[0057] S3-2. Construct a first-level sliding surface based on the aforementioned conversion error;

[0058] S3-3. Based on the first-level sliding surface, a second-level and a third-level sliding surface are constructed through recursive integration to form a recursive sliding structure.

[0059] Furthermore, in step S3-1, the predetermined time performance function Defined as

[0060]

[0061] in , , , Let represent the initial error value and the expected maximum steady-state error, respectively, and satisfy . , This indicates the scheduled convergence time.

[0062] Conversion error Defined as:

[0063]

[0064] in , which are the error constraint boundary coefficients, are transformed to constrain the tracking error. Convert to unconstrained conversion error . The first derivative with respect to time is

[0065]

[0066] The second derivative with respect to time is

[0067]

[0068] in , .

[0069] Furthermore, in steps S3-2 and S3-3, the recursive sliding surface is constructed as follows:

[0070] Primary sliding surface:

[0071]

[0072] in It is a parameter used to adjust the convergence rate. Then, considering the zero convergence of the sliding surface, the following recursive integral second-order and third-order sliding surfaces are proposed respectively.

[0073]

[0074]

[0075] in , This is the integral index.

[0076] Furthermore, the specific process of step S4 is as follows:

[0077] S4-1. Design the equivalent control part, and add the disturbance estimate obtained in step S2 as a feedforward compensation term to the control law.

[0078] S4-2. Design the switching control section and introduce the upper bound of the residual estimation error of the adaptive sliding mode observer in the adaptive gain online estimation step S2;

[0079] S4-3. Superimpose the equivalent control part with the switching control part to generate the final virtual control torque command. The control law form is as follows:

[0080]

[0081] Among them, the equivalent control part for:

[0082]

[0083] Switching control section for:

[0084]

[0085] in , , , , , This is the scheduled convergence time. The adaptive gain to compensate for the residual error of the observer is given by the adaptive law as follows: ,in It is adaptive gain. It is the attenuation coefficient.

[0086] Furthermore, the specific process of step S5 is as follows:

[0087] S5-1. Based on the current flight mode and the nose rotor tilt angle, dynamically calculate the control weight coefficient between the propulsion system and the aerodynamic control surfaces;

[0088] S5-2. Based on the control weight coefficient and the preset allocation matrix, the virtual control torque command is parsed into the rotation speed command of each rotor and the deflection command of each aerodynamic control surface.

[0089] S5-3. Send the rotation speed command and yaw command to the corresponding actuators to complete the attitude control of the UAV.

[0090] The present invention also provides a tilt-rotor unmanned aerial vehicle (UAV) anti-interference control system, comprising:

[0091] The model input module is used to receive the attitude loop subsystem model of the tiltrotor UAV in the transition state;

[0092] An adaptive sliding mode observer, connected to the model input module, is used to estimate the lumped disturbance contained in the attitude loop subsystem in real time.

[0093] A pre-defined time recursive non-singular terminal sliding mode controller is connected to the model input module and the adaptive sliding mode observer, respectively, to generate virtual control torque commands;

[0094] The control distribution module, connected to the predetermined time recursive non-singular terminal sliding mode controller, is used to distribute virtual control torque commands to the actuators of the UAV.

[0095] The present invention also provides a tiltrotor unmanned aerial vehicle (UAV) including the above-described anti-interference control system.

[0096] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method.

[0097] Compared with the prior art, the present invention has the following beneficial effects:

[0098] (1) By designing an adaptive sliding mode observer, the upper bound of the perturbation derivative is learned online, which overcomes the strong assumption that the traditional sliding mode observer needs to know the upper bound of the perturbation derivative in advance, and improves the adaptability and estimation accuracy of the observer in time-varying perturbation environment.

[0099] (2) By designing a pre-time recursive non-singular terminal sliding mode controller and introducing a pre-time performance function, the convergence time of the attitude tracking error can be directly preset by the user and is independent of the initial state of the system, thereby enhancing the predictability of the control.

[0100] (3) By using a three-level recursive sliding surface design, the “arrival stage” of sliding mode control is effectively eliminated, the convergence process is accelerated, and the singularity problem of traditional terminal sliding mode is avoided.

[0101] (4) By introducing an adaptive compensation mechanism to estimate the residual error of the observer online and integrating it into the switching control part, a three-layer disturbance rejection structure of "observation-feedforward compensation-feedback adaptation" is formed, which significantly enhances the robustness to unmodeled dynamics and observation errors. Attached Figure Description

[0102] Figure 1 This is a schematic diagram of the tilt-rotor quadcopter UAV structure, coordinate axes, and flight attitude angles used in this invention;

[0103] Figure 2This is a schematic diagram of the system based on an adaptive sliding mode observer and a recursive non-singular terminal sliding mode controller based on a predetermined time, according to the present invention.

[0104] Figure 3 This is a schematic diagram of the adaptive sliding mode observer of the present invention;

[0105] Figure 4 This is a schematic diagram of the recursive nonsingular terminal sliding mode controller based on a predetermined time according to the present invention.

[0106] Figure 5 The above is the attitude angle response curve of the longitudinal model of the tilting quadcopter UAV under external wind disturbance in a specific embodiment. Figure 6 Here is the convergence curve of attitude tracking error, where , , These represent the attitude angle tracking errors for the roll, pitch, and yaw channels, respectively. For predetermined time performance functions; Figure 7 The response curve of the adaptive sliding mode observer to external disturbances. Detailed Implementation

[0107] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings. Those skilled in the art should understand that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0108] Example 1: Disturbance Rejection Control Method for the Transition State of a Tiltrotor Unmanned Aerial Vehicle

[0109] This embodiment provides a disturbance rejection control method for the transition state of a tiltrotor unmanned aerial vehicle (UAV), including the following steps:

[0110] Step S1: Establish a dynamic model

[0111] S1-1. First, establish the relevant coordinate system for the tilt-rotor UAV, defining three coordinate systems:

[0112] Ground inertial coordinate system :origin For a fixed point on the ground, The axis points north geographically. The axis points eastward. The axis points vertically downwards towards the Earth's center.

[0113] Body coordinate system :origin Located at the center of mass of the drone, The shaft points towards the machine head along the longitudinal axis of the machine body. The axis points to the right side of the fuselage. The axis is perpendicular to the right-hand rule. The plane is facing downwards.

[0114] Rotor coordinate system :origin Located at the center of each rotor, for tilting rotors Its coordinate system tilts with the rotor; for a fixed rotor Its coordinate system is parallel to the body coordinate system.

[0115] S1-2. Establish the six-degree-of-freedom nonlinear dynamic equations of the tiltrotor UAV in the body coordinate system. Based on rigid body dynamics and the Newton-Euler equations, decouple the six-degree-of-freedom nonlinear dynamic equations into a position loop subsystem and an attitude loop subsystem. The specific process of step S1-2 is as follows:

[0116] The attitude of a drone is described by three Euler angles of the body coordinate system relative to the ground coordinate system: roll angle (around) (axis), pitch angle (around) (axis) and yaw angle (around) (axis). Transformation matrix from ground coordinate system to body coordinate system. for:

[0117]

[0118] in The transformation matrix from rotor coordinate system to body coordinate system is:

[0119]

[0120] The transformation matrix from the body coordinate system to the ground coordinate system is:

[0121]

[0122] in For Euler angles.

[0123] Based on the Newton-Euler equations, the translational and rotational dynamics of the six-degree-of-freedom UAV in the body coordinate system are as follows:

[0124]

[0125]

[0126] Among them, external force Including gravity Rotor thrust Harmony and Energy :

[0127]

[0128] in

[0129]

[0130]

[0131]

[0132] in, For the thrust of each rotor, The tensile coefficient, For the rotational speed of each rotor, For dynamic pressure, Airspeed, Where S is the air density and S is the wing reference area. , , These are the drag, lateral force, and lift coefficients, respectively.

[0133] The net external torque M includes the torque generated by the rotor system. and aerodynamic torque :

[0134]

[0135] Among them, rotor torque Torque generated by tension and counter torque constitute:

[0136]

[0137]

[0138]

[0139]

[0140] in, Let each rotor center be a position vector from its center of mass. The inverse torque coefficient is denoted as , where For wingspan, For the average aerodynamic chord length, , , These are the roll, pitch, and yaw moment coefficients, respectively. S1-3. Simplifying the attitude loop subsystem, we obtain the second-order subsystem form containing the Coriolis term, gyroscopic effect term, and unknown lumped disturbance as follows:

[0141]

[0142] in Indicates the roll, pitch, and yaw angles of the aircraft. These are the components of roll, pitch, and yaw angular velocities along the airframe axis, respectively. , , , , , For rotational inertia, For virtual roll control torque, , To centralize interference, It refers to the unmodeled system dynamics (including model parameter uncertainties, gyroscopic effects, aerodynamic damping, etc.). It is an external disturbance.

[0143] Step S2: Design an adaptive sliding mode observer

[0144] S2-1. Design a sliding mode observer structure to make preliminary estimates of attitude angular velocity and lumped disturbance.

[0145] S2-2. Design an adaptive law to learn the upper bound of the perturbation derivative online, and incorporate the upper bound of the perturbation derivative into the sliding mode gain to overcome the dependence of the traditional sliding mode observer on the known upper bound of the perturbation derivative.

[0146] S2-3. The adaptive sliding mode observer is constructed in the following form:

[0147]

[0148] in , For angular velocity estimation error, For sliding mode, It is the observer gain parameter. The upper bound of the derivative of adaptive disturbance, i.e. , , For rotor-related uncertainties, denoted as

[0149]

[0150] Step S3: Design a pre-defined time recursive non-singular terminal sliding mode controller

[0151] S3-1. Design a predetermined time performance function to convert constrained attitude tracking error into unconstrained conversion error through error transformation;

[0152] S3-2. Construct a first-level sliding surface based on the aforementioned conversion error;

[0153] S3-3. Based on the first-level sliding surface, a second-level and a third-level sliding surface are constructed through recursive integration to form a recursive sliding structure.

[0154] Furthermore, in step S3-1, the predetermined time performance function Defined as

[0155] in , , , Let represent the initial error value and the expected maximum steady-state error, respectively, and satisfy . , This indicates the scheduled convergence time.

[0156] Conversion error Defined as:

[0157]

[0158] in , which are the error constraint boundary coefficients, are transformed to constrain the tracking error. Convert to unconstrained conversion error . The first derivative with respect to time is

[0159]

[0160] The second derivative with respect to time is

[0161]

[0162] in , .

[0163] Furthermore, in steps S3-2 and S3-3, the recursive sliding surface is constructed as follows:

[0164] Primary sliding surface:

[0165]

[0166] in It is a parameter used to adjust the convergence rate. Then, considering the zero convergence of the sliding surface, the following recursive integral second-order and third-order sliding surfaces are proposed respectively.

[0167]

[0168]

[0169] in , This is the integral index.

[0170] Step S4: Generate virtual control torque command

[0171] S4-1. Design the equivalent control part, and add the disturbance estimate obtained in step S2 as a feedforward compensation term to the control law.

[0172] S4-2. Design the switching control section and introduce the upper bound of the residual estimation error of the adaptive sliding mode observer in the adaptive gain online estimation step S2;

[0173] S4-3. Superimpose the equivalent control part with the switching control part to generate the final virtual control torque command. The control law form is as follows:

[0174]

[0175] Among them, the equivalent control part for:

[0176]

[0177] Switching control section for:

[0178]

[0179] in , , , , , This is the scheduled convergence time. The adaptive gain to compensate for the residual error of the observer is given by the adaptive law as follows: ,in It is adaptive gain. It is the attenuation coefficient.

[0180] Step S5: Control Allocation

[0181] S5-1. Based on the current flight mode and the nose rotor tilt angle, dynamically calculate the control weight coefficient between the propulsion system and the aerodynamic control surfaces;

[0182] S5-2. Based on the control weight coefficient and the preset allocation matrix, the virtual control torque command is parsed into the rotation speed command of each rotor and the deflection command of each aerodynamic control surface.

[0183] S5-3. Send the rotation speed command and yaw command to the corresponding actuators to complete the attitude control of the UAV.

[0184] Example 2: Anti-disturbance control system for tilt-rotor UAVs

[0185] This embodiment provides a tilt-rotor unmanned aerial vehicle (UAV) anti-interference control system, including:

[0186] The model input module is used to receive the attitude loop subsystem model of the tiltrotor UAV in the transition state;

[0187] An adaptive sliding mode observer, connected to the model input module, is used to execute step S2;

[0188] A pre-defined time recursive non-singular terminal sliding mode controller is connected to the model input module and the adaptive sliding mode observer, respectively, to execute steps S3 and S4;

[0189] The control allocation module is connected to the pre-defined time recursive non-singular terminal sliding mode controller and is used to execute step S5.

[0190] Example 3: Tiltrotor Unmanned Aerial Vehicle

[0191] This embodiment provides a tiltrotor unmanned aerial vehicle (UAV) including an anti-interference control system as described in Embodiment 2.

[0192] Example 4: Computer-readable storage medium

[0193] This embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in Embodiment 1.

[0194] To verify the effectiveness of this invention, numerical simulations were performed in the MATLAB / Simulink environment. The simulation parameters were set as follows: UAV mass... Moment of inertia , , Initial attitude angle Desired attitude angle .

[0195] Observer parameters , , , , , The controller parameters are , , , , , , .

[0196] Predetermined performance function parameters , , .

[0197] To verify the estimation performance of the adaptive sliding mode observer for external disturbances, the external disturbance is given as:

[0198]

[0199]

[0200]

[0201] Meanwhile, the process of tilt angle change of the tilting UAV is given as follows:

[0202]

[0203]

[0204]

[0205] During the transition phase During the transition phase The entire transition process is simulated, with 6 to 16 seconds representing the transition phase and 20 to 24 seconds representing the re-transition phase.

[0206] Figure 5 In the figure, Figure (a) is the attitude angle response curve, in which the attitude angle of the tilting quadcopter UAV converges to the target value within a predetermined time. Figure (b) is the attitude tracking error convergence curve, in which the attitude angle converges to within a preset value within a predetermined time. Figure (c) is the response curve of the adaptive sliding mode observer to external disturbances, in which the adaptive sliding mode observer of the present invention achieves accurate tracking of external disturbances.

[0207] The above description is merely a preferred embodiment of the present invention and does not limit the scope of the patent. Any equivalent structural transformations made based on the technical concept of the present invention and the description and drawings, or direct / indirect applications in other related technical fields, are included within the scope of patent protection of the present invention.

Claims

1. A disturbance rejection control method for the transition state of a tiltrotor unmanned aerial vehicle (UAV), characterized in that, Includes the following steps: S1. Establish a dynamic model of the tiltrotor UAV in the transition state and decouple it into an attitude loop subsystem containing lumped disturbances; S2. Design an adaptive sliding mode observer to estimate the lumped disturbance contained in the attitude loop subsystem in step S1 in real time. S3. Design a pre-time recursive non-singular terminal sliding mode controller and introduce a pre-time performance function to constrain the attitude tracking error. S4. Feedforward compensation of the disturbance estimate obtained by the adaptive sliding mode observer in step S2 to the predetermined time recursive non-singular terminal sliding mode controller designed in step S3, and introduce an adaptive compensation mechanism to estimate the observer residual error online and generate virtual control torque command. S5. Control the tiltrotor UAV using the virtual control torque command obtained in step S4.

2. The anti-disturbance control method for the transition state of a tilt-rotor UAV according to claim 1, characterized in that, The specific process of step S1 is as follows: S1-1. First, establish the relevant coordinate system for the tilt-rotor UAV, defining three coordinate systems: Ground inertial coordinate system :origin For a fixed point on the ground, The axis points north geographically. The axis points eastward. The axis points vertically downwards towards the Earth's center. Body coordinate system :origin Located at the center of mass of the drone, The shaft points towards the machine head along the longitudinal axis of the machine body. The axis points to the right side of the fuselage. The axis is perpendicular to the right-hand rule. The plane is facing downwards. Rotor coordinate system :origin Located at the center of each rotor, for tilting rotors Its coordinate system tilts with the rotor; for a fixed rotor Its coordinate system is parallel to the body coordinate system. S1-2. Establish the six-degree-of-freedom nonlinear dynamic equations of the tiltrotor UAV in the body coordinate system. Based on rigid body dynamics and the Newton-Euler equations, decouple the six-degree-of-freedom nonlinear dynamic equations into a position loop subsystem and an attitude loop subsystem. The specific process of step S1-2 is as follows: The attitude of a drone is described by three Euler angles of the body coordinate system relative to the ground coordinate system: roll angle (around) (axis), pitch angle (around) (axis) and yaw angle (around) (axis). Transformation matrix from ground coordinate system to body coordinate system. for: in The transformation matrix from rotor coordinate system to body coordinate system is: The transformation matrix from the body coordinate system to the ground coordinate system is: in For Euler angles. Based on the Newton-Euler equations, the translational and rotational dynamics of the six-degree-of-freedom UAV in the body coordinate system are as follows: Among them, external force Including gravity Rotor thrust Harmony and Energy : in in, For the thrust of each rotor, The tensile coefficient, For the rotational speed of each rotor, For dynamic pressure, Airspeed, Where S is the air density and S is the wing reference area. , , These are the drag, lateral force, and lift coefficients, respectively. The net external torque M includes the torque generated by the rotor system. and aerodynamic torque : Among them, rotor torque Torque generated by tension and counter torque constitute: in, Let each rotor center be a position vector from its center of mass. The inverse torque coefficient is denoted as , where For wingspan, For the average aerodynamic chord length, , , These are the roll, pitch, and yaw moment coefficients, respectively. S1-3. Simplifying the attitude loop subsystem, we obtain the form of a second-order subsystem containing Coriolis terms, gyroscopic effect terms, and unknown lumped perturbations: in Indicates the roll, pitch, and yaw angles of the aircraft. These are the components of roll, pitch, and yaw angular velocities along the airframe axis, respectively. , , , , , For rotational inertia, For virtual roll control torque, , To centralize interference, It refers to the unmodeled system dynamics (including model parameter uncertainties, gyroscopic effects, aerodynamic damping, etc.). It is an external disturbance.

3. The anti-disturbance control method for the transition state of a tiltrotor UAV according to claim 2, characterized in that, The specific process of step S2 is as follows: S2-1. Design a sliding mode observer structure to make preliminary estimates of attitude angular velocity and lumped disturbance. S2-2. Design an adaptive law to learn the upper bound of the perturbation derivative online and dynamically adjust the gain of the sliding mode observer according to the upper bound. S2-3. The adaptive sliding mode observer is constructed in the following form: in , For angular velocity estimation error, For sliding mode, It is the observer gain parameter. The upper bound of the derivative of adaptive disturbance, i.e. , , For rotor-related uncertainties, denoted as 4. The anti-disturbance control method for the transition state of a tiltrotor UAV according to claim 3, characterized in that, The specific process of step S3 is as follows: S3-1. Design a predetermined time performance function to convert constrained attitude tracking error into unconstrained conversion error through error transformation; S3-2. Construct a first-level sliding surface based on the aforementioned conversion error; S3-3. Based on the first-level sliding surface, a second-level and a third-level sliding surface are constructed through recursive integration to form a recursive sliding structure.

5. The anti-disturbance control method for the transition state of a tiltrotor unmanned aerial vehicle according to claim 4, characterized in that, In step S3-1, the predetermined time performance function Defined as in , , , Let represent the initial error value and the expected maximum steady-state error, respectively, and satisfy . , This indicates the scheduled convergence time. Conversion error Defined as: in , which are the error constraint boundary coefficients, are transformed to constrain the tracking error. Convert to unconstrained conversion error . The first derivative with respect to time is The second derivative with respect to time is in , .

6. The anti-disturbance control method for the transition state of a tiltrotor unmanned aerial vehicle according to claim 5, characterized in that, In steps S3-2 and S3-3, the recursive sliding surface is constructed as follows: Primary sliding surface: in It is a parameter used to adjust the convergence rate. Then, considering the zero convergence of the sliding surface, the following recursive integral second-order and third-order sliding surfaces are proposed respectively. in , .

7. The anti-disturbance control method for the transition state of a tilt-rotor UAV according to claim 6, characterized in that, The specific process of step S4 is as follows: S4-1. Design the equivalent control part, and add the disturbance estimate obtained in step S2 as a feedforward compensation term to the control law. S4-2. Design the switching control section and introduce the upper bound of the residual estimation error of the adaptive sliding mode observer in the adaptive gain online estimation step S2; S4-3. Superimpose the equivalent control part with the switching control part to generate the final virtual control torque command. The control law form is as follows: Among them, the equivalent control part for: Switching control section for: in , , , , , This is the scheduled convergence time. The adaptive gain to compensate for the residual error of the observer is given by the adaptive law as follows: ,in It is adaptive gain. It is the attenuation coefficient.

8. The anti-disturbance control method for the transition state of a tiltrotor unmanned aerial vehicle according to claim 7, characterized in that, The specific process of step S5 is as follows: S5-1. Based on the current flight mode and the nose rotor tilt angle, dynamically calculate the control weight coefficient between the propulsion system and the aerodynamic control surfaces; S5-2. Based on the control weight coefficient and the preset allocation matrix, the virtual control torque command is parsed into the rotation speed command of each rotor and the deflection command of each aerodynamic control surface. S5-3. Send the rotation speed command and yaw command to the corresponding actuators to complete the attitude control of the UAV.

9. A tilt-rotor unmanned aerial vehicle (UAV) anti-interference control system, characterized in that, include: The model input module is used to receive the attitude loop subsystem model of the tiltrotor UAV in the transition state; An adaptive sliding mode observer, connected to the model input module, is used to perform step S2 as described in claim 1, to estimate the lumped disturbance contained in the attitude loop subsystem in real time. A pre-defined time recursive non-singular terminal sliding mode controller is connected to the model input module and the adaptive sliding mode observer, respectively, to execute steps S3 and S4 as described in claim 1, and generate virtual control torque commands; The control allocation module, connected to the predetermined time recursive non-singular terminal sliding mode controller, is used to perform step S5 as described in claim 1, allocating virtual control torque commands to the actuators of the UAV.

10. A tilt-rotor unmanned aerial vehicle, characterized in that, Including the tilt-rotor unmanned aerial vehicle anti-interference control system as described in claim 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the disturbance rejection control method for the transition state of a tiltrotor unmanned aerial vehicle as described in any one of claims 1-8.

Images