Aircraft flight fault-tolerant control method, system and terminal for control surface failure

Abstract

The present invention discloses a fault-tolerant flight control method, system, and terminal for aircraft in the event of control surface failures. The method constructs a longitudinal dynamics model of a fixed-wing unmanned aerial vehicle (UAV) under an actuator failure state. A state estimator is then designed based on the UAV model to estimate the UAV's state information in real time. Based on the state estimation signal, an L1 adaptive backstepping fault-tolerant controller is designed for pitch attitude control. Furthermore, a simplified longitudinal dynamics model is constructed, and a fault-based control allocation strategy is designed to compensate for ailerons. With the compensation effects of the elevator and ailerons, the fixed-wing UAV achieves stable flight in a faulty state. The present invention enables the UAV to control its pitch angle in a faulty state, preventing serious accidents.

Description

Technical Field

[0001] The present invention belongs to the field of unmanned aerial vehicles (UAVs), and relates to a method, system, and terminal for aircraft flight fault-tolerant control facing control surface failures. Background Art

[0002] Over the past decade, drones have been widely used in various fields. Depending on the mission type and flight environment, many types of drones have emerged, with quadcopters and fixed-wing drones being the most common. However, the low speed, short range, and small payload of quadcopters have limited their development. Therefore, fixed-wing drones are the preferred model for missions that require certain speed, range, and payload. Fixed-wing drones, on the other hand, offer advantages such as high altitude and high speed, but they carry a high probability and risk of safety accidents. Therefore, when designing and developing fixed-wing drone flight control systems, key safety issues must be considered. Control surfaces, being components that are highly susceptible to failure and play a vital role in control, warrant particular attention in developing fault-tolerant control systems for these surfaces.

[0003] Currently, most fault-tolerant control methods for aircraft control surface failures rely on aircraft modeling, using nonlinear control methods and adaptive control techniques to estimate fault parameters online, and then using controllers to compensate in real time. This model-based fault-tolerant control approach relies heavily on model accuracy; traditional fault-tolerant methods redesign controllers when fixed-wing UAVs experience failures without considering their coherence and integrity. Summary of the Invention

[0004] The purpose of the present invention is to solve the problems in the prior art and provide an aircraft flight fault-tolerant control method, system and terminal for control surface failures. The method utilizes a fault-based control allocation strategy and a designed L1 adaptive backstepping controller to achieve stable attitude control, enabling the UAV to still stably control the pitch angle in a fault state, thereby avoiding more serious accidents of the UAV.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for aircraft flight fault-tolerant control oriented to control surface failures, comprising the following steps:

[0007] Based on Newton's second law and Euler's dynamic equation, the flight state of the UAV is analyzed and the longitudinal dynamic model of the UAV is constructed;

[0008] Based on the UAV longitudinal dynamics model, the flight parameters of the UAV are simplified to obtain a simplified UAV longitudinal dynamics model.

[0009] Based on the simplified UAV longitudinal dynamics model, a fault-based control allocation strategy is constructed;

[0010] Estimate the real-time pitch angle and pitch velocity of the UAV based on the state prediction dynamics formula and the adaptive rate formula;

[0011] Based on the real-time pitch angle and pitch velocity of the UAV, an L1 adaptive backstepping attitude controller is constructed;

[0012] Based on the constructed L1 adaptive backstepping attitude controller and fault-based control allocation strategy, the pitch angle command with or without fault is generated to control the deflection of the UAV elevator surface.

[0013] In a second aspect, the present invention provides an aircraft flight fault-tolerant control system for control surface failures, comprising:

[0014] A first building block, which analyzes the flight state of the UAV based on Newton's second law and Euler's dynamic equations and constructs a longitudinal dynamic model of the UAV;

[0015] A simplification module, wherein the simplification module simplifies the flight parameters of the UAV based on the obtained UAV longitudinal dynamics model to obtain a simplified UAV longitudinal dynamics model;

[0016] a second building block, wherein the second building block constructs a fault-based control allocation strategy based on a simplified longitudinal dynamics model of the UAV;

[0017] A third building block is used to construct a state prediction dynamics formula and an adaptive rate formula to estimate the real-time pitch angle and pitch angular velocity of the UAV;

[0018] A fourth building block, wherein the fourth building block builds an L1 adaptive backstepping attitude controller based on the real-time pitch angle and pitch angular velocity of the UAV;

[0019] The control module generates a pitch angle command under fault or no fault conditions based on the constructed L1 adaptive backstepping attitude controller and the fault-based control allocation strategy to control the deflection of the UAV elevator surface.

[0020] In a third aspect, the present invention provides a terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0021] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention constructs a longitudinal dynamics model of a UAV under an actuator fault state, then designs a state estimator based on the UAV model to estimate the state information of the UAV in real time, and designs an L1 adaptive backstepping fault-tolerant controller based on the state estimation signal for pitch attitude control. At the same time, through the constructed simplified longitudinal dynamics model of the UAV, a fault-based control allocation strategy is designed to compensate for the ailerons. Under the compensation effect of the elevator and ailerons, the UAV can achieve stable flight in a fault state. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 This is a flow chart of the aircraft flight fault-tolerant control method for control surface failures of the present invention.

[0026] Figure 2 This is another flow chart of the aircraft flight fault-tolerant control method for control surface failures of the present invention.

[0027] Figure 3 Schematic diagram of the fixed-wing UAV of the present invention.

[0028] Figure 4 This is a state diagram of the aircraft under the action of the fixed-wing UAV fault-tolerant flight control system of the present invention, where (a) is the pitch angle, (b) is the pitch angular velocity, (c) is the angle of attack, and (d) is the true airspeed.

[0029] Figure 5 This is a diagram of the aircraft state under the action of the fixed-wing UAV fault-tolerant flight control system of the present invention, where (a) is the elevator efficiency, (b) is the engine thrust, (c) is the elevator deflection, and (d) is the aileron deflection.

[0030] Figure 6 The pitch angle and pitch rate errors of the aircraft under the action of the fixed-wing UAV fault-tolerant flight control system of the present invention, where (a) is the error pitch angle and (b) is the error pitch rate.

[0031] Figure 7 This is a structural diagram of the aircraft flight fault-tolerant control system for control surface failures of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0034] In the description of the embodiments of the present invention, it should be noted that if the terms "upper," "lower," "horizontal," "inner," etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the inventive product is typically placed when in use. These terms are merely for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0035] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0036] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0037] The present invention is described in further detail below with reference to the accompanying drawings:

[0038] Figure 1 and Figure 2 The embodiment of the present invention discloses a method for aircraft flight fault-tolerant control facing control surface failure, comprising:

[0039] S101, based on Newton's second law and Euler's dynamic equation, analyzes the flight state of the UAV and constructs the UAV longitudinal dynamic model.

[0040] See Figure 3 , according to Newton's second law and Euler's dynamic equation, the longitudinal dynamic model of the fixed-wing UAV is established. Before construction, the longitudinal spatial state vector is selected as X lon =[θ,Q,α,V t ], where θ is the pitch angle of the UAV, Q is the pitch angular velocity of the UAV, α is the angle of attack of the UAV, and V t is the airspeed of the UAV. Therefore, according to the selected longitudinal space state vector, the longitudinal dynamic model of the fixed-wing UAV can be designed as shown in formula (1):

[0041]

[0042] in, is the pitch angle rate, Q is the true pitch angle rate, α is the aircraft angle of attack, is the angular rate of the angle of attack, V t is the aircraft airspeed, δ e is the deflection angle of the elevator surface, is a complex number with Q, α, V t and δ e Related functions, m is the mass of the drone, g represents the acceleration of gravity, I y is the moment of inertia about the y-axis, is the dynamic pressure, and is the wing area, is the average aerodynamic chord length of the wing, ρ is the air density, T is the engine thrust, D is the aircraft drag, and L is the aircraft lift; c m0 、 c mδe 、 and are dimensionless coefficients, θ is the true pitch angle, is the rate of change of the aircraft's airspeed;

[0043] The engine thrust T satisfies the relationship shown in formula (2):

[0044]

[0045] where η and δ trepresent propeller efficiency and input power respectively.

[0046] S102: Based on the obtained UAV longitudinal dynamics model, simplify the flight parameters of the UAV to obtain a simplified UAV longitudinal dynamics model.

[0047] Construct aircraft drag D, lift L, side force Y, and rolling moment Pitching moment Yaw moment The physical mathematical relationship between the deflection angle of the control surface is shown in formula (3):

[0048]

[0049] Among them, x lon =[φ,ψ,P,R,β] represents the lateral spatial state vector of the UAV, x lat is the longitudinal space state vector of the UAV, b is the wingspan, δ a and δ r are the deflection angles of the aileron and rudder surfaces, Δ D (x lon ,δ e ) is the unmodeled portion of the aircraft drag D, Δ L (x lon ,δ e ) is the unmodeled portion of the aircraft lift L, Δ Y (x lat ,δ a ,δ r ) is the unmodeled portion of the lateral force Y, Δ l (x lat ,δ a ,δ r ) is the unmodeled portion of the rolling moment l; Δ m (x lon ,δ e ) is the unmodeled portion of the pitching moment m, Δ n (x lat ,δ a ,δ r ) is the unmodeled part of the yaw moment n, c D (x lon ,δ e ) is the resistance coefficient, c L (x lon ,δ e ) is the lift coefficient, c Y (x lat ,δ a ,δ r ) is the lateral force coefficient, c l (x lat,δ a ,δ r ) is the rolling moment coefficient, c m (x lon ,δ e ) is the pitching moment coefficient, c n (x lat ,δ a ,δ r ) is the yaw moment coefficient, l is the rolling moment, and n is the yaw moment; where,

[0050] Since the controller designed later will be based on the model constructed here, in order to reduce the difficulty of subsequent controller design, it is necessary to simplify the model constructed above. The simplification is based on the following assumptions:

[0051] A. Since airspeed is controlled separately in the field of aircraft control, the airspeed factor can be ignored in the design of the pitch controller.

[0052] B. Assume that the change in angle of attack is a time-dependent function, and that both angle of attack and airspeed vary within a range, i.e., |α|≤α max 、 and 0≤V t,min ≤V t ≤V t,max .

[0053] C. Assume that the only uncertainty is in the pitch moment, and that the pitch coefficient c m0 ,c mδe is completely known, and for the remaining coefficients, the relationship between the actual value and the used value is shown in formula (4):

[0054]

[0055] in, represents the true coefficient value, Q, σ represents the uncertainty between the pitching moment coefficient and the angle of attack, ω represents the uncertainty between the pitching moment coefficient and the derivative of the angle of attack, represents the uncertainty between the pitch moment coefficient and the pitch angular velocity, and assuming that σ, ω and The rate of change is 0, c mα 、 and c mQ All are dimensionless coefficients;

[0056] The simplified aircraft longitudinal dynamics model is shown in formula (5):

[0057]

[0058] in, is the pitch angle acceleration, c mδe is the dimensionless coefficient.

[0059] S103, based on the simplified UAV longitudinal dynamics model, a fault-based control allocation strategy is constructed.

[0060] Based on a simplified longitudinal dynamics model of a fixed-wing UAV, a fault-based control allocation strategy is designed to achieve control redistribution under fault conditions. Only faults occurring on the elevator surfaces are considered. Among these faults, partial loss of rudder efficiency, also known as loss of control surface failure, is a very common and significant risk event.

[0061] The mathematical model of control surface loss failure is constructed as shown in formula (6):

[0062] δ a (t)=W(t)δ(t) (6)

[0063] Among them, δ a is the actual control vector, δ is the ideal control vector, W(t) represents the control surface efficiency, and t represents time;

[0064] W(t) is calculated according to formula (7):

[0065]

[0066] where w1(t), w2(t), and w3(t) are the diagonal elements of the diagonal matrix W(t), I is the identity matrix, K(t) is the multiplicative fault matrix, and K(t) = diag(k1(t), k2(t), k3(t)), where k1(t), k2(t), and k3(t) are the diagonal elements of the multiplicative fault matrix K(t);

[0067] The multiplicative fault matrix is ​​related to the elevator surface, aileron and rudder surface. If k i (t) = 0 means that the i-th control surface is fault-free. If k i (t)=1 means that the i-th control surface has completely failed.

[0068] Before introducing a fault into the control distribution, it is necessary to determine the nominal deflection angles of the control surfaces so that the aircraft will produce the desired forces and moments from the controller under fault-free conditions. Furthermore, it is important to note that the control distribution does not take into account the uncertainty in the pitching moment, so the following calculations only use the nominal values ​​of the aerodynamic coefficients.

[0069] According to the derived aircraft lift L and rolling moment and yaw moment And ignoring the uncertain terms, the three equations can be rewritten as:

[0070]

[0071] Among them, c L (x lon ) is the lift coefficient, c l (x lat ) is the rolling moment coefficient, c n (x lat ) is the yaw moment coefficient;

[0072] By analyzing equation (8), we can obtain the expected deflection angle of the control surface under nominal conditions, as shown in equation (9):

[0073]

[0074] Among them, δ e,nom is the elevator rudder deflection angle under nominal conditions, δ a,nom is the aileron rudder deflection angle under nominal conditions, δ r,nom is the rudder deflection angle under nominal conditions; dynamic coefficient Under stable aircraft conditions, it is a constant and non-zero value. In addition, the rudder angle values ​​of each operating surface calculated according to formula (9) must be limited to the specified range, that is,

[0075] δ min <δ e,nom ,δ a,nom ,δ r,nom <δ max (10)

[0076] Among them, δ min is the minimum rudder angle, δ max is the maximum rudder deflection angle;

[0077] After considering the control allocation under nominal fault-free conditions, we will next consider the control allocation under fault conditions. Here, we only consider the case of elevator faults. When an elevator fault occurs, the elevator's steering efficiency will be reduced. In order to compensate for the reduced steering efficiency of the elevator surface, according to the fault-based control allocation strategy proposed by the present invention, the aileron control surface will be utilized to compensate for the lost elevator control efficiency. The compensation angle of the aileron control surface is shown in Equation (11):

[0078]

[0079] Among them, c m (x lon ) is the pitching moment coefficient.

[0080] S104, constructing a state prediction dynamics formula and an adaptive rate formula to estimate the real-time pitch angle and pitch angular velocity of the fixed-wing UAV.

[0081] In order to compensate for the possible uncertainty between the control surface and the actual forces and moments, an adaptive backstepping controller based on L1 is constructed, which can calculate the required elevator surface deflection angle according to the attitude error of the UAV.

[0082] The control object and goal are clearly defined, and an L1-based adaptive backstepping controller is proposed to control the current pitch angle of the fixed-wing UAV to stabilize at the desired pitch angle, even in the case of faults.

[0083] A state estimator is designed to estimate the real-time pitch angle and pitch velocity of a fixed-wing UAV. The estimation error is shown in Equation (12):

[0084]

[0085] in, represents the estimated error of the pitch angle, represents the estimated error of the pitch angular velocity, represents the estimated pitch angle, represents the estimated pitch angular velocity;

[0086] Design the expected estimation error dynamics function, which is shown in formula (13):

[0087]

[0088] in, is the error dynamics function of the pitch angle, is the error dynamics function of the pitch angular velocity, L1 and L2 are coefficients;

[0089] The state prediction dynamic model is shown in formula (14):

[0090]

[0091] in, is the estimated rate of change of the pitch angle, is the estimated rate of change of the pitch angle angular rate, and is the uncertainty estimate of the aerodynamic coefficient;

[0092] Combining Equations (13), (14), (5) and (12), we can obtain a new state prediction dynamics model as shown in Equation (15):

[0093]

[0094] in, is the rate of change of the estimated error of the pitch angle, is the rate of change of the estimated error of the pitch angle rate, and is the estimation error of the uncertainty estimation term of the aerodynamic coefficient;

[0095] Design the adaptive rate to estimate As shown in formula (16):

[0096]

[0097] in, and Represents the rate of change of the uncertainty estimate of the aerodynamic coefficient, Proj function represents the projection algorithm, Respectively represent The adaptive gain estimation of the state prediction dynamics model and adaptive rate formula can be used to estimate the real-time pitch angle and pitch angular velocity of the fixed-wing UAV and use them in the controller designed in S105.

[0098] S105, based on the real-time pitch angle and pitch velocity of the fixed-wing UAV, builds an L1 adaptive backstepping attitude controller.

[0099] Define error variables z1 and z2 as shown in formula (17):

[0100]

[0101] Among them, θ d is the desired pitch angle, α1 is a stable function, and its expression is shown in formula (18):

[0102] α1=-K1z1+Q d (18)

[0103] Among them, K1 is the coefficient, Q d is the desired pitch rate;

[0104] The dynamic expression of the error variable z2 is shown in formula (19):

[0105]

[0106] in, is the differential form of the error variable z2, is the differential form of the stability function α1;

[0107] According to the dynamic expression of z2, the L1 adaptive backstepping attitude controller is designed as shown in formula (20):

[0108]

[0109] Where K2 is the coefficient, and the L1 adaptive backstepping attitude controller is the elevator deflection δe .

[0110] S106 , based on the constructed L1 adaptive backstepping attitude controller and the fault-based control allocation strategy, generates a pitch angle command with or without a fault to control the deflection of the UAV elevator surface.

[0111] The elevator deflection δ e and aileron deflection δ a Under the joint action of the fixed-wing UAV, it can maintain stable flight.

[0112] Figure 4 The figure shows the changes in pitch angle, pitch rate, angle of attack and airspeed when a fault occurs. From the results, it can be seen that without the participation of fault-tolerant control, these four states of the aircraft cannot achieve the desired tracking value and may even become out of control. However, with the participation of fault-tolerant control, these four states of the aircraft can achieve stable tracking.

[0113] Figure 5 The figure shows the changes in the aircraft's elevator deflection efficiency, motor power, elevator deflection angle, and aileron deflection angle when a fault occurs. Figure 4 Similarly, through analysis, it is found that when a fault occurs, the fault-tolerant control system will participate in the control and achieve stable flight of the aircraft in the fault state by changing the elevator deflection efficiency, motor power, elevator deflection angle and aileron deflection angle.

[0114] Figure 6 The figure reflects the transformation curve of the pitch angle error and pitch angle rate error before and after the fault. It can be seen that after the fault occurs, the two errors can basically stabilize at 0, indicating that the fault-tolerant control system has played a role in stabilizing the errors.

[0115] See also Figure 7 The present invention discloses an aircraft flight fault-tolerant control system for control surface failures, comprising:

[0116] A first building block, which analyzes the flight state of the UAV based on Newton's second law and Euler's dynamic equations and constructs a longitudinal dynamic model of the UAV;

[0117] A simplification module, wherein the simplification module simplifies the flight parameters of the UAV based on the obtained UAV longitudinal dynamics model to obtain a simplified UAV longitudinal dynamics model;

[0118] a second building block, wherein the second building block constructs a fault-based control allocation strategy based on a simplified longitudinal dynamics model of the UAV;

[0119] A third building block is used to construct a state prediction dynamics formula and an adaptive rate formula to estimate the real-time pitch angle and pitch angular velocity of the fixed-wing UAV;

[0120] A fourth building block, wherein the fourth building block constructs an L1 adaptive backstepping attitude controller based on the real-time pitch angle and pitch angular velocity of the fixed-wing UAV;

[0121] The control module generates a pitch angle command with or without faults based on the constructed L1 adaptive backstepping attitude controller and the fault-based control allocation strategy to control the deflection of the UAV elevator surface.

[0122] An embodiment of the present invention provides a terminal device. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of each of the aforementioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of each module / unit in each of the aforementioned device embodiments are implemented.

[0123] The computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to accomplish the present invention.

[0124] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0125] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0126] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0127] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0128] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An aircraft flight fault-tolerant control method for control surface failures, characterized in that: The following steps are involved: Based on Newton's second law and Euler's dynamic equation, the flight state of the UAV is analyzed and the longitudinal dynamic model of the UAV is constructed; Based on the UAV longitudinal dynamics model, the flight parameters of the UAV are simplified to obtain a simplified UAV longitudinal dynamics model. Based on the simplified UAV longitudinal dynamics model, a fault-based control allocation strategy is constructed; Estimate the real-time pitch angle and pitch velocity of the UAV based on the state prediction dynamics formula and the adaptive rate formula; Based on the real-time pitch angle and pitch velocity of the UAV, an L1 adaptive backstepping attitude controller is constructed; Based on the constructed L1 adaptive backstepping attitude controller and the fault-based control allocation strategy, the pitch angle command is generated to control the deflection of the UAV elevator surface; The L1 adaptive backstepping attitude controller is constructed based on the real-time pitch angle and pitch velocity of the UAV, specifically: The error variables z1 and z2 are as follows: Among them, θ d is the desired pitch angle, α1 is a stable function, and its expression is shown in formula (18): α1=-K1z1+Q d (18) Among them, K1 is the coefficient, Q d is the desired pitch rate; The dynamic expression of the error variable z2 is shown in formula (19): in, is the differential form of the error variable z2, is the differential form of the stability function α1; According to the dynamic expression of z2, the L1 adaptive backstepping attitude controller is designed as shown in formula (20): Where K2 is the coefficient, and the L1 adaptive backstepping attitude controller is the elevator deflection δ e ; The control allocation strategy based on the simplified UAV longitudinal dynamics model is constructed as follows: The mathematical model of control surface loss failure is constructed as shown in formula (6): δ a (t)=W(t)δ(t) (6) Among them, δ a is the actual control vector, δ is the ideal control vector, W(t) represents the control surface efficiency, and t represents time; W(t) is calculated according to formula (7): where w1(t), w2(t), and w3(t) are the diagonal elements of the diagonal matrix W(t), I is the identity matrix, K(t) is the multiplicative fault matrix, and K(t) = diag(k1(t), k2(t), k3(t)), where k1(t), k2(t), and k3(t) are the diagonal elements of the multiplicative fault matrix K(t); According to the aircraft lift L and rolling moment in formula (3): and yaw moment Ignoring the uncertainties, the three can be rewritten as shown in formula (8): Among them, c L (x lon ) is the lift coefficient, c l (x lat ) is the rolling moment coefficient, c n (x lat ) is the yaw moment coefficient; By analyzing equation (8), we can obtain the expected deflection angle of the control surface under nominal conditions, as shown in equation (9): Among them, δ e,nom is the elevator rudder deflection angle under nominal conditions, δ a,nom is the aileron rudder deflection angle under nominal conditions, δ r,nom is the rudder deflection angle under nominal conditions; The rudder deflection angle values ​​of each operating surface calculated by formula (9) are limited to the specified range, that is: d min <d e,nom ,d a,nom ,d r,nom <d max (10) Among them, δ min is the minimum rudder angle, δ max is the maximum rudder deflection angle; Considering the situation where the elevator fails, the aileron rudder is used to compensate for the lost elevator rudder effect, that is, the control allocation strategy for the failure. The compensation angle of the aileron rudder is shown in formula (11): Among them, c m (x lon ) is the pitching moment coefficient.

2. The aircraft flight fault-tolerant control method for control surface failure according to claim 1, characterized in that: The longitudinal dynamic model of the UAV is shown in formula (1): is the pitch angle rate, Q is the true pitch angle rate, α is the aircraft angle of attack, is the angular rate of the angle of attack, V t is the aircraft airspeed, δ e is the deflection angle of the elevator surface, is a complex number with Q, α, V t and δ e Related functions, m is the mass of the drone, g represents the acceleration of gravity, I y is the moment of inertia about the y-axis, is the dynamic pressure, and is the wing area, is the average aerodynamic chord length of the wing, ρ is the air density, T is the engine thrust, D is the aircraft drag, and L is the aircraft lift; c m0 、 c mδe 、 and are dimensionless coefficients, θ is the true pitch angle, is the rate of change of the aircraft's airspeed; The engine thrust T satisfies the relationship shown in formula (2): Among them, η and δ t represent propeller efficiency and input power respectively.

3. The aircraft flight fault-tolerant control method for control surface failure according to claim 2, characterized in that: The flight parameters of the UAV are simplified to obtain a simplified UAV longitudinal dynamics model, specifically: Construct aircraft drag D, lift L, side force Y, and rolling moment Pitching moment Yaw moment The physical mathematical relationship between and the control surface deflection angle is shown in formula (3): Among them, x lon =[φ,ψ,P,R,β] represents the lateral spatial state vector of the UAV, x lat is the longitudinal space state vector of the UAV, b is the wingspan, δ a and δ r are the deflection angles of the aileron and rudder surfaces, Δ D (x lon ,δ e ) is the unmodeled portion of the aircraft drag D, Δ L (x lon ,δ e ) is the unmodeled portion of the aircraft lift L, Δ Y (x lat ,δ a ,δ r ) is the unmodeled portion of the lateral force Y, Δ l (x lat ,δ a ,δ r ) is the rolling moment The unmodeled part of m (x lon ,δ e ) is the pitching moment The unmodeled part of n (x lat ,δ a ,δ r ) is the yaw moment The unmodeled part, c D (x lon ,δ e ) is the resistance coefficient, c L (x lon ,δ e ) is the lift coefficient, c Y (x lat ,δ a ,δ r ) is the lateral force coefficient, c l (x lat ,δ a ,δ r ) is the rolling moment coefficient, c m (x lon ,δ e ) is the pitching moment coefficient, c n (x lat ,δ a ,δ r ) is the yaw moment coefficient, is the rolling moment, is the yaw moment; First, define the assumptions: A. Since airspeed is controlled separately in the field of aircraft control, the airspeed factor is ignored; B. Assume that the change in angle of attack is a time-dependent function, and that both angle of attack and airspeed vary within a range, i.e., |α|≤α max 、 and 0≤V t,min ≤V t ≤V t,max ; C. Assume that the uncertainty factor exists in the pitching moment and the pitch coefficient c m0 ,c mδe It is known that the pitching moment In relation to the angle of attack, the relationship between the actual value and the used value is shown in formula (4): in, represents the true coefficient value, σ represents the uncertainty between the pitching moment coefficient and the angle of attack, ω represents the uncertainty between the pitching moment coefficient and the derivative of the angle of attack, represents the uncertainty between the pitch moment coefficient and the pitch angular velocity, and assuming that σ, ω and The rate of change is 0, c mα 、 and c mQ All are dimensionless coefficients; The simplified aircraft longitudinal dynamics model is shown in formula (5): in, is the pitch angle acceleration, c mδe is the dimensionless coefficient.

4. The method for controlling a control surface failure-tolerant flight of an aircraft according to claim 1, wherein: The real-time pitch angle and pitch angular velocity of the UAV are estimated based on the state prediction dynamics formula and the adaptive rate formula, specifically: Determine the estimation error, which is shown in formula (12): in, represents the estimated error of the pitch angle, represents the estimated error of the pitch angular velocity, represents the estimated pitch angle, represents the estimated pitch angular velocity; Design the expected estimation error dynamics function, which is shown in formula (13): in, is the error dynamics function of the pitch angle, is the error dynamics function of the pitch angular velocity, L1 and L2 are coefficients; The state prediction dynamic model is shown in formula (14): in, is the estimated rate of change of the pitch angle, is the estimated rate of change of the pitch angle angular rate, and is the uncertainty estimate of the aerodynamic coefficient; Based on equations (13), (14), (5) and (12), a new state prediction dynamics model is obtained as shown in equation (15): in, is the rate of change of the estimated error of the pitch angle, is the rate of change of the estimated error of the pitch angle rate, and is the estimation error of the uncertainty estimation term of the aerodynamic coefficient; Design the adaptive rate to estimate and As shown in formula (16): in, and represents the rate of change of the uncertainty estimate of the aerodynamic coefficient, the Proj function represents the projection algorithm, and γ σ ,γ ω , Represent σ, ω, Adaptive gain estimation of the UAV is performed; the real-time pitch angle and pitch angular velocity of the UAV are estimated by the designed equations (15) and (16).

5. The aircraft flight fault-tolerant control method for control surface failure according to claim 1, characterized in that: The constructed L1 adaptive backstepping attitude controller and the fault-based control allocation strategy generate pitch angle commands with or without faults to control the deflection of the UAV elevator surface, specifically: the elevator deflection amount δ e and aileron deflection δ a Under the action of the force, the UAV maintains the same pitch angle.

6. An aircraft flight fault-tolerant control system for control surface failures for implementing the method of claim 1, characterized in that: It includes a first building module, a simplified module, a second building module, a third building module, a fourth building module and a control module connected in sequence: The first building module is used to analyze the flight state of the UAV based on Newton's second law and Euler's dynamic equations and build a longitudinal dynamic model of the UAV; The simplification module is used to simplify the flight parameters of the UAV based on the UAV longitudinal dynamics model to obtain a simplified UAV longitudinal dynamics model; The second building module is used to build a fault-based control allocation strategy based on a simplified UAV longitudinal dynamics model; The third building block is used to estimate the real-time pitch angle and pitch angular velocity of the UAV based on the state prediction dynamics formula and the adaptive rate formula; The fourth building block is used to build an L1 adaptive backstepping attitude controller based on the real-time pitch angle and pitch velocity of the UAV; The control module is used to generate pitch angle instructions under fault conditions or no fault conditions based on the constructed L1 adaptive backstepping attitude controller and the fault-based control allocation strategy to control the deflection of the UAV elevator surface.

7. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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