An Adaptive Control Method for Autogyro Aircraft

Abstract

This invention provides an adaptive autorotor control method. It conducts in-depth research on the modeling and control of autorotors. Based on the flight characteristics of autorotors, adaptive fast tracking controllers are designed for the rotational speed loop and the quasi-aircraft attitude angle loop, respectively. This method enables parameter identification and rapid command tracking of the autorotor within a limited time even when the inertial parameters are unknown. It also overcomes the shortcomings of existing technologies where command tracking requires a high degree of dependence on the accurate nonlinear model of the aircraft, and has good control performance.

Description

Technical Field

[0001] This invention belongs to the field of aircraft control technology, and particularly relates to an adaptive autorotor aircraft control method. Background Technology

[0002] Autogyroplanes are low-speed, small rotorcraft unmanned aerial vehicles (UAVs) characterized by vertical takeoff and landing (VTOL) and hovering. Unlike traditional rotorcraft, their basic components consist of a rotating wing forming the lifting surface and an electric propeller mounted at the wingtips. The mechanism involves the propeller generating thrust to drive the wing to rotate freely around its main axis, and the rotating wing then produces the lift required for flight. Due to their mechanical simplicity, low drag, high flight stability, and high payload capacity, these aircraft have attracted widespread attention.

[0003] Like traditional rotorcraft, autorotor aircraft are also underactuated systems. Modeling their horizontal, vertical, and rotational motions is extremely complex. Furthermore, considering that some parameters of the aircraft model are difficult to measure in real-world scenarios, identifying parameters of this unknown model to accurately model the dynamic equations and designing a controller to control its rotational speed and attitude angles is a very challenging task.

[0004] The paper "Spincopter wing design and flight control" by Matko Orsag et al. proposes a basic configuration for autorotors, namely, that the basic components of such autorotor aircraft consist of a rotating wing forming the lifting surface and an electric propeller mounted at the wing tip. The mechanism is that the thrust generated by the propeller drives the wing to rotate freely around its main axis, and the rotating wing then generates the lift required for flight. The authors establish a simplified dynamic model of the aircraft in this paper to reveal its inherent stability and design a control system for it. Finally, based on extensive simulations of the autorotor using the X-Plane software package, they elaborate on the design recommendations for the rotating wing.

[0005] However, the paper by Matko Orsag et al. only considers vertical and horizontal motion dynamics, neglecting a more important aspect of aircraft attitude: rotational dynamics. This simplified dynamic model struggles to accurately describe the flight state of actual aircraft and cannot address the unmeasurable nature of certain parameters in real-world scenarios, exhibiting significant technical shortcomings.

[0006] In their paper "PID-based sliding mode control of asynchronous multi-actuator monocopter," Hitesh Bhardwaj et al. established dynamic and kinematic models for a class of single-rotor aircraft. Based on variations in the control signals assigned to the motors, they investigated the flight response of a single-rotor aircraft with a dual-motor + flap configuration. Numerical simulations of step response, waypoint tracking, and trajectory tracking were conducted, considering different application scenarios. A PID-based sliding mode control method was proposed to achieve attitude control of the asynchronous multi-actuator aircraft. Numerical simulations show that the controller can control the single-rotor aircraft even in the presence of noise and exhibits good control performance.

[0007] However, this technology, implemented through a PID-based sliding mode control method, heavily relies on an accurate nonlinear model of the aircraft, meaning the control method requires measuring various parameters of the model. In reality, however, model parameters are often difficult to obtain accurately, and uncertainties always exist within the system. When certain model parameters are unknown, this control method cannot guarantee effective command tracking, resulting in poor control performance. Therefore, parameter identification becomes a crucial technology that urgently needs to be addressed. Summary of the Invention

[0008] To address the aforementioned problems, this invention provides an adaptive autogyro aircraft control method that enables command tracking and parameter identification of an autogyro aircraft within a finite time frame when inertial parameters are unknown.

[0009] An adaptive control method for autorotor aircraft uses a set adaptive rotation speed controller to control the rotation speed of the autorotor aircraft.

[0010] The adaptive rotation speed controller is as follows:

[0011]

[0012] Where, τ y To control the body coordinate system The y-axis can measure the rotational speed ω. y The control torque, All are set rotational speed control gains, and For the body coordinate system Relative to the inertial coordinate system The three-axis rotation speed can be measured. The tracking error is the rotational speed, and there is ω y For the body coordinate system Relative to the inertial coordinate system The y-axis can measure rotational speed. For the given rotation speed command The derivative, Auxiliary variables related to the positive definite symmetric inertial tensor I of an autorotor aircraft The estimated value, and I x For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the x-axis, I y For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the y-axis, I z For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the z-axis, I xz For the autorotor aircraft to orbit around the body coordinate system The angular momentum generated about the z-axis when the x-axis rotates.

[0013] Furthermore, a set attitude angle controller is used to control the pitch and yaw angles of the autogyro aircraft;

[0014] The attitude angle controller is:

[0015]

[0016] Among them, control torque τ x To control the body coordinate system The x-axis on the top can measure the rotational speed ω y The control torque, τ z To control the body coordinate system The z-axis can measure the rotational speed ω. y The control torque, All are set attitude angle control gains, and Auxiliary variables related to the positive definite symmetric inertial tensor I of an autorotor aircraft The estimated value, and ψ is the yaw angle of the autorotor, φ is the roll angle of the autorotor, and g is the sum of the yaw angle ψ, the roll angle φ, and an estimated value. The relevant auxiliary matrix, Auxiliary variables related to the positive definite symmetric inertial tensor I of an autorotor aircraft The estimated value, and f is the regression matrix related to the yaw angle ψ and the roll angle φ, and Φ3 is the regression matrix related to the yaw angle ψ, the roll angle φ, and the three-axis measurable rotational speed. The relevant auxiliary variable, r, is an auxiliary variable related to the attitude angle tracking error.

[0017] Furthermore, the following relationship exists between the yaw angle ψ, pitch angle θ, and roll angle φ of the autorotor aircraft:

[0018]

[0019] in, The first derivative of the roll angle φ Let ω be the second derivative of the roll angle φ. x For the body coordinate system Relative to the inertial coordinate system The x-axis can measure rotational speed. For ω x The first derivative, ω z For the body coordinate system Relative to the inertial coordinate system The z-axis can measure rotational speed. For ω z The first derivative, Let ψ be the first derivative. It is the second derivative of θ.

[0020] Furthermore, the formula for calculating the auxiliary variable r related to the attitude angle tracking error is as follows:

[0021]

[0022] Among them, v e Let v be the tracking error of the attitude angle, and v e =vv d v is the body coordinate system Relative to the inertial coordinate system Measurable attitude angle, v d Given an attitude angle command, For v e The first derivative, α v β v γ v All are set coefficients, and α v >0, β v >0, 0<γ v <1.

[0023] Furthermore, the formula for calculating the regression matrix f related to the yaw angle ψ and roll angle φ is as follows:

[0024]

[0025] Among them, v e Let v be the tracking error of the attitude angle, and v e =vv d v is the body coordinate system Relative to the inertial coordinate system Measurable attitude angle, v d Given an attitude angle command, and φ d For the given roll angle command, For φ d The first derivative, For φ d The second derivative, θ d For a given pitch angle command, For θ d The first derivative, For θ d The second derivative, α v β v γ v All are set coefficients, and α v >0, β v >0, 0<γ v <1, where I represents the positive definite symmetric inertial tensor of the autorotor aircraft, and is the first auxiliary variable related to the yaw angle ψ. Second auxiliary variable related to yaw angle ψ

[0026] Furthermore, along with yaw angle ψ, roll angle φ, and three-axis measurable rotational speed... The formula for calculating the relevant auxiliary variable Φ3 is as follows:

[0027]

[0028] Where, ω x For the body coordinate system Relative to the inertial coordinate system The x-axis can measure rotational speed, ω z For the body coordinate system Relative to the inertial coordinate system The z-axis can measure rotational speed.

[0029] Furthermore, the positive definite symmetric inertial tensor I of the autorotor aircraft is as follows:

[0030]

[0031] in,

[0032] Furthermore, the motors of the autogyro are mounted at the ends of two sets of rotors located on the same straight line, and the attitude kinematics equations of the autogyro are as follows:

[0033]

[0034] Where ψ is the coordinate system of the autorotor aircraft around the quasi-body coordinate system. The roll angle of the x-axis rotation, φ, is the coordinate system of the autorotor aircraft around the quasi-body coordinate system. The y-axis rotation y-angle, θ is the coordinate angle of the autorotor aircraft about the quasi-body coordinate system. The pitch angle of rotation along the z-axis, Let ψ be the first derivative. Let φ be the first derivative. It is the first derivative of θ.

[0035] Furthermore, the estimated value The method to obtain it is as follows:

[0036] The adaptive law for memory enhancement is constructed as follows:

[0037]

[0038] in, for The estimated value, for The first derivative, k γ To set the coefficient, and 0 <k γ <1, tracking error vector Γ、Γ α ,Γ β Both represent adaptive gain, and Γ>0, Γ α >0,Γ β >0, M is the memory feature matrix. For the estimated value The memory-enhanced estimation error matrix, and has L is the memory enhancement coefficient matrix, and L = MW;

[0039] Solve the memory enhancement adaptive law to obtain the estimated value.

[0040] Furthermore, the method for calculating the memory feature matrix M is as follows:

[0041]

[0042] Where t is the integration time, ν is the integration variable, and Φ F(ν) is the frequency domain regression diagonal matrix Φ, and the regression diagonal matrix Φ = diag(Φ1,[Φ2,Φ3]); Φ1 and Φ2 are the triaxial measurable rotational velocities. Related auxiliary variables, and

[0043]

[0044] Beneficial effects:

[0045] 1. This invention provides an adaptive autorotor control method. It conducts in-depth research on the modeling and control of autorotors. Based on the flight characteristics of autorotors, adaptive fast tracking controllers are designed for the rotational speed loop and the quasi-aircraft attitude angle loop, respectively. This method enables parameter identification and fast command tracking of the autorotor within a limited time when the inertial parameters are unknown. It also overcomes the shortcomings of existing technologies where command tracking requires a high degree of dependence on the accurate nonlinear model of the aircraft, and has good control performance.

[0046] 2. This invention provides an adaptive autorotor control method. In real-world scenarios where the aircraft model parameters are unmeasurable, rotational dynamics are added while fully considering horizontal and vertical motion. This establishes a more accurate dynamic and kinematic model for the autorotor, making the description of the autorotor's nonlinear model more accurate.

[0047] 3. This invention provides an adaptive autorotor control method, introducing a memory-enhanced adaptive control strategy to achieve control and unknown parameters. The simultaneous identification process enables accurate estimation of unknown parameters while ensuring the stability of the closed-loop system. Attached Figure Description

[0048] Figure 1 This invention provides a schematic diagram of a self-rotating rotor structure and a coordinate system definition.

[0049] Figure 2 The attitude angle response provided by this invention;

[0050] Figure 3 The attitude angular velocity response provided by this invention;

[0051] Figure 4 The estimated value of the unknown parameter W1 provided by this invention;

[0052] Figure 5 The estimated value of the unknown parameter W2 provided by this invention;

[0053] Figure 6The estimated value of the unknown parameter W3 provided for this invention. Detailed Implementation

[0054] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0055] This invention aims to perform kinematic and dynamic modeling of the horizontal and vertical motion and rotational motion of an autorotor aircraft. Taking into account the problem that the parameters of the aircraft model are unmeasurable in actual situations, the invention identifies the parameters to obtain an accurate dynamic model. Finally, an adaptive controller is designed to track the commands for the rotational speed and attitude angle of the aircraft within a finite time, so as to achieve effective control of the aircraft model with unknown parameters.

[0056] Specifically, the specific implementation process of the present invention is as follows:

[0057] Step 1: Establish the dynamic equations of the autorotor aircraft

[0058] In adaptive control and parameter identification, the concept of finite excitation of the signal v(t) is crucial for ensuring parameter convergence. The definition of finite excitation (FE) is as follows:

[0059] Definition 1: Consider a bounded signal v(t) and a finite time interval [T0, T0 + ΔT], where ΔT > 0. If there exists a positive constant α > 0, such that...

[0060]

[0061] Where I represents an identity matrix of appropriate dimension, then the bounded signal v(t) satisfies the finite excitation condition.

[0062] The following lemma describes the Lyapunov representation of a nonlinear system that converges rapidly in finite time.

[0063] Lemma 1: Consider a nonlinear system Where x is the state vector and t is time. Suppose there exists a continuous positive definite functional V(x,t) such that...

[0064]

[0065] Where α>0, β>0, and 0<γ<1, the nonlinear system can then converge to its equilibrium point in a finite time.

[0066]

[0067] like Figure 1 As shown, an inertial coordinate system is defined. Fixed coordinate system of the machine body Quasi-body coordinate system

[0068] Based on the definition of the coordinate system above, the kinematic equations of attitude can be expressed as:

[0069]

[0070] in, The definition is the body coordinate system. Relative to the inertial coordinate system The measurable angular velocity. ψ is the coordinate system of the autorotator aircraft around the quasi-body coordinate system. The yaw angle of the x-axis rotation, φ is the coordinate angle of the autorotor aircraft about the quasi-body coordinate system. The roll angle of the y-axis rotation, θ is the coordinate system of the autorotor aircraft around the quasi-body coordinate system. The pitch angle of rotation along the z-axis, Let ψ be the first derivative. Let φ be the first derivative. It is the first derivative of θ.

[0071] Assuming the moment of inertia of the autorotor is constant, the attitude dynamics equations can be written as:

[0072]

[0073] in, The positive definite symmetric inertial tensor of an autorotor aircraft:

[0074]

[0075] The formula satisfies In other words, I is an invertible matrix. x For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the x-axis, I y For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the y-axis, I z For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the z-axis, I xz For the autorotor aircraft to orbit around the body coordinate system The angular momentum generated about the z-axis when the x-axis rotates. This represents the control torque, T represents the transpose, and G = -ω. × I y ω y e y Represents the gyroscope torque, where symbol ω × Describes the skew-symmetric matrix of ω, specifically

[0076]

[0077] Compared to other vertical takeoff and landing aircraft (such as quadcopters), autogyros rotate continuously around their main axis during flight. Therefore, considering the attitude in a quasi-body coordinate system is more meaningful than considering the attitude in a body coordinate system. Furthermore, the lift of the fuselage is related to the rotational speed but not to the yaw angle, making rotational speed another important factor to consider. Therefore, the ultimate goal of this paper is to design an adaptive controller that can achieve command tracking and parameter identification within a finite time when the inertial parameters are unknown.

[0078] Step 2: Design a rotation speed controller

[0079] The autogyro aircraft rotates at a speed ω during flight. y around The axis rotates continuously, ω y The dynamic equation can be obtained from (5), that is

[0080]

[0081] Given rotation speed command The tracking error of rotational speed can be defined as:

[0082]

[0083] Its time derivative can be expressed as:

[0084]

[0085] in, These are unknown coefficients related to the parameters of the inertia tensor.

[0086] In order to track the rotation speed command within a limited time We propose the following adaptive controller:

[0087]

[0088] in, This represents the constant control gain. express The estimated value, It is a regression vector.

[0089] Note 1: Note that due to the control torque τ y Since it is included in the regression vector Φ1, the adaptive control law equation (11) cannot be implemented in practical applications. Adding a term to both sides of equation (11) Then divide by simultaneously Then we have

[0090]

[0091] This allows for control of the rotation speed.

[0092] Step 3: Design the attitude angle controller

[0093] Quasi-body coordinate system Relative to the inertial coordinate system The attitude is determined only by the pitch angle θ and the yaw angle ψ, therefore, this invention designs a finite-time tracking controller for φ and θ. From (4), the second derivatives of φ and θ can be formulated as:

[0094]

[0095] To obtain the attitude angle and control torque The mapping relationship between them, the present invention will ω in (5) x and ω z The time derivative is rewritten as:

[0096]

[0097] Substituting equations (4) and (14) into equation (13) and rearranging like terms, we get:

[0098]

[0099] in, and

[0100] Given attitude angle command The tracking error of the attitude angle can then be expressed as:

[0101] v e =vv d (16)

[0102] Where v is the quasi-body coordinate system Relative to the inertial coordinate system Measurable attitude angle, v d For the given attitude angle command;

[0103] The auxiliary variable r, defined as being related to the attitude angle tracking error, is as follows:

[0104]

[0105] Its time derivative can be written as

[0106]

[0107] In the formula, α v >0, β v >0, and 0<γ v <1.

[0108] Here is defined

[0109] Substituting equation (15) into equation (18) yields

[0110]

[0111] In the formula, This represents the unknown parameters related to the inertia tensor coefficients. Φ2, Φ3, and f represent the regression matrix, i.e.

[0112]

[0113] Where f is the regression matrix related to the yaw angle ψ and the roll angle φ, and Φ2 and Φ3 are the regression matrices related to the yaw angle ψ, the roll angle φ, and the three-axis measurable rotational speed. Related auxiliary variables; v d Given an attitude angle command, and φ d For the given roll angle command, For φ d The first derivative, For φ d The second derivative, θ d For a given pitch angle command, For θ d The first derivative, For θ d The second derivative; ω x For the body coordinate system Relative to the inertial coordinate system The x-axis can measure rotational speed, ω z For the body coordinate system Relative to the inertial coordinate system The z-axis can measure rotational speed.

[0114] In order to track the attitude angle command v within a limited time d The present invention will employ the following adaptive controller:

[0115]

[0116] in, and These represent the estimated values ​​of the unknown constants W2 and W3, respectively.

[0117] Note 2: Similar to the rotational speed controller (11), the torque control (20) cannot be implemented in practical applications. The controller in equation (20) can be simplified as follows:

[0118]

[0119] In the formula,

[0120] Step 4: Design a memory-enhancing adaptive law

[0121] In rotational speed adaptive controllers and attitude angle controllers, the estimated value For unknown quantities, we need to obtain an estimated value. Then estimate the value These parameters are incorporated into the rotational speed adaptive controller and attitude angle controller to control the rotational speed, pitch angle, and yaw angle of the autorotor aircraft.

[0122] Based on this, substituting the rotational speed controller equation (11) and the attitude angle controller equation (20) into equations (10) and (18), we can obtain the following closed-loop dynamic equations:

[0123]

[0124] The tracking errors are summed up, that is The dynamic equation (22) of the closed-loop system can be simplified to:

[0125]

[0126] In the formula, 0 <k γ <1.

[0127] The remaining term in equation (23) Then there is

[0128]

[0129] Assuming the initial tracking error is zero, we can transform equation (24) from the t-domain to the s-domain, in the form of:

[0130] Φ(s)W=(sI+k α η(s)+ε(s) (25)

[0131] Consider a stable first-order low-pass filter of the following form:

[0132]

[0133] In the formula, τ represents the time constant of the filter.

[0134] Multiplying both sides of equation (25) by F(s) yields the closed-loop system dynamics equation in the s-domain after low-pass filtering.

[0135] Φ F (s)W=(sI+k α )η F (s)+ε F (s) (27)

[0136] Where the subscript F represents the signal filtered by F(s), i.e., η F (s)=F(s)η(s). Furthermore, according to the following transformation:

[0137]

[0138] The dynamic equation (27) of the closed-loop system in the s-domain can be further simplified to:

[0139]

[0140] Assume ξ is The result of the inverse Laplace transform is that the time derivative of ξ in the t domain is...

[0141]

[0142] Where ξ(0) = 0. Therefore, the inverse Laplace transform of equation (29) can be written as:

[0143]

[0144] In the formula, Φ F It is Φ F The representation of (s) in the t domain can be calculated by the following formula.

[0145]

[0146] In the formula Φ F (0) = 0;

[0147] The integral of the filtered regression matrix over time t is defined as the memory feature.

[0148]

[0149] t is the integration time, ν is the integration variable, and Φ is the integration variable. F (ν) is the regression diagonal matrix Φ in the frequency domain, and the regression diagonal matrix Φ = diag(Φ1,[Φ2,Φ3]);

[0150] Considering equation (31), the present invention can obtain the unknown coefficients of memory enhancement:

[0151]

[0152] Then, the memory enhancement estimation error can be defined as

[0153]

[0154] To identify unknown coefficients within a finite time, the following memory-enhancing adaptive law is proposed.

[0155]

[0156] In the formula, Γ>0, Γ α >0,Γ β >0 indicates adaptive gain.

[0157] The objective of this invention is to design an adaptive controller for autogyros, enabling command tracking and parameter identification within a finite time frame when inertial parameters are unknown. To demonstrate the superiority of the proposed Finite-time Adaptive Control and Identification (FTACI) method, this invention compares it with Traditional Adaptive Control (TAC), Finite-time Adaptive Control (FTAC), and Finite-time Adaptive Concurrent Learning Control (FTACC) to identify alternative solutions. Figures 2-6 Numerical simulation results for various control methods are presented. From Figure 2 It can be seen that the proposed control methods (FTACI) and FTAC can achieve finite-time tracking of attitude angle commands, while FTAC and TAC cannot. For rotational speed control, all control methods can achieve command tracking, such as... Figure 3 As shown. Figures 4-6 This indicates that the proposed FTACI can achieve finite-time identification of unknown coefficients, while the other three methods cannot. Simulation results show that, with this control method, the estimated values ​​will converge to their nominal values ​​within a finite time.

[0158] In summary, the Finite-Time Adaptive Control and Identification (FTACI) method innovatively proposed in this invention enables command tracking and parameter identification of an autorotor aircraft within a finite time when the inertial parameters are unknown, a goal that other control strategies cannot achieve.

[0159] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. An adaptive autorotor control method, characterized in that, The rotational speed of the autogyro aircraft is controlled by a pre-defined adaptive rotational speed controller. The adaptive rotation speed controller is as follows: Where, τ y To control the body coordinate system The y-axis can measure the rotational speed ω. y The control torque, All are set rotational speed control gains, and For the body coordinate system Relative to the inertial coordinate system The three-axis rotation speed can be measured. The tracking error is the rotational speed, and there is ω y For the body coordinate system Relative to the inertial coordinate system The y-axis can measure rotational speed. For the given rotation speed command The derivative, The auxiliary variable W1 = [W] represents the variable related to the positive definite symmetric inertial tensor I of the autorotor aircraft. 11 W 12 W 13 ] T The estimated value, and I x For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the x-axis, I y For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the y-axis, I z For the autorotor aircraft to orbit around the body coordinate system The angular momentum of rotation along the z-axis, I xz For the autorotor aircraft to orbit around the body coordinate system The angular momentum generated about the z-axis when the x-axis rotates.

2. The adaptive autorotor control method as described in claim 1, characterized in that, It also employs a pre-defined attitude angle controller to control the pitch and yaw angles of the autogyro aircraft; The attitude angle controller is: Wherein, the control torque u=[τ x ,τ z ] T , τ x To control the body coordinate system The x-axis on the top can measure the rotational speed ω y The control torque, τ z To control the body coordinate system The z-axis can measure the rotational speed ω. y The control torque, All are set attitude angle control gains, and The auxiliary variable W2 = [W] represents the positive definite symmetric inertial tensor I of the autorotor aircraft. 21 W 22 W 23 ] T The estimated value, and ψ is the yaw angle of the autorotor, φ is the roll angle of the autorotor, and g is the sum of the yaw angle ψ, the roll angle φ, and an estimated value. The relevant auxiliary matrix, The auxiliary variable W3 = [W] represents the variable related to the positive definite symmetric inertial tensor I of the autorotor aircraft. 31 W 32 W 33 ] T The estimated value, and f is the regression matrix related to the yaw angle ψ and the roll angle φ, and Φ3 is the regression matrix related to the yaw angle ψ, the roll angle φ, and the three-axis measurable rotational speed ω=[ω x ,ω y ,ω z ] T The relevant auxiliary variable, r, is an auxiliary variable related to the attitude angle tracking error.

3. The adaptive autorotor control method as described in claim 2, characterized in that, The following relationships exist between the yaw angle ψ, pitch angle θ, and roll angle φ of an autorotor aircraft: in, The first derivative of the roll angle φ Let ω be the second derivative of the roll angle φ. x For the body coordinate system Relative to the inertial coordinate system The x-axis can measure rotational speed. For ω x The first derivative, ω z For the body coordinate system Relative to the inertial coordinate system The z-axis can measure rotational speed. For ω z The first derivative, Let ψ be the first derivative. It is the second derivative of θ.

4. The adaptive autorotor control method as described in claim 2, characterized in that, The formula for calculating the auxiliary variable r related to attitude angle tracking error is as follows: Among them, v e Let v be the tracking error of the attitude angle, and v e =vv d v is the body coordinate system Relative to the inertial coordinate system Measurable attitude angle, v d Given an attitude angle command, For v e The first derivative, α v β v γ v All are set coefficients, and α v >0, β v >0, 0<γ v <1.

5. The adaptive autorotor control method as described in claim 2, characterized in that, The formula for calculating the regression matrix f related to the yaw angle ψ and roll angle φ is as follows: Among them, v e Let v be the tracking error of the attitude angle, and v e =vv d v is the body coordinate system Relative to the inertial coordinate system Measurable attitude angle, v d Given an attitude angle command, and v d =[φ d ,θ d ] T φ d For the given roll angle command, For φ d The first derivative, For φ d The second derivative, θ d For a given pitch angle command, For θ d The first derivative, For θ d The second derivative, α v β v γ v All are set coefficients, and α v >0, β v >0, 0<γ v <1, where I represents the positive definite symmetric inertial tensor of the autorotor aircraft, and is the first auxiliary variable related to the yaw angle ψ. Second auxiliary variable related to yaw angle ψ 6. The adaptive autorotor control method as described in claim 2, characterized in that, Along with yaw angle ψ, roll angle φ, and three-axis measurable rotational speed ω=[ω x ,ω y ,ω z ] T The formula for calculating the relevant auxiliary variable Φ3 is as follows: Where, ω x For the body coordinate system Relative to the inertial coordinate system The x-axis can measure rotational speed, ω z For the body coordinate system Relative to the inertial coordinate system The z-axis can measure rotational speed.

7. The adaptive autorotor control method as described in any one of claims 1 to 6, characterized in that, The positive definite symmetric inertial tensor I of an autorotor aircraft is as follows: in, 8. The adaptive autorotor control method as described in claim 1, characterized in that, The motors of the autogyro are mounted at the ends of two sets of rotors located in a straight line, and the attitude kinematics equations of the autogyro are as follows: Where ψ is the coordinate system of the autorotor aircraft around the quasi-body coordinate system. The roll angle of the x-axis rotation, φ, is the coordinate system of the autorotor aircraft around the quasi-body coordinate system. The y-axis rotation y-angle, θ is the coordinate angle of the autorotor aircraft about the quasi-body coordinate system. The pitch angle of rotation along the z-axis, Let ψ be the first derivative. Let φ be the first derivative. It is the first derivative of θ.

9. The adaptive autorotor control method as described in claim 2, characterized in that, estimated value The method to obtain it is as follows: The adaptive law for memory enhancement is constructed as follows: in, for The estimated value, for The first derivative, k γ To set the coefficient, and 0 <k γ <1, tracking error vector Γ、Γ α ,Γ β Both represent adaptive gain, and Γ>0, Γ α >0,Γ β >0, M is the memory feature matrix. For estimated value The memory-enhanced estimation error matrix, and has L is the memory enhancement coefficient matrix, and L = MW; Solve the memory enhancement adaptive law to obtain the estimated value.

10. The adaptive autorotor control method as described in claim 9, characterized in that, The method for calculating the memory feature matrix M is as follows: Where t is the integration time, ν is the integration variable, and Φ F (ν) is the frequency domain regression diagonal matrix Φ, and the regression diagonal matrix Φ = diag(Φ1,[Φ2,Φ3]); Φ1 and Φ2 are both related to the triaxial measurable rotational speed ω = [ω x ,ω y ,ω z ] T Related auxiliary variables, and

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