Multi-path collaborative disturbance cancellation trajectory tracking control method for wing-body fusion UAV platform

Abstract

This invention proposes a multi-path collaborative disturbance mitigation trajectory tracking control method for a wing-body fusion UAV platform. First, a six-degree-of-freedom dynamic model of a low-altitude wing-body fusion UAV is established, and a trim analysis is performed at a reference state point to obtain the trim parameters at the reference state point. The UAV's outer-loop trajectory guidance layer is constructed, and longitudinal and lateral tracking modules are designed separately. Based on the desired speed and altitude, the corresponding desired thrust and desired pitch angle are generated, and based on the desired trajectory, the corresponding desired roll angle is generated. Finally, the UAV's attitude control layer is constructed, and an attitude stabilization loop and an anti-disturbance compensation loop are designed separately. The equivalent rudder deflection angle corresponding to the desired pitch angle and desired roll angle is obtained to achieve control of the UAV. This method provides an anti-disturbance trajectory tracking control strategy for low-altitude wing-body fusion UAVs, improving their control robustness and enabling them to maintain stable flight in complex low-altitude wind environments and accurately track the desired trajectory.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft control and guidance, and specifically relates to a multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion unmanned aerial vehicle platform. Background Art

[0002] The wing-body fusion UAV has a clean overall appearance and excellent aerodynamic characteristics. This layout has the advantages of a high lift-to-drag ratio, a long cruising range, and a long endurance. At the same time, the lightweight flying wing layout UAV has strong low-altitude flight capabilities and is suitable for low-altitude airspace operations. It has broad application prospects and is an important technical foundation for the current development of the low-altitude economy. Low-altitude flying wing layout UAVs have significant innovative research significance. In the civilian field, this type of UAV is a low-cost aerial work platform with a flat and compact structural design. It is suitable for a variety of work scenarios such as aerial photography and mapping, express delivery, power inspection, disaster relief, etc., and has good promotion and application value.

[0003] However, due to the tailless design of low-altitude wing-body fusion UAVs, their control systems are subject to certain limitations. Furthermore, due to factors such as their light weight and small inertia, their inherent stability characteristics are insufficient when affected by external disturbances, making it difficult to recover immediately and maintain stable flight. Furthermore, the low-altitude airspace environment is complex and diverse, and low-altitude wind field disturbances can significantly affect the attitude control and trajectory tracking accuracy of UAVs. This is especially true when performing low-altitude, near-ground flight missions. UAVs lack sufficient space and time to make effective attitude adjustments after being disturbed. Therefore, traditional UAV control algorithms have been unable to meet the control requirements of low-altitude flying-wing layout UAVs. The key technical challenge in this field is how to construct a robust control method with active anti-disturbance capabilities.

[0004] Currently, for the anti-disturbance trajectory tracking control problem of this type of UAV, existing methods mostly focus on the separate optimization of the attitude control layer or the track guidance layer, lack of systematic design, and fail to fully consider the impact of low-altitude disturbances in the trajectory tracking process. For example, in recent years, a variety of algorithms based on sliding mode control, model predictive control and anti-disturbance control theory have been proposed, which mainly enhance flight stability by improving attitude control accuracy, but generally ignore the problem of UAV position deviation under disturbance. At the same time, the commonly used proportional guidance law, Guidance Law and While the guidance law has a certain degree of wind field adaptability, it has not yet fully considered the technical difficulty of actively converging the lateral offset error during low-altitude trajectory tracking for wing-body fusion UAVs. In summary, to address the interference-resistant trajectory tracking problem of low-altitude wing-body fusion UAVs in complex wind environments, it is urgent to design a comprehensive control method that can both enhance attitude control stability and improve low-altitude flight trajectory tracking accuracy. Summary of the Invention

[0005] In response to the problems existing in the prior art, the present invention proposes a multi-channel collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform. A nonlinear disturbance observer with active anti-disturbance capability is designed in the attitude control layer of the UAV, which realizes real-time estimation and feedforward compensation of attitude disturbances; a new nonlinear guidance algorithm with lateral offset compensation is designed in the track guidance layer of the UAV, thereby effectively improving the trajectory tracking accuracy of the UAV. This method provides a new anti-disturbance trajectory tracking control strategy for low-altitude wing-body fusion UAVs, improves the control robustness of wing-body fusion UAVs, enables them to maintain stable flight in low-altitude complex wind field environments, and accurately track the desired trajectory.

[0006] The technical solution of the present invention is:

[0007] A multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform includes the following steps:

[0008] Step 1: Establish a six-degree-of-freedom dynamic model of the low-altitude wing-body fusion UAV and perform a trim analysis at the reference state point to obtain the trim parameters at the reference state point;

[0009] Step 2: Based on the six-degree-of-freedom dynamic model, construct the outer loop trajectory guidance layer of the UAV and design the longitudinal tracking module and the lateral tracking module respectively;

[0010] The longitudinal tracking module is designed based on the total energy control theory. By controlling and distributing the potential energy and kinetic energy of the drone, the altitude and speed are decoupled, so that the desired speed can be achieved. and high expectations , generating the corresponding expected thrust and the desired pitch angle ;

[0011] The lateral tracking module adopts a nonlinear guidance algorithm with side deviation compensation. By dynamically correcting the reference distance, limiting the size of the sight angle, and introducing compensation for the tracking side deviation error, the corresponding desired roll angle is generated according to the desired track. ;

[0012] Step 3: Based on the six-degree-of-freedom dynamics model, construct the attitude control layer of the drone, design the attitude stabilization loop and the anti-disturbance compensation loop respectively, and obtain the desired pitch angle and the desired roll angle The corresponding equivalent rudder deflection angle is used to control the UAV.

[0013] Furthermore, in step 1, when establishing the six-degree-of-freedom dynamic model of the UAV, the UAV is assumed to be a rigid body, and the influence of its structural elasticity and the curvature of the earth is ignored, in line with the "flat earth assumption", and has a longitudinal symmetry plane; and the UAV is only equipped with a set of elevons as control surfaces, and the control efficiency of the elevons is equivalent to the linear superposition of the elevator and the ailerons, realizing the longitudinal and lateral separation of the aerodynamic force solution.

[0014] Furthermore, in step 1, the six-degree-of-freedom dynamic model of the drone is:

[0015]

[0016] Where, is the rolling moment, is the pitching moment, is the yaw moment; For resistance, is the lateral force, for lift; is the angle of attack, is the sideslip angle; is the equivalent elevator full deflection angle, is the equivalent aileron full deflection angle; is the roll angular rate, is the pitch angular rate, is the yaw rate; is the dynamic pressure, is the wing reference area, is the mean aerodynamic chord length, For the exhibition length; 、 、 and They are the aerodynamic derivative of sideslip angle relative to rolling moment, the aerodynamic derivative of equivalent aileron deflection angle relative to rolling moment, the aerodynamic derivative of roll angular rate relative to rolling moment, and the aerodynamic derivative of yaw angular rate relative to rolling moment. 、 and They are the aerodynamic derivative of the angle of attack relative to the pitching moment, the aerodynamic derivative of the equivalent elevator deflection angle relative to the pitching moment, and the aerodynamic derivative of the pitch angular rate relative to the pitching moment. 、 、 and They are the aerodynamic derivative of sideslip angle relative to yaw moment, the aerodynamic derivative of equivalent aileron deflection angle relative to yaw moment, the aerodynamic derivative of yaw angular rate relative to yaw moment and the aerodynamic derivative of roll angular rate relative to yaw moment. 、 and They are the aerodynamic derivative of the angle of attack relative to the drag, the aerodynamic derivative of the equivalent elevator deflection angle relative to the drag, and the aerodynamic derivative of the equivalent aileron deflection angle relative to the drag; and They are the aerodynamic derivative of the sideslip angle relative to the side force and the aerodynamic derivative of the equivalent aileron deflection angle relative to the side force; 、 and They are the aerodynamic derivative of the angle of attack relative to lift, the aerodynamic derivative of the equivalent elevator deflection angle relative to lift, and the aerodynamic derivative of the equivalent aileron deflection angle relative to lift.

[0017] Furthermore, in step 2, the expected thrust obtained by the longitudinal tracking module and the desired pitch angle Expressed as:

[0018]

[0019]

[0020] in To balance the thrust, To trim the pitch angle; is the expected thrust increment, is the desired pitch angle increment, according to the formula

[0021]

[0022] Get, among them is the control channel proportional gain parameter, is the control channel integral gain parameter, To allocate channel proportional gain parameters, To allocate channel integral gain parameters; is the track angle error, is the speed change rate error, is the acceleration due to gravity, is the rate of change of track angle error, is the speed error control term.

[0023] Furthermore, in the longitudinal tracking module, the speed error control term

[0024]

[0025] In the formula is the proportional gain parameter of the velocity error, is the expected speed, is the actual flight speed.

[0026] Furthermore, in the longitudinal tracking module, the track angle error change rate

[0027]

[0028] In the formula is the height error change rate, is the height error, is the proportional gain parameter of the height error, is the actual flight speed.

[0029] Furthermore, in step 2, the desired roll angle obtained by the lateral tracking module Expressed as

[0030]

[0031] In the formula is the acceleration due to gravity, is the lateral acceleration after compensation, according to the formula

[0032]

[0033] Get, among them is the drone ground speed, is the corrected distance between the UAV and the virtual target point, is the sight angle, and the virtual target point is a point selected on the desired trajectory; is the gain parameter of the integral term of the lateral deviation error, is the measured trajectory deviation distance error during the tracking process.

[0034] Furthermore, in the lateral tracking module, the distance between the corrected drone and the virtual target point

[0035]

[0036] in is the actual track angle, is the forward projection length of the UAV along the desired trajectory, according to the formula

[0037]

[0038] Value, where is the vertical distance between the UAV and the desired trajectory, is a vector The maximum angle between the vector and the desired trajectory The direction is from the UAV to the virtual target point, Define the parameters for the set distance, is the distance between the UAV and the virtual target point.

[0039] Furthermore, in the lateral tracking module, the sight angle Maximum viewing angle limit:

[0040]

[0041] in is the maximum roll angle of the UAV, For thrust.

[0042] Furthermore, in step 3, the final result is The equivalent rudder deflection angle at the moment is divided into The equivalent elevator full deflection angle at time and The equivalent aileron full deflection angle at time :

[0043]

[0044]

[0045] in for The equivalent elevator basic deflection angle at time , for The equivalent elevator compensation angle at time , for The equivalent aileron basic deflection angle at time , for The equivalent aileron compensation deflection angle at the moment;

[0046] The equivalent elevator basic deflection angle at the time is based on Expected pitch angle at time , according to the formula

[0047]

[0048] Calculated;

[0049] The equivalent aileron basic deflection angle at the moment is based on Expected roll angle at time , according to the formula

[0050]

[0051] Calculated; where, for The expected pitch rate at time , for The expected roll rate at time t; is the pitch angle proportional control gain parameter, is the roll angle proportional control gain parameter; is the pitch angle integral control gain parameter, is the roll angle integral control gain parameter; for The desired pitch angle at the moment, for The expected roll angle at the moment; for The actual pitch angle at the moment, for The actual roll angle at the moment; for The equivalent elevator basic deflection angle at time , for The equivalent aileron basic deflection angle at the moment; is the equivalent elevator trim angle, Trim the deflection angle for the equivalent aileron; is the pitch angle rate proportional control gain parameter, is the roll angular rate proportional control gain parameter; is the pitch angle rate integral control gain parameter, is the roll angular rate integral control gain parameter; for The actual pitch rate at the moment, for The actual roll angular rate at the moment;

[0052] Equivalent elevator compensation angle at time According to the formula

[0053]

[0054] Calculated; where is the equivalent elevator control efficiency, for The estimated value of the external longitudinal disturbance torque on the UAV at the moment:

[0055]

[0056] in and The nonlinear disturbance observer of the pitch angle compensation channel is obtained through iterative calculation. The nonlinear disturbance observer of the pitch angle compensation channel is:

[0057] { p t i = m i ˙ t − 1 z ˙ t i =− m [ ( I zzz − I xx ) ϕ ˙ t − 1 ψ ˙ t − 1 I yyy + L d e d e , ( t − 1 ) final I yyy + m i ˙ t − 1 I yyy ] − m z t − 1 i I yyy

[0058] Where, for The first nonlinear reaching law function at time, is the set nonlinear gain parameter, for The intermediate variable of the disturbance observer of the pitch angle compensation channel at the moment is obtained by taking the derivative of the intermediate variable Integrate to get , for The actual pitch angular velocity at the moment, for The actual roll angular velocity at the moment, for The actual yaw rate at the moment; is the moment of inertia of the drone around the x-axis of the body axis, is the moment of inertia of the drone around the y-axis of the body axis, is the moment of inertia of the drone around the z-axis of the body axis; for The equivalent elevator full deflection angle at time , for The intermediate variable of the disturbance observer of the pitch angle compensation channel at each moment;

[0059] The equivalent aileron compensation angle at time According to the formula

[0060]

[0061] Calculated; where is the equivalent aileron control efficiency, for The estimated value of the external lateral disturbance torque on the drone at this moment:

[0062]

[0063] in and The nonlinear disturbance observer of the roll angle compensation channel is obtained through iterative calculation. The nonlinear disturbance observer of the roll angle compensation channel is:

[0064] { p t ϕ = l ϕ ˙ t − 1 z ˙ t ϕ =− l [ ( I yyy − I zzz ) i ˙ t − 1 ψ ˙ t − 1 I xx + L d a d a , ( t − 1 ) final I xx + l ϕ ˙ t − 1 I xx ] − l z t − 1 ϕ I xx

[0065] Where, for The second nonlinear reaching law function of time, is the set nonlinear gain parameter, for The intermediate variable of the disturbance observer of the roll angle compensation channel at the moment is obtained by taking the derivative of the intermediate variable You can get points by ; for The equivalent aileron full deflection angle at time , for The intermediate variable of the disturbance observer of the roll angle compensation channel at time instant.

[0066] Beneficial effects:

[0067] In response to the problems of weak attitude anti-interference ability and insufficient trajectory tracking accuracy of current low-altitude wing-body fusion UAVs, the present invention proposes a multi-channel collaborative disturbance elimination trajectory tracking control method for wing-body fusion UAV platforms. This method introduces active anti-interference control technology based on nonlinear disturbance observer in the attitude control layer, and adopts a guidance strategy with lateral offset compensation in the track guidance layer. Through the division of labor and coordination among multi-level controllers and active anti-interference control, the attitude stability and trajectory tracking accuracy of the wing-body fusion UAV in low-altitude complex disturbance environments are effectively improved, providing a new anti-interference trajectory tracking control strategy for low-altitude wing-body fusion UAVs. The specific advantages are as follows:

[0068] (1) This invention implements anti-interference design from two aspects: the inner attitude control layer and the outer trajectory guidance layer, taking into account the functional characteristics of both, and forming a new multi-level controller. Through the composite nesting of the attitude control layer and the trajectory guidance layer, the UAV can achieve comprehensive anti-interference control in both the inner and outer loops, significantly improving the UAV's flight capability in low-altitude complex environments and ensuring the efficient completion of flight missions. It is particularly suitable for high-precision robust control of low-altitude wing-body fusion UAVs.

[0069] (2) The attitude control layer of the UAV constructs a complete inner-loop control system by designing a stabilization control loop and an anti-disturbance compensation loop. A nonlinear disturbance observer with active anti-disturbance capability is designed, forming a dedicated anti-disturbance compensation loop. This enables the UAV to accurately estimate external disturbances in real time and compensate for disturbances based on the estimated results, thereby effectively improving the attitude control effect of the UAV during low-altitude flight and greatly enhancing flight safety and attitude stability.

[0070] (3) In the UAV's trajectory guidance layer, a longitudinal tracking module and a lateral tracking module are used to track the desired altitude and the desired waypoint, respectively, to construct a complete outer-loop guidance system. A new nonlinear guidance algorithm with lateral offset compensation is designed. This algorithm effectively improves the UAV's trajectory tracking accuracy and anti-interference performance during low-altitude flight. By compensating for lateral offset errors in trajectory tracking in real time, the UAV can accurately track the desired trajectory, thereby significantly improving the accuracy and reliability of trajectory tracking.

[0071] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which:

[0073] Figure 1 This is a schematic diagram of a typical low-altitude wing-body fusion UAV;

[0074] Figure 2 This is the architecture diagram of the outer loop system trajectory guidance layer of the UAV;

[0075] Figure 3 This is the architecture diagram of the attitude control layer of the inner loop system of the UAV;

[0076] Figure 4 The graph of attitude angle changes corresponding to the two control methods under the influence of disturbance;

[0077] Figure 5 This is the estimation diagram of the external disturbance torque by the nonlinear disturbance observer;

[0078] Figure 6 A comparison chart of the tracking effects of the guidance law of the present invention and other guidance laws;

[0079] Figure 7 Figure 1 is a diagram showing the roll angle output of the guidance law of the present invention and other guidance laws;

[0080] Figure 8 This is a comparison chart of the comprehensive trajectory tracking effects of the method of the present invention and the conventional method. DETAILED DESCRIPTION

[0081] The following describes in detail embodiments of the present invention. The embodiments are exemplary and intended to explain the present invention, but are not to be construed as limiting the present invention.

[0082] In this embodiment, a multi-path collaborative disturbance mitigation trajectory tracking control method for a low-altitude wing-body fusion UAV platform is proposed to address the current issues of weak attitude anti-interference capability and insufficient trajectory tracking accuracy. To further illustrate the specific technical solution of this embodiment, the proposed control method will be described in detail in conjunction with the complete trajectory tracking control process of a specific low-altitude wing-body fusion UAV.

[0083] The multi-path collaborative disturbance elimination trajectory tracking control method for the wing-body fusion UAV platform proposed in this embodiment is specifically described as follows:

[0084] Step 1: Establish a six-degree-of-freedom dynamic model of the low-altitude wing-body fusion UAV, and perform a balancing analysis at the reference state point to obtain the balancing parameters at the reference state point.

[0085] In this embodiment, the basic platform for trajectory tracking control analysis is a typical low-altitude wing-body fusion UAV, such as Figure 1 As shown, the drone adopts a flying wing layout with a fused wing and body, resulting in a compact structure and high aerodynamic efficiency. The drone is designed with only one set of elevons as control surfaces, symmetrically arranged on the left and right trailing edges of the wings. A push-back propeller system is installed at the rear of the drone, providing the required forward thrust and ensuring the drone's flight capability.

[0086] When developing the UAV's six-degree-of-freedom dynamic model, the UAV is assumed to be rigid, ignoring the effects of structural elasticity and Earth curvature, conforming to the "flat Earth" assumption and possessing a longitudinal plane of symmetry. Since the UAV is equipped with only one set of elevons as control surfaces, the elevon's control effectiveness is equated to the linear superposition of the elevator and ailerons to achieve longitudinal and lateral separation of the aerodynamic forces. Based on these basic modeling assumptions and dynamic modeling methods, the six-degree-of-freedom UAV dynamic modeling method employed is well-known in the art.

[0087] The UAV's six-degree-of-freedom dynamic model is constructed using an interpolation calculation method based on aerodynamic data. The aerodynamic force and torque calculation formulas used are well-known in the art. However, for the low-altitude wing-body fusion UAV used in this embodiment, the formulas need to be appropriately modified and simplified based on its unique structure and flight characteristics. The specific calculation formula is as follows:

[0088]

[0089] Where, is the rolling moment, is the pitching moment, is the yaw moment; For resistance, is the lateral force, for lift; is the angle of attack, is the sideslip angle; is the equivalent elevator full deflection angle, is the equivalent aileron full deflection angle; is the roll angular rate, is the pitch angular rate, is the yaw rate; is the dynamic pressure, is the wing reference area, is the mean aerodynamic chord length, For the exhibition length; 、 、 and They are the aerodynamic derivative of sideslip angle relative to rolling moment, the aerodynamic derivative of equivalent aileron deflection angle relative to rolling moment, the aerodynamic derivative of roll angular rate relative to rolling moment, and the aerodynamic derivative of yaw angular rate relative to rolling moment. 、 and They are the aerodynamic derivative of the angle of attack relative to the pitching moment, the aerodynamic derivative of the equivalent elevator deflection angle relative to the pitching moment, and the aerodynamic derivative of the pitch angular rate relative to the pitching moment. 、 、 and They are the aerodynamic derivative of sideslip angle relative to yaw moment, the aerodynamic derivative of equivalent aileron deflection angle relative to yaw moment, the aerodynamic derivative of yaw angular rate relative to yaw moment and the aerodynamic derivative of roll angular rate relative to yaw moment. 、 and They are the aerodynamic derivative of the angle of attack relative to the drag, the aerodynamic derivative of the equivalent elevator deflection angle relative to the drag, and the aerodynamic derivative of the equivalent aileron deflection angle relative to the drag; and They are the aerodynamic derivative of the sideslip angle relative to the side force and the aerodynamic derivative of the equivalent aileron deflection angle relative to the side force; 、 and They are the aerodynamic derivative of the angle of attack relative to lift, the aerodynamic derivative of the equivalent elevator deflection angle relative to lift, and the aerodynamic derivative of the equivalent aileron deflection angle relative to lift.

[0090] In this example, a trim analysis of the drone used in this example was performed based on a six-degree-of-freedom dynamic model of a low-altitude wing-body blended UAV to determine its flight control performance. The trim and analysis of the UAV dynamics model was performed at a specific flight state point, and the model trim and analysis methods employed are well-known in the art.

[0091] In this example, the drone weighs 2.5 kg, and the typical flight state is defined as an altitude of 100 m and a cruising speed of 20 m / s. At this state, the drone's trim angle of attack is 5.4725°, the trim thrust is 6.1639 N, and the trimmed effective elevator angle is -9.7647°. Based on this trim state, the modal eigenvalues ​​of the drone are calculated, yielding the characteristic roots of the longitudinal short-period and long-period modes as -7.27 ± j21.60 and -0.117 ± j0.64, respectively, where j represents the imaginary sign. The characteristic roots of the lateral Dutch roll mode, spiral mode, and roll convergence mode are -1.43 ± j11.10, -0.13, and -10.46, respectively.

[0092] According to the results of trim and modal analysis, the UAV has sufficient and stable flight capabilities at this typical altitude and cruising speed. The UAV's longitudinal short-period mode and long-period mode are both a pair of conjugate complex roots with negative real parts, and the negative real part of the short-period mode is large, indicating that under the current mass and center of gravity configuration, the aircraft has good damping characteristics and strong longitudinal stability. In terms of lateral heading, the Dutch roll mode is a pair of conjugate complex roots with negative real parts, the spiral mode is a smaller negative real root, and the roll convergence mode is a larger negative real root. This shows that although the three lateral heading modes of the UAV can converge, the negative real part of the Dutch roll mode is small, indicating that its ability to resist lateral heading disturbances is weak, and therefore needs to be further improved through a stability augmentation control system.

[0093] Step 2: Based on the six-degree-of-freedom dynamic model, construct the outer-loop trajectory guidance layer of the UAV, design the longitudinal tracking module and the lateral tracking module respectively, and use the outer-loop trajectory guidance layer to obtain the desired thrust, desired pitch angle, and desired roll angle.

[0094] In this embodiment, the drone needs to track a desired altitude, speed, and trajectory. Based on the UAV's vertical and horizontal separation characteristics, the trajectory guidance layer is designed and implemented in two parts: a longitudinal tracking module and a lateral tracking module. The longitudinal tracking module generates the desired thrust and pitch angle, enabling the drone to track the desired altitude and maintain the desired speed. The lateral tracking module generates the desired roll angle, ensuring the drone accurately tracks the desired trajectory.

[0095] Step 2.1: Design the longitudinal tracking module of the trajectory guidance layer. The longitudinal tracking module is designed based on the total energy control theory. By controlling and distributing the potential energy and kinetic energy of the UAV, the altitude and speed are decoupled, so that the desired speed can be achieved. and high expectations , generating the corresponding expected thrust and the desired pitch angle .

[0096] The total energy of the drone consists of kinetic energy and potential energy, which can be expressed as:

[0097]

[0098] Where, For the overall quality of the drone, is the acceleration due to gravity, is the actual flight altitude of the UAV, is the actual flight speed of the UAV.

[0099] According to the above formula, the total energy formula of the drone also includes the actual flight altitude of the drone. and actual flight speed So consider changing the total energy of the drone The total amount and total energy of the drone The distribution of kinetic energy and potential energy can be used to control the height and speed of the drone.

[0100] The altitude change rate of the drone and speed change rate Expressed as:

[0101]

[0102]

[0103] Where, is the actual flight speed, is the actual track angle, For thrust, For resistance, For drone quality, is the acceleration due to gravity.

[0104] Defining the total energy of a drone The total rate of change for:

[0105]

[0106] Defining the total energy of a drone The distribution rate between kinetic energy and potential energy for:

[0107]

[0108] In order to increase the expected speed Convert to desired speed change rate , then:

[0109]

[0110] Where, is the expected velocity change rate, is the expected speed, It is the proportional parameter for realizing speed information conversion.

[0111] To raise expectations Convert to desired track angle , then:

[0112]

[0113]

[0114] Where, is the desired track angle, is the height error, For the expected height, A scale parameter for achieving height information conversion.

[0115] Calculate track angle error and velocity change rate error for:

[0116]

[0117]

[0118] According to the total energy change rate The distribution ratio of total energy between kinetic energy and potential energy The relationship, combined with the proportional-integral control strategy, is solved to obtain the desired thrust increment Desired pitch angle increment for:

[0119]

[0120] Where, is the control channel proportional gain parameter, is the control channel integral gain parameter, To allocate channel proportional gain parameters, Assign channel integral gain parameters.

[0121] Since the acceleration signal is affected by the speed change rate error in the above control method, In order to eliminate this adverse effect, the present invention introduces compensation for speed error:

[0122]

[0123] Where, is the speed error control term, is the proportional gain parameter of the velocity error, is the expected speed.

[0124] Since there is a steady-state error in the control of the flight altitude in the above control method, in order to reduce the steady-state error and improve the tracking accuracy, the present invention also introduces compensation for the altitude error:

[0125]

[0126] Where, is the rate of change of track angle error, is the height error change rate, is the proportional gain parameter of the height error.

[0127] Finally, the expected thrust increment derived previously Desired pitch angle increment The formula is improved and the longitudinal tracking module finally solves the expected thrust increment. and the desired pitch angle increment The complete formula is:

[0128]

[0129] In this embodiment, the longitudinal tracking module solves the expected thrust and the desired pitch angle The final expression is:

[0130]

[0131]

[0132] Where, To balance the thrust, To trim the pitch angle.

[0133] Step 2.2: Design the lateral tracking module of the track guidance layer. The function of this module is to generate the corresponding desired roll angle according to the desired track. This module uses a nonlinear guidance algorithm with offset compensation. By dynamically correcting the reference distance, limiting the sight angle, and introducing compensation for offset errors, it effectively improves the anti-interference characteristics of the UAV's trajectory tracking.

[0134] When the drone is tracking the trajectory, it will continuously select new virtual target points on the desired trajectory and define the distance between the drone and the virtual target points. for:

[0135]

[0136] Where, is the set time constant used to adjust the distance between the drone and the virtual target point; is the drone ground speed.

[0137] Define the forward projection length of the drone along the desired trajectory for:

[0138]

[0139] Where, is a vector The forward projection vector in the direction of the desired trajectory, is the vertical distance between the UAV and the desired trajectory, is a vector The maximum angle between the vector and the desired trajectory The direction is from the UAV to the virtual target point, Defines parameters for the set distance.

[0140] For the distance To limit the value to avoid it being too large, the present invention uses the forward projection length Distance Make corrections to get the corrected distance between the drone and the virtual target point for:

[0141]

[0142] According to the ground speed vector and the corrected vector from the drone to the virtual target point The vector relationship between them, solve the angle between the two vectors, that is, the sight angle for:

[0143]

[0144] Since the maximum roll angle of the drone in actual conditions should be constrained, so the maximum lateral acceleration The restrictions are:

[0145]

[0146] Similarly, due to the maximum roll angle of the drone in actual conditions should be constrained, so the sight angle Maximum viewing angle limit:

[0147]

[0148] According to the UAV flight state parameters, solve the lateral acceleration required for tracking for:

[0149]

[0150] However, since the low-altitude flight process is easily affected by external disturbances, the UAV will produce a large lateral deviation error during the trajectory tracking process. In order to improve the trajectory tracking accuracy, the present invention introduces a compensation control for the tracking lateral deviation error, and the lateral acceleration after compensation is for:

[0151]

[0152] Where, is the gain parameter of the integral term of the lateral deviation error, is the measured trajectory deviation distance error during the tracking process.

[0153] In this embodiment, the lateral tracking module solves the desired roll angle The solution is:

[0154]

[0155] Finally, based on the design derivation of step 2 of the method above, the outer ring track guidance layer of the UAV of this embodiment is formed. The specific architecture is as follows: Figure 2 shown.

[0156] Step 3: Based on the six-degree-of-freedom dynamics model, the attitude control layer of the UAV is constructed. The attitude stabilization loop and the anti-disturbance compensation loop are designed respectively to obtain the equivalent rudder angle corresponding to the desired pitch angle and the desired roll angle to achieve control of the UAV.

[0157] Step 3.1: Based on the UAV dynamics model established in step 1, this embodiment designs the stabilization control loop of the attitude control layer. Since the attitude control of the UAV is divided into longitudinal and lateral, the stabilization control loop includes a pitch angle control channel and a roll angle control channel. In the pitch angle control channel, The control command input at any time is the desired pitch angle ; In the roll angle control channel, The control command input at any time is the desired roll angle The control objectives of both channels are to make the attitude angle of the UAV tend to the desired attitude angle. The pitch angle control channel will solve and output the equivalent elevator base deflection angle The roll angle control channel will solve and output the equivalent aileron basic deflection angle .

[0158] The solution formula for the pitch angle control channel in the stability augmentation control loop is:

[0159]

[0160] The solution formula for the roll angle control channel of the stability augmentation control loop is:

[0161]

[0162] Where, for The expected pitch rate at time , for The expected roll rate at time t; is the pitch angle proportional control gain parameter, is the roll angle proportional control gain parameter; is the pitch angle integral control gain parameter, is the roll angle integral control gain parameter; for The desired pitch angle at the moment, for The expected roll angle at the moment; for The actual pitch angle at the moment, for The actual roll angle at the moment; for The equivalent elevator basic deflection angle at time , for The equivalent aileron basic deflection angle at the moment; is the equivalent elevator trim angle, Trim the deflection angle for the equivalent aileron; is the pitch angle rate proportional control gain parameter, is the roll angular rate proportional control gain parameter; is the pitch angle rate integral control gain parameter, is the roll angular rate integral control gain parameter; for The actual pitch rate at the moment, for The actual roll angular rate at the moment.

[0163] Step 3.2: This embodiment further designs an anti-disturbance compensation loop based on the stabilization control loop. The function of this loop is to estimate the external disturbance torque in real time and perform corresponding feedforward compensation. The anti-disturbance compensation loop also includes a pitch angle compensation channel and a roll angle compensation channel. Different nonlinear disturbance observers are designed on the two channels. The two channels estimate the longitudinal pitch disturbance torque and the lateral roll disturbance torque respectively, and perform reverse solution in combination with the control efficiency of the equivalent elevator and equivalent aileron of the UAV, and finally obtain Equivalent elevator compensation angle at time and equivalent aileron compensation deflection .

[0164] In combination with the inherent characteristics of the low-altitude wing-body fusion UAV of this embodiment, the torque equations in the dynamic model are rewritten as the equations represented by the attitude angular acceleration:

[0165]

[0166] Where, is the actual roll angular acceleration, is the actual pitch angular acceleration, is the actual yaw acceleration; is the moment about the x-axis of the body axis, is the moment about the y-axis of the body axis system, is the moment about the z-axis of the body axis; is the moment of inertia of the drone around the x-axis of the body axis, is the moment of inertia of the drone around the y-axis of the body axis, is the moment of inertia of the drone around the z-axis of the body axis; is the actual roll angular velocity, is the actual pitch angular velocity, is the actual yaw angular velocity; is the equivalent aileron control efficiency, is the equivalent elevator control efficiency; is the equivalent aileron full deflection angle, is the equivalent elevator full deflection angle; for the initial moment, the equivalent aileron full deflection angle is the equivalent aileron trim deflection angle, and the equivalent elevator full deflection angle is the equivalent elevator trim deflection angle.

[0167] When designing the pitch angle compensation channel, considering that the UAV is subjected to external disturbance torque, its pitch angle acceleration can be expressed as:

[0168]

[0169] Where, is the longitudinal disturbance torque acting on the UAV. Its specific value is unknown and needs to be estimated.

[0170] Design the nonlinear gain of the pitch angle compensation channel as the given parameter , then through the iterative calculation of the time step, the nonlinear disturbance observer of the pitch angle compensation channel is expressed as:

[0171] { p t i = m i ˙ t − 1 z ˙ t i =− m [ ( I zzz − I xx ) ϕ ˙ t − 1 ψ ˙ t − 1 I yyy + L d e d e , ( t − 1 ) final I yyy + m i ˙ t − 1 I yyy ] − m z t − 1 i I yyy

[0172] Where, for The first nonlinear reaching law function at time, is the nonlinear gain parameter, for The intermediate variable of the disturbance observer of the pitch angle compensation channel at the moment is obtained by taking the derivative of the intermediate variable You can get points by , for The actual pitch angular velocity at the moment, for The actual roll angular velocity at the moment, for The actual yaw rate at the moment.

[0173] According to the above formula, we can deduce The estimated value of the longitudinal disturbance torque of the drone from the outside world at the moment for:

[0174]

[0175] According to the control relationship of the equivalent elevator, solve Equivalent elevator compensation angle at time for:

[0176]

[0177] Similarly, when designing the roll angle compensation channel, considering that the UAV is subjected to external disturbance torque, its roll angle acceleration can be expressed as:

[0178]

[0179] Where, is the lateral disturbance torque acting on the UAV. Its specific value is unknown and needs to be estimated.

[0180] Similarly, the nonlinear gain of the roll angle compensation channel is designed to be a given parameter , then the nonlinear disturbance observer of the roll angle compensation channel is expressed as:

[0181] { p t ϕ = l ϕ ˙ t − 1 z ˙ t ϕ =− l [ ( I yyy − I zzz ) i ˙ t − 1 ψ ˙ t − 1 I xx + L d a d a , ( t − 1 ) final I xx + l ϕ ˙ t − 1 I xx ] − l z t − 1 ϕ I xx

[0182] Where, for The second nonlinear reaching law function of time, is the nonlinear gain parameter, for The intermediate variable of the disturbance observer of the roll angle compensation channel at the moment is obtained by taking the derivative of the intermediate variable You can get points by .

[0183] Similarly, according to the above formula, we can deduce The estimated value of the lateral disturbance torque of the drone at the moment for:

[0184]

[0185] Similarly, according to the control relationship of the equivalent aileron, solve The equivalent aileron compensation angle at time for:

[0186]

[0187] The desired command output by the attitude control layer is generated by the combined action of the attitude stabilization loop and the anti-disturbance compensation loop. Equivalent elevator basic deflection angle at time and Equivalent elevator compensation angle at time Summing, we get The equivalent elevator full deflection angle at time ;Will The equivalent aileron basic deflection angle at time and The equivalent aileron compensation angle at time Summing, we get The equivalent aileron full deflection angle at time The specific combination formula is as follows:

[0188]

[0189]

[0190] Thus, according to the above design derivation of step 3, the inner loop attitude control layer of the drone of this embodiment is formed, and the specific architecture is as follows: Figure 3 As shown, according to Expected pitch angle at time and the desired roll angle , and finally get The equivalent elevator full deflection angle at time and The equivalent aileron full deflection angle at time , compensation for unknown interference is achieved through interference estimation.

[0191] The methods designed in the previous steps are integrated to form a complete and effective composite layered anti-interference trajectory tracking method. Specifically, step 2 calculates the corresponding desired pitch angle, thrust, and desired roll angle based on the desired altitude, speed, and desired trajectory; step 3 generates the equivalent elevator full deflection angle and equivalent aileron full deflection angle based on the desired pitch angle and desired roll angle. The UAV's inner-loop attitude control layer and outer-loop trajectory guidance layer work together to enable the UAV to robustly and accurately execute the desired trajectory tracking flight.

[0192] After the design and construction of the above four steps, a complete composite layered anti-interference trajectory tracking control method for low-altitude wing-body fusion UAV is formed in this embodiment. Next, the trajectory tracking control process of a typical low-altitude wing-body fusion UAV is simulated and verified. The specific simulation experiment is as follows:

[0193] Experiment 1: Verify the effect of nonlinear disturbance observer in attitude disturbance rejection control in the attitude control layer.

[0194] Because the nonlinear disturbance observer can estimate the external disturbance torque based on the drone's real-time flight state and inversely resolve the equivalent rudder deflection angle for disturbance rejection compensation, the key metrics for measuring the control system's disturbance rejection effectiveness are the magnitude of change and convergence speed of the drone's attitude angle when subjected to unknown torque disturbances. Furthermore, the criterion for evaluating the effectiveness of the nonlinear disturbance observer design lies in the accuracy of its estimation of the external disturbance torque.

[0195] In this embodiment, based on the trim state model of the drone, three step torque disturbances in opposite directions are introduced into the pitch channel and the roll channel, which is equivalent to the drone encountering three unknown external low-altitude gust disturbances during steady level flight. During the simulation process, the conventional control method is compared with the anti-disturbance control method with the nonlinear disturbance observer proposed in this invention. The simulation results are shown in Figure 2. Figure 4 and Figure 5 shown.

[0196] according to Figure 4 and Figure 5 The attitude angle change curve and torque estimation curve in Figure 3 show that the proposed nonlinear disturbance observer can effectively estimate the unknown disturbance torque in both the pitch and roll channels, and real-time feedforward compensation significantly improves the stabilization control effect of the attitude angle. Experimental results show that the proposed attitude disturbance rejection control algorithm can effectively improve the attitude control stability of the UAV, thereby indirectly enhancing the reliability of trajectory tracking.

[0197] Experiment 2: Verify the trajectory tracking effect of the new guidance law with lateral offset compensation in the track guidance layer.

[0198] Currently commonly used guidance algorithms include: Guidance Law, Guidance Law and Guidance law. Among them, The guidance law can be divided into two cases according to the reference distance: relatively large distance and relatively small distance. The guidance law is It is obtained by optimizing the guidance law.

[0199] Guidance law and reference distance are small The guidance law may produce overshoot, causing the UAV to oscillate during tracking, and the generated desired roll angle is likely to reach the limit. The guidance law is prone to over-damping, which can cause the drone to be unable to "approach" the preset waypoint and the guidance effect is not ideal. The tracking effect of the guidance law will be improved, but the ability to correct the side offset error in real time may still be insufficient, and the trajectory tracking convergence speed will be slow. In order to verify the track guidance performance of the proposed algorithm, this embodiment simulates and compares the tracking conditions of different guidance laws. The results are as follows: Figure 6 and Figure 7 shown.

[0200] Depend on Figure 6 and Figure 7 The tracking results of different guidance laws show that the new nonlinear guidance algorithm proposed in this invention effectively makes up for the The guidance law has shortcomings in real-time compensation of lateral offset errors. When the UAV causes tracking errors due to disturbances, the guidance system can adjust and correct them in real time, thereby effectively improving the trajectory tracking effect.

[0201] Experiment 3: Tracking comparison between the composite layered anti-disturbance trajectory tracking control method and the conventional trajectory tracking control method.

[0202] The complete composite layered anti-disturbance trajectory tracking method takes into account the anti-disturbance control effect of the UAV attitude and trajectory. In this experiment, a simulation trajectory including level flight, climb, descent and maneuvering turn was planned, and three external step disturbance torques were introduced during this process, and turbulent wind field disturbances were applied at the same time. By comparing the conventional trajectory tracking control method with the composite layered anti-disturbance trajectory tracking method proposed in this invention, Figure 8 According to the comparison results, it can be seen that the method proposed in the present invention significantly improves the anti-interference tracking capability of the UAV.

[0203] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention.

Claims

1. A multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform, characterized by: The following steps are involved: Step 1: Establish a six-degree-of-freedom dynamic model of the low-altitude wing-body fusion UAV and perform a trim analysis at the reference state point to obtain the trim parameters at the reference state point; Step 2: Based on the six-degree-of-freedom dynamic model, construct the outer loop trajectory guidance layer of the UAV and design the longitudinal tracking module and the lateral tracking module respectively; The longitudinal tracking module is designed based on the total energy control theory. By controlling and distributing the potential energy and kinetic energy of the drone, the altitude and speed are decoupled, so that the desired speed can be achieved. and high expectations , generating the corresponding expected thrust and the desired pitch angle ; The lateral tracking module adopts a nonlinear guidance algorithm with side deviation compensation. By dynamically correcting the reference distance, limiting the size of the sight angle, and introducing compensation for the tracking side deviation error, the corresponding desired roll angle is generated according to the desired track. ; Step 3: Based on the six-degree-of-freedom dynamics model, construct the attitude control layer of the drone, design the attitude stabilization loop and the anti-disturbance compensation loop respectively, and obtain the desired pitch angle and the desired roll angle The corresponding equivalent rudder deflection angle is used to control the UAV; the anti-disturbance compensation loop includes a pitch angle compensation channel and a roll angle compensation channel. Different nonlinear disturbance observers are designed on the two channels to estimate the longitudinal pitch disturbance moment and the lateral roll disturbance moment respectively, and the control effectiveness of the UAV's equivalent elevator and equivalent aileron is combined with the reverse solution to obtain the equivalent elevator compensation deflection angle and the equivalent aileron compensation deflection angle.

2. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 1 is characterized by: In step 1, when establishing the UAV's six-degree-of-freedom dynamic model, the UAV is assumed to be a rigid body, and the effects of its structural elasticity and the curvature of the Earth are ignored. This model conforms to the "flat Earth assumption" and has a longitudinal symmetry plane. The UAV is also equipped with only one set of elevons as control surfaces. The control efficiency of the elevons is equivalent to the linear superposition of the elevator and ailerons, achieving longitudinal and lateral separation of the aerodynamic force solution.

3. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 2 is characterized by: In step 1, the six-degree-of-freedom dynamic model of the drone is: Where, is the rolling moment, is the pitching moment, is the yaw moment; For resistance, is the lateral force, for lift; is the angle of attack, is the sideslip angle; is the equivalent elevator full deflection angle, is the equivalent aileron full deflection angle; is the roll angular rate, is the pitch angular rate, is the yaw rate; is the dynamic pressure, is the wing reference area, is the mean aerodynamic chord length, For the exhibition length; 、 、 and They are the aerodynamic derivative of sideslip angle relative to rolling moment, the aerodynamic derivative of equivalent aileron deflection angle relative to rolling moment, the aerodynamic derivative of roll angular rate relative to rolling moment, and the aerodynamic derivative of yaw angular rate relative to rolling moment. 、 and They are the aerodynamic derivative of the angle of attack relative to the pitching moment, the aerodynamic derivative of the equivalent elevator deflection angle relative to the pitching moment, and the aerodynamic derivative of the pitch angular rate relative to the pitching moment. 、 、 and They are the aerodynamic derivative of sideslip angle relative to yaw moment, the aerodynamic derivative of equivalent aileron deflection angle relative to yaw moment, the aerodynamic derivative of yaw angular rate relative to yaw moment and the aerodynamic derivative of roll angular rate relative to yaw moment. 、 and They are the aerodynamic derivative of the angle of attack relative to the drag, the aerodynamic derivative of the equivalent elevator deflection angle relative to the drag, and the aerodynamic derivative of the equivalent aileron deflection angle relative to the drag; and They are the aerodynamic derivative of the sideslip angle relative to the side force and the aerodynamic derivative of the equivalent aileron deflection angle relative to the side force; 、 and They are the aerodynamic derivative of the angle of attack relative to lift, the aerodynamic derivative of the equivalent elevator deflection angle relative to lift, and the aerodynamic derivative of the equivalent aileron deflection angle relative to lift.

4. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 3 is characterized by: In step 2, the expected thrust obtained by the longitudinal tracking module and the desired pitch angle Expressed as: in To balance the thrust, To trim the pitch angle; is the expected thrust increment, is the desired pitch angle increment, according to the formula Get, among them is the control channel proportional gain parameter, is the control channel integral gain parameter, To allocate channel proportional gain parameters, To allocate channel integral gain parameters; is the track angle error, is the speed change rate error, is the acceleration due to gravity, is the rate of change of track angle error, is the speed error control term.

5. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 4 is characterized by: In the longitudinal tracking module, the speed error control term In the formula is the proportional gain parameter of the velocity error, is the expected speed, is the actual flight speed.

6. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 4 is characterized by: In the longitudinal tracking module, the track angle error change rate In the formula is the height error change rate, is the height error, is the proportional gain parameter of the height error, is the actual flight speed.

7. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 3 is characterized by: In step 2, the desired roll angle obtained by the lateral tracking module Expressed as In the formula is the acceleration due to gravity, is the lateral acceleration after compensation, according to the formula Get, among them is the drone ground speed, is the corrected distance between the UAV and the virtual target point, is the sight angle, and the virtual target point is a point selected on the desired trajectory; is the gain parameter of the integral term of the lateral deviation error, is the measured trajectory deviation distance error during the tracking process.

8. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 7 is characterized by: In step 2, in the lateral tracking module, the corrected distance between the drone and the virtual target point in is the actual track angle, is the forward projection length of the UAV along the desired trajectory, according to the formula Value, where is the vertical distance between the UAV and the desired trajectory, is a vector The maximum angle between the vector and the desired trajectory The direction is from the UAV to the virtual target point, Define the parameters for the set distance, is the distance between the UAV and the virtual target point.

9. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 7, characterized in that: In step 2, in the lateral tracking module, the sight angle Maximum viewing angle limit: in is the maximum roll angle of the UAV, For thrust.

10. The multi-path collaborative disturbance elimination trajectory tracking control method for a wing-body fusion UAV platform according to claim 3, characterized in that: In step 3, the final result is The equivalent rudder deflection angle at the moment is divided into The equivalent elevator full deflection angle at time and The equivalent aileron full deflection angle at time : in for The equivalent elevator basic deflection angle at time , for The equivalent elevator compensation angle at time , for The equivalent aileron basic deflection angle at time , for The equivalent aileron compensation deflection angle at the moment; The equivalent elevator basic deflection angle at the time is based on Expected pitch angle at time , according to the formula Calculated; The equivalent aileron basic deflection angle at the moment is based on Expected roll angle at time , according to the formula Calculated; where, for The expected pitch rate at time , for The expected roll rate at time t; is the pitch angle proportional control gain parameter, is the roll angle proportional control gain parameter; is the pitch angle integral control gain parameter, is the roll angle integral control gain parameter; for The desired pitch angle at the moment, for The expected roll angle at the moment; for The actual pitch angle at the moment, for The actual roll angle at the moment; for The equivalent elevator basic deflection angle at time , for The equivalent aileron basic deflection angle at the moment; is the equivalent elevator trim angle, Trim the deflection angle for the equivalent aileron; is the pitch angle rate proportional control gain parameter, is the roll angular rate proportional control gain parameter; is the pitch angle rate integral control gain parameter, is the roll angular rate integral control gain parameter; for The actual pitch rate at the moment, for The actual roll angular rate at the moment; Equivalent elevator compensation angle at time According to the formula Calculated; where is the equivalent elevator control efficiency, for The estimated value of the external longitudinal disturbance torque on the UAV at the moment: in and The nonlinear disturbance observer of the pitch angle compensation channel is obtained through iterative calculation. The nonlinear disturbance observer of the pitch angle compensation channel is: Where, for The first nonlinear reaching law function at time, is the set nonlinear gain parameter, for The intermediate variable of the disturbance observer of the pitch angle compensation channel at the moment is obtained by taking the derivative of the intermediate variable Integrate to get , for The actual pitch angular velocity at the moment, for The actual roll angular velocity at the moment, for The actual yaw rate at the moment; is the moment of inertia of the drone around the x-axis of the body axis, is the moment of inertia of the drone around the y-axis of the body axis, is the moment of inertia of the drone around the z-axis of the body axis; for The equivalent elevator full deflection angle at time , for The intermediate variable of the disturbance observer of the pitch angle compensation channel at each moment; The equivalent aileron compensation angle at time According to the formula Calculated; where is the equivalent aileron control efficiency, for The estimated value of the external lateral disturbance torque on the drone at this moment: in and The nonlinear disturbance observer of the roll angle compensation channel is obtained through iterative calculation. The nonlinear disturbance observer of the roll angle compensation channel is: Where, for The second nonlinear reaching law function of time, is the set nonlinear gain parameter, for The intermediate variable of the disturbance observer of the roll angle compensation channel at the moment is obtained by taking the derivative of the intermediate variable You can get points by ; for The equivalent aileron full deflection angle at time , for The intermediate variable of the disturbance observer of the roll angle compensation channel at time instant.

Images