Adaptive preset performance fault-tolerant control method for hypersonic aircraft

Abstract

A hypersonic aircraft adaptive preset performance fault-tolerant control method comprises the following steps: S1, establishing a dynamic model of a hypersonic aircraft with an unknown elevator fault, and converting the dynamic model into a state-space equation for describing a height subsystem and a speed subsystem of the hypersonic aircraft; s2, constructing a fixed time preset performance function of a speed subsystem based on the state-space equation, approaching the fixed time preset performance function by adopting a radial basis function neural network, and designing a parameter update rate and actual control input of the speed subsystem; according to the method, under the condition that the hypersonic aircraft elevator breaks down, it can be ensured that the actual finite time of the closed-loop system is stable, so that the flight safety and performance of the hypersonic aircraft are powerfully guaranteed, boundary information of fault parameters does not need to be obtained in advance, and the adaptability and reliability of the system are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hypersonic vehicle control, and specifically to an adaptive preset performance fault-tolerant control method for hypersonic vehicles. Background Art

[0002] A hypersonic vehicle is an advanced vehicle with a flight speed exceeding five times the speed of sound and mainly flying in the near space. It can form a powerful deterrent to strategic attack targets and achieve rapid reconnaissance of targets worldwide. In practical applications, its extremely high flight speed, complex and changeable flight environment, flight envelope constraints, as well as factors such as unmodeled dynamics, random noise, and external interference, pose extremely high requirements for the safety and reliability of the flight control system. It should be noted that when faults such as actuator jamming or insufficient output torque occur, the control accuracy and the stability of the closed-loop system will be significantly reduced, making it unable to accurately execute the instructions issued by the controller, and thus resulting in a slower response speed and an increased overshoot of the vehicle.

[0003] Although existing adaptive fault-tolerant control methods for hypersonic vehicles can compensate for actuator faults to a certain extent, they have deficiencies in adjusting transient performance and steady-state performance requirements, and it is difficult to simultaneously ensure core indicators such as convergence time, maximum overshoot, and steady-state accuracy.

[0004] Therefore, there is an urgent need to design an adaptive preset performance finite-time fault-tolerant controller for hypersonic vehicles suffering from unknown elevator faults to improve the system dynamic performance and achieve fast tracking of the reference trajectory in the case of elevator faults. Summary of the Invention

[0005] The purpose of the present invention is to propose an adaptive preset performance fault-tolerant control method for hypersonic vehicles, which can ensure the actual finite-time stability of the closed-loop system in the case of elevator faults of hypersonic vehicles, thus effectively guaranteeing the flight safety and performance of hypersonic vehicles, and without the need to obtain the boundary information of fault parameters in advance, greatly improving the adaptability and reliability of the system.

[0006] The technical solution adopted by the present invention is: an adaptive preset performance fault-tolerant control method for hypersonic vehicles, including the following steps:

[0007] S1. Establish a dynamic model of a hypersonic vehicle with unknown elevator faults and transform it into a state-space equation describing the altitude subsystem and speed subsystem of the hypersonic vehicle;

[0008] S2. Construct the fixed-time preset performance function η(t) of the velocity subsystem based on the state-space equation, approximate the fixed-time preset performance function η(t) using a radial basis function neural network, and design the parameter update rate and actual control input Ψ of the velocity subsystem c ;

[0009] S3. Introduce the velocity tracking error e v (t) of the constrained velocity subsystem, and construct the error transformation function and transformation equation to obtain the unconstrained equivalent error

[0010] S4. Based on the equivalent error and the adaptive command backstepping control method, construct the coordinate transformation equation, and construct a finite-time command filter, an error compensation system, and the first virtual control law α for the altitude subsystem 1 ;

[0011] Design the parameter update law of the altitude subsystem based on the radial basis function neural network, and design the second virtual control law α for the altitude subsystem 2 ;

[0012] Design the intermediate control law α of the altitude subsystem based on the new virtual control law and the error compensation system 3 and the actual control input ξ q ;

[0013] S5. Analyze the stability of the closed-loop of the altitude subsystem and the velocity subsystem of the hypersonic vehicle under the actual control input Ψ c and the actual control input ξ q , and determine the controller gains of the first virtual control law α 1 , the second virtual control law α 2 , the parameter update law, and the intermediate control law α 3 ;

[0014] S6. Perform finite-time preset performance fault-tolerant control on the hypersonic vehicle based on the determined controller gains.

[0015] As an optimal solution, step S5 includes the following sub-steps:

[0016] S501. Construct the first Lyapunov function V 1 for the coordinate transformation equation of the altitude subsystem, design the first virtual control law α 1 and the parameter update law

[0017] Based on the first Lyapunov function V 1 , construct the second Lyapunov function V2 Design the second virtual control law α of the altitude subsystem of the hypersonic vehicle 2 ;

[0018] Based on the second Lyapunov function V 2 Construct the third Lyapunov function V 3 Let the actual control input ξ of the altitude subsystem of the hypersonic vehicle q and the parameter update law Parameter update law and the parameter update law

[0019] S502. For the speed subsystem of the hypersonic vehicle, construct the fourth Lyapunov function V 4 Design the actual control input Ψ of the speed subsystem of the hypersonic vehicle c and the parameter update law

[0020] S503. According to the third Lyapunov function V 3 and the fourth Lyapunov function V 4 Construct the fifth Lyapunov function V 5 Based on the Lyapunov stability theory, analyze the stability of the closed-loop speed subsystem and the closed-loop altitude subsystem of the hypersonic vehicle, and determine the controller gains to be designed;

[0021] S504. For the error compensation system, construct the sixth Lyapunov function V 6 to make all signals of the closed-loop system actually finite-time bounded.

[0022] As a preferred solution, in step S1, the unknown elevator fault model suffered by the hypersonic vehicle is:

[0023]

[0024] where: q = 1, 2, the elevator deflection angle u q is the control input signal of the hypersonic vehicle, k q，h ∈(0, 1] is the actuator efficiency coefficient, ξ q is the actual control input, is the unknown time-varying deviation fault, and represent the start time and the end time of the elevator fault respectively.

[0025] As a preferred solution, in step S4, the coordinate transformation equation is:

[0026]

[0027] Where: e i is the error before compensation, ω i is the error compensation signal, i = 1, 2, 3, e 1 = x 1 - γ d , e 2 = x 2 - x 2c , e 3 = x 3 - x 3c ; γ d is the reference trajectory of the track angle; x 1 , x 2 and x 3 are the system states; χ 1 , χ 2 , χ 3 and χ 4 are the first compensation error, the second compensation error, the third error compensation error and the fourth error variable respectively; is the unconstrained equivalent error; δ min and δ max are positive design parameters;

[0028] The finite-time command filter is designed as:

[0029]

[0030] Where, α 1 and α 2 are the first virtual control law and the second virtual control law respectively, x 2c and x 3c are the output signals of the finite-time command filter, ρ, β 1 and β 2 are positive design parameters, sign(·) is the sign function;

[0031] The error compensation system is designed as:

[0032]

[0033] Where: K 1 , K 2 , K 3 , i 1 , i 2 and ι 3 are positive design parameters; g 1 and g 2 are system parameters.

[0034] As an optimal solution, the first virtual control law α 1 is designed as:

[0035]

[0036] where: c 1 and a 1 are positive design parameters, is the estimated value of θ 1 , is the transpose of the radial basis function , is the derivative of the track angle reference trajectory γ d ;

[0037] The parameter update law is designed as:

[0038]

[0039] where: μ f1 and are positive design parameters.

[0040] As an optimal solution, the second virtual control law α 2 is designed as:

[0041]

[0042] where: c 2 is a positive design parameter, is the derivative of the output signal x 2c of the finite-time command filter.

[0043] As an optimal solution, the actual control input ξ q of the hypersonic vehicle altitude subsystem is:

[0044]

[0045] where: and are the estimated values of N and θ 3 and respectively; τ, c 3 , a 3 and are positive design parameters, is the derivative of the output signal x 3c of the finite-time command filter, is the transpose of the radial basis function ;

[0046] The parameter update law The parameter update law and the parameter update law are designed as:

[0047]

[0048] where: μN , μ f3 , and are positive design parameters.

[0049] As a preferred solution, the actual control input Ψ of the hypersonic vehicle speed subsystem c is:

[0050]

[0051] where: g 4 is a system variable, e v (t) is the speed tracking error, η(t) is the fixed-time preset performance function, a 4 and c 4 are positive design parameters, is the estimated value of θ 4 , is the transpose of the radial basis function ;

[0052] The parameter update law is designed as:

[0053]

[0054] where: μ f4 and are positive design parameters.

[0055] Compared with the prior art, the beneficial effects of the present invention are:

[0056] 1) The adaptive preset performance finite-time fault-tolerant control method disclosed in the present invention can ensure that all signals of the closed-loop system are finite-time bounded, and at the same time enable the output trajectory of the hypersonic vehicle to quickly and accurately track the reference trajectory. This method effectively compensates for the adverse effects caused by unknown elevator faults by designing the parameter update law and the parameter update law, and does not require prior knowledge of the elevator fault parameters. In addition, by constructing a finite-time command filter and an error compensation system, not only the "computational complexity explosion" problem is avoided, but also the influence of filtering errors on the tracking performance is solved, ensuring that the hypersonic vehicle always maintains excellent flight performance and reliability under complex and changeable flight conditions.

[0057] 2) Different from the traditional exponential preset performance function control scheme, the present invention ensures that the speed tracking error can accurately converge within the envelope of the performance function within a specified time according to the preset performance index by designing a fixed-time preset performance function. This design not only significantly improves the transient and steady-state performance of the system but also realizes the refined control of the system's dynamic behavior. The design parameters of the fixed-time preset performance function are highly flexible and can be adjusted in real-time according to the specific control task requirements, so that appropriate performance indicators can be flexibly selected under different flight scenarios and task requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following-described drawings are only some embodiments of the invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0059] Figure 1 is a schematic structural diagram of a hypersonic vehicle;

[0060] Figure 2 is a structural diagram of the tracking control method of a hypersonic vehicle;

[0061] Figure 3 is a trajectory diagram of the altitude tracking error of a hypersonic vehicle;

[0062] Figure 4 is a trajectory diagram of the speed tracking error of a hypersonic vehicle;

[0063] Figure 5 is a control input curve diagram of the altitude subsystem of a hypersonic vehicle;

[0064] Figure 6 is a control input curve diagram of the speed subsystem of a hypersonic vehicle. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] Hereinafter, the present invention will be specifically described by way of exemplary embodiments. However, it should be understood that, without further description, the elements, structures, and features in one embodiment can also be beneficially combined into other embodiments.

[0066] It should be noted that: unless otherwise defined, the technical terms or scientific terms used in this article should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The words such as "a", "an" or "the" used in the specification and claims of this invention patent application do not express a limitation of quantity, but mean that there is at least one; the "first", "second" and "third" used in this article should not be regarded as a limitation of the order of components, but only to distinguish different components; words such as "including" or "comprising" indicate that the elements or objects appearing before "including" or "comprising" cover the elements or objects listed after "including" or "comprising" and their equivalents, but do not exclude other elements or objects with the same functions.

[0067] In order to more clearly describe the adaptive preset performance fault-tolerant control method for a hypersonic vehicle, the following describes this embodiment in conjunction with the attached Figure 1-6 description:

[0068] As Figure 2 shown, an adaptive preset performance fault-tolerant control method for a hypersonic vehicle includes the following steps:

[0069] S1. Establish a dynamic model of a hypersonic vehicle with unknown elevator faults and transform it into state space equations describing the altitude subsystem and speed subsystem of the hypersonic vehicle;

[0070] The dynamic model is as follows:

[0071]

[0072] The expression obtained by curve fitting

[0073]

[0074] Where:

[0075]

[0076] ρ is the air density; S, and R E are the reference area, reference length and radius of the earth respectively; u q and Ψ are the elevator deflection angle and engine throttle opening respectively; V and h are the flight speed and altitude respectively; q, γ and α are the pitch angular velocity, flight path angle and angle of attack respectively; T, D, L and M yy represent thrust, drag, lift and pitching moment respectively; m, I yy μ and r represent the mass of the aircraft, the moment of inertia about the pitch axis, the gravitational constant and the radial distance to the center of the earth respectively.

[0077] The second-order system model of the engine throttle input is as follows:

[0078]

[0079] The unknown elevator fault model suffered by the hypersonic vehicle is:

[0080]

[0081] where q = 1, 2, the elevator deflection angle u q is the control input signal of the hypersonic vehicle, and k q，h ∈(0, 1] is the actuator efficiency coefficient, and ξ q is the actual control input, is the unknown time-varying deviation fault, and represent the start time and end time of the elevator fault respectively.

[0082] To simplify the subsequent reasoning, the dynamic model of the hypersonic vehicle system is summarized as a state-space equation:

[0083]

[0084] where, when Ψ c ≤1, f 4 = -(D / m + μsinγ / r 2 ); when Ψ c > 1,

[0085] Define the altitude tracking error as e h = h - h d , where h d represents the desired altitude, and its derivative is:

[0086]

[0087] The relationship between the flight path angle and altitude is altitude-coupled. To reduce the order of the system, first, the altitude tracking problem is transformed into a flight path angle tracking problem in the altitude controller. The reference flight path angle γ d obtained from the inverse design idea is:

[0088]

[0089] where l h and l 0 are positive constants.

[0090] S2. Construct the fixed-time preset performance function η(t) of the velocity subsystem based on the state-space equation, approximate the fixed-time preset performance function η(t) using a radial basis function neural network, and design the parameter update rate and actual control input Ψ of the velocity subsystem c ;

[0091] The main control objective of hypersonic vehicle tracking control is that the output trajectories h and V track the reference trajectories h d and V d as closely as possible, which will generate two altitude tracking errors e h = h - h d and velocity tracking error e v = V - V d . To make the velocity tracking error have good transient and steady-state performance, the following fixed-time preset performance function η(t) is constructed to constrain the tracking error e v :

[0092]

[0093] where η 0 and η ∞ are the initial value and steady-state value of the fixed-time performance function respectively, and T f is the convergence time to be designed. The convergence characteristic of the fixed-time preset performance function is used to constrain the velocity tracking error e v , so that the velocity tracking error converges to the preset performance interval within the constrained convergence time T f .

[0094] S3. Introduce the velocity tracking error e v (t) of the constrained velocity subsystem, and construct the error transformation function and transformation equation based on the fixed-time preset performance function η(t) to obtain the unconstrained equivalent error

[0095] To achieve the control objective of constraining the tracking error, the following inequality relationship is established to limit the tracking error within the envelope of the preset performance function η(t):

[0096] -n(t) ≤ e v (t) ≤ n(t). (8)

[0097] Furthermore, to avoid the increase in the complexity and difficulty of controller design caused by the introduction of the fixed-time preset performance function, an equality relationship and an error transformation function

[0098]

[0099] Convert the tracking error subject to inequality constraints into an equivalent error without constraints Furthermore, it can be obtained that:

[0100]

[0101] Among them,

[0102] S4. Based on the equivalent error and the adaptive command backstepping control method, construct a coordinate transformation equation, and construct a finite-time command filter, an error compensation system, and a first virtual control law α 1 ;

[0103] The coordinate transformation equation is:

[0104]

[0105] Among them: e i is the error before compensation, ω i is the error compensation signal, i = 1, 2, 3, e 1 = x 1 -γ d , e 2 = x 2 -x 2 c, e 3 = x 3 -x 3c ; γ d is the track angle reference trajectory; x 1 , x 2 and x 3 are the system states; χ 1 , χ 2 , χ 3 and χ 4 are the first compensation error, the second compensation error, the third error compensation error, and the fourth error variable respectively; is the equivalent error without constraints; δ min and δ max are positive design parameters;

[0106] The finite-time command filter is designed as:

[0107]

[0108] Among them, α 1 and α 2 are the first virtual control law and the second virtual control law respectively, x 2c and x 3c are the output signals of the finite-time command filter, ρ, β 1 and β 2is a positive design parameter, and sign(·) is the sign function;

[0109] The error compensation system is designed as:

[0110]

[0111] where: K 1 、K 2 、K 3 、i 1 、i 2 and ι 3 are positive design parameters; g 1 and g 2 are system parameters.

[0112] Design the parameter update law of the altitude subsystem based on the radial basis function neural network, and design the second virtual control law α 2 for the altitude subsystem;

[0113] Design the intermediate control law α 3 of the altitude subsystem and the actual control input ξ q based on the new virtual control law and the error compensation system;

[0114] S5. Analyze the stability of the closed-loop of the hypersonic vehicle altitude subsystem and speed subsystem under the actual control input Ψ c and the actual control input ξ q , and determine the controller gains of the first virtual control law α 1 , the second virtual control law α 2 , the parameter update law, and the intermediate control law α 3 ;

[0115] Specifically, it includes the following steps:

[0116] S501. Construct the first Lyapunov function V 1 for the coordinate transformation equation of the altitude subsystem, design the first virtual control law α 1 and the parameter update law

[0117] The first Lyapunov function V 1 constructed is as follows:

[0118]

[0119] where, μ f1 is a positive design parameter.

[0120] Furthermore, take the derivative of the first Lyapunov function V 1 with respect to time, and we can get:

[0121]

[0122] Use a radial basis function neural network to approximate the nonlinear function f 1 (x 1 ), which can be specifically expressed as:

[0123]

[0124] where, represents the ideal weight vector, represents the radial basis function with input x 1 , ε 1 represents the approximation error and satisfies is an unknown positive constant, represents transpose.

[0125] Construct the first virtual control law α 1 and the parameter update law as:

[0126]

[0127] where: a 1 , K 1 , c 1 , and are positive controller gains to be designed, is the estimated value of θ 1 .

[0128] Substitute the designed first virtual control law α 1 , the parameter update law and the error compensation signal into formula (15), and we can get:

[0129]

[0130] Based on the first Lyapunov function V 1 , construct the second Lyapunov function V 2 , and design the second virtual control law α 2 for the altitude subsystem of the hypersonic vehicle;

[0131] The second Lyapunov function V 2 is:

[0132]

[0133] Furthermore, take the derivative of formula (20) with respect to time t, and we can get:

[0134]

[0135] Construct the second virtual control law α 2 as follows:

[0136]

[0137] where c 2 and K 2 are positive controller gains to be designed.

[0138] Based on the second Lyapunov function V 2 , construct the third Lyapunov function V 3 . Let the actual control input ξ of the hypersonic vehicle altitude subsystem q , the parameter update law Parameter update law and the parameter update law

[0139] Construct the third Lyapunov function V 3 :

[0140]

[0141] where Π is an unknown positive constant, and μ f3 , and μ N are positive constants.

[0142] Furthermore, taking the derivative of formula (23) with respect to time t, we get:

[0143]

[0144] Adopt the radial basis function neural network technology to approximate the nonlinear function f 3 (x 1 , x 2 , x 3 ). Specifically, it can be expressed as:

[0145]

[0146] where represents the ideal weight vector, represents the radial basis function with the input being f 3 (x 1 , x 2 , x 3 ), ε 3 represents the approximation error and satisfies is a positive constant, represents transpose of

[0147] Due to the complex and variable flight environment of hypersonic vehicles, they are more prone to problems such as airframe vibration and deformation than conventional aircraft. This may further cause failures of physical components such as actuators, reduce flight performance, and even lead to flight accidents. For the elevator fault model suffered, it is defined that:

[0148]

[0149] Among them, and are the estimated values of and N respectively, and the estimation errors are expressed as

[0150] The actual control input ξ q , the third virtual control law α 3 , the parameter update law Parameter update law And the parameter update law are designed as follows:

[0151]

[0152]

[0153] Among them, a 3 , c 3 , K 3 , ζ N And π are positive controller gains to be designed, is the estimated value of θ 3 .

[0154] Substitute the actual control input ξ q , the third virtual control law α 3 , the error compensation signal Parameter update law Parameter update law And the parameter update law into Equation (24), and the calculation shows that:

[0155]

[0156] Among them:

[0157]

[0158] S502. For the speed subsystem of the hypersonic vehicle, construct the fourth Lyapunov function V 4 , and design the actual control input Ψ c of the speed subsystem of the hypersonic vehicle and the parameter update law

[0159] The fourth Lyapunov function V of the structure 4 is as follows:

[0160]

[0161] where μ f4 is a positive design parameter,

[0162] Furthermore, differentiating formula (33) with respect to time t, we can obtain:

[0163]

[0164] A radial basis function neural network is used to approximate the composite function which can be specifically expressed as:

[0165]

[0166] where represents the ideal weight vector, represents the radial basis function with input F, and ε 4 represents the approximation error and satisfies is a positive constant, represents the transpose of

[0167] Construct the following actual control input Ψ c and the parameter update law

[0168]

[0169] where a 4 、K 4 、 and c 4 are positive controller gains to be designed, is the estimated value of θ 4

[0170] Substitute the actual control input Ψ c and the parameter update law into (34), we can obtain:

[0171]

[0172] S503. According to the third Lyapunov function V 3 and the fourth Lyapunov function V 4 , construct the fifth Lyapunov function V 5 ​, analyze the stability of the closed-loop speed subsystem and altitude subsystem of the hypersonic vehicle based on the Lyapunov stability theory, and determine the controller gain to be designed;

[0173] The constructed fifth Lyapunov function V 5 is:

[0174] V 5 = V 3 + V 4 . (39)

[0175] Furthermore, take the derivative of the fifth Lyapunov function V 5 with respect to time, and the calculation shows that:

[0176]

[0177] Among them,

[0178] Based on the Lyapunov finite-time stability theory, the adaptive preset performance finite-time fault-tolerant control scheme disclosed in the present invention can ensure the actual finite-time stability of the altitude subsystem and speed subsystem of the hypersonic vehicle, and the closed-loop signal χ i (i = 1, 2, 3, 4) can converge to a small neighborhood near the origin within a finite time .

[0179] S504. For the error compensation system, construct the sixth Lyapunov function V 6 to make all signals of the closed-loop system actually finite-time bounded.

[0180] The constructed sixth Lyapunov function V 6 is:

[0181]

[0182] Take the derivative of the sixth Lyapunov function V 6 , and the calculation shows that:

[0183]

[0184] Among them, the inequality satisfies ||x (j+1)c - α j || ≤ Ω j , where Ω j is an unknown constant that satisfies ι j > Ω j ; Z 3 = 2min{K i}, Based on the Lyapunov-based finite-time stability theory, the error compensation system can converge to stability within a finite time.

[0185] So far, the design of the improved finite-time prescribed performance fault-tolerant tracking controller for hypersonic vehicles has been completed.

[0186] S6. Perform finite-time prescribed performance fault-tolerant control on the hypersonic vehicle based on the determined controller gains.

[0187] To illustrate the control effect of the proposed scheme in detail, a simulation experiment will be carried out in MATLAB with a fixed simulation step size of 0.0001. The system model parameters of the hypersonic vehicle are shown in Table 1 below:

[0188] Table 1: System model parameters

[0189]

[0190]

[0191] The elevator fault parameter is selected as: k q = 0.5,

[0192] The simulation results are plotted in Figures 3 to 6 . Figure 3 The tracking error curve of the altitude subsystem of the hypersonic vehicle is plotted. Figure 4 The tracking error curve of the speed subsystem of the hypersonic vehicle is plotted. It can be clearly seen from Figure 4 that the hypersonic speed tracking error converges within the envelope of the time performance function within the preset time T f = 15 s. Figure 5 And Figure 6 are the control input diagrams of the altitude subsystem and the speed subsystem respectively. Combining the results of these simulation experiments, the adaptive prescribed performance finite-time fault-tolerant method designed in this invention can ensure that, in the case of the hypersonic vehicle suffering from unknown elevator faults, all signals of the closed-loop altitude subsystem and speed subsystem are actually finite-time bounded. At the same time, the speed tracking error can evolve to the pre-set performance interval within the given time, thus significantly improving the transient performance and steady-state performance of the system, fully demonstrating the excellent effectiveness of this invention in improving the control performance of hypersonic vehicles.

[0193] The parts not detailed in the above embodiments are prior art.

[0194] It should be noted that although the present invention has been described through the above embodiments, the present invention may also have various other embodiments. Without departing from the spirit and scope of the present invention, those skilled in the art can obviously make various corresponding changes and deformations to the present invention, but these changes and deformations should all fall within the scope protected by the appended claims of the present invention and their equivalents.

Claims

1. A hypersonic vehicle adaptive preset performance fault-tolerant control method, characterized in that: The following steps are involved: S1. Establish a dynamic model of a hypersonic aircraft with an unknown elevator failure and convert it into a state space equation describing the altitude subsystem and speed subsystem of the hypersonic aircraft; S2. Construct a fixed-time preset performance function η(t) of the speed subsystem based on the state-space equation, use a radial basis function neural network to approximate the fixed-time preset performance function η(t), and design the parameter update rate and actual control input Ψ of the speed subsystem c ; S3, introduce the speed tracking error e of the constrained speed subsystem v (t), and construct an error conversion function based on the fixed time preset performance function η(t) And the conversion equation Get the unconstrained equivalent error S4, based on equivalent error The coordinate transformation equations are constructed by using the adaptive command backstepping control method, and a finite time command filter, an error compensation system and the first virtual control law α1 are constructed for the altitude subsystem; Design the parameter update law of the altitude subsystem based on radial basis function neural network, and design the second virtual control law α2 for the altitude subsystem; Design the intermediate control law α3 of the altitude subsystem and the actual control input ξ based on the new virtual control law and error compensation system q ; S5. Analyze the actual control input ψ c and the actual control input ξ q The stability of the closed loop of the altitude subsystem and the speed subsystem of the hypersonic aircraft is determined, and the controller gains of the first virtual control law α1, the second virtual control law α2, the parameter update law and the intermediate control law α3 are determined; S6. Perform finite-time preset performance fault-tolerant control on the hypersonic vehicle based on the determined controller gain.

2. A hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 1, characterized in that: Step S5 includes the following sub-steps: S501: Construct the first Lyapunov function V1 for the coordinate transformation equation of the height subsystem, and design the first virtual control law α1 and parameter update law Based on the first Lyapunov function V1, a second Lyapunov function V2 is constructed to design a second virtual control law α2 of the altitude subsystem of the hypersonic vehicle; Based on the second Lyapunov function V2, a third Lyapunov function V3 is constructed, assuming that the actual control input ξ of the altitude subsystem of the hypersonic vehicle q , parameter update law Parameter update law and parameter update law S502: Construct the fourth Lyapunov function V4 for the speed subsystem of the hypersonic aircraft and design the actual control input Ψ of the speed subsystem of the hypersonic aircraft c and parameter update law S503, constructing a fifth Lyapunov function V5 according to the third Lyapunov function V3 and the fourth Lyapunov function V4, analyzing the stability of the closed-loop speed subsystem and the closed-loop altitude subsystem of the hypersonic aircraft based on the Lyapunov stability theory, and determining the controller gain to be designed; S504. Construct the sixth Lyapunov function V6 for the error compensation system, so that all signals of the closed-loop system are actually finite-time bounded.

3. The hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 1, characterized in that: In step S1, the unknown elevator fault model suffered by the hypersonic aircraft is: Where: q = 1, 2, elevator deflection angle u q is the control input signal of the hypersonic vehicle, k q，h ∈(0, 1] is the execution efficiency coefficient of the actuator, ξ q is the actual control input, is an unknown time-varying deviation fault, and They respectively represent the start time and end time of the elevator failure.

4. A hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 2, characterized in that: In step S4, the coordinate transformation equation is: Where: e i is the error before compensation, ω i is the error compensation signal, i = 1, 2, 3, e1 = x1-γ d , e2=x2-x 2c , e3=x3-x 3c ; γ d is the track angle reference trajectory; x1, x2 and x3 are system states; χ1, χ2, χ3 and χ4 are the first compensation error, the second compensation error, the third compensation error and the fourth error variable respectively; is the unconstrained equivalent error; δ min and δ max is a positive design parameter; The finite time command filter is designed as: Among them, α1 and α2 are the first virtual control law and the second virtual control law respectively, x 2c and x 3c are the output signals of the finite-time command filter, ρ, β1 and β2 are positive design parameters, and sign(·) is the sign function; The error compensation system is designed as: Among them: K1, K2, K3, ι1, l2 and l3 are positive design parameters; g1 and g2 are system parameters.

5. A hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 4, characterized in that: The first virtual control law α1 is designed as: Among them: c1 and a1 are positive design parameters, is the estimated value of θ1, is the radial basis function The transpose of is the track angle reference trajectory γ d The derivative of Parameter update law Designed for: Where: μ f1 and is a positive design parameter.

6. A hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 5, characterized in that: The second virtual control law α2 is designed as: Where: c2 is the positive design parameter, is the output signal x of the finite time command filter 2c The derivative of .

7. The hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 1, characterized in that: The actual control input ξ of the altitude subsystem of the hypersonic vehicle q for: in: and are N, θ3 and The estimated value of; τ, c3, a3 and are positive design parameters, is the output signal x of the finite time command filter 3c The derivative of is the radial basis function The transpose of Parameter update law Parameter update law and parameter update law Designed for: Where: μ N , μ f3 , and is a positive design parameter.

8. The hypersonic vehicle adaptive preset performance fault-tolerant control method according to claim 1, characterized in that: Actual control input Ψ of the hypersonic vehicle speed subsystem c for: Among them: g4 is a system variable, e v (t) is the speed tracking error, η(t) is the fixed time preset performance function, a4 and c4 are positive design parameters, is the estimated value of θ4, is the radial basis function The transpose of Parameter update law Designed for: Where: μ f4 and is a positive design parameter.

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