CN111273681A - Hypersonic aircraft high-safety anti-interference control method considering limited attack angle - Google Patents

Hypersonic aircraft high-safety anti-interference control method considering limited attack angle Download PDF

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CN111273681A
CN111273681A CN202010272309.1A CN202010272309A CN111273681A CN 111273681 A CN111273681 A CN 111273681A CN 202010272309 A CN202010272309 A CN 202010272309A CN 111273681 A CN111273681 A CN 111273681A
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邵星灵
张文豪
张文栋
刘俊
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Abstract

The invention discloses a high-safety anti-interference control method of a hypersonic aircraft considering the limitation of an attack angle, and relates to the field of control of hypersonic aircraft. Firstly, establishing an AHV longitudinal motion/dynamic model containing external interference, secondly, constructing a full-loop matching/non-matching interference observer by combining a minimum parameter learning neural network (MLPNN) and an extended state observer aiming at a height subsystem, and designing a minimum parameter learning neural network approximator aiming at a speed subsystem so as to reconstruct the flight state and multi-source interference of the AHV on line; and finally, introducing a barrier Lyapunov function, constructing an attack angle limited feedback controller, ensuring that the response of the attack angle is within a safety range, and realizing accurate tracking control on a given height/speed instruction under an output feedback framework through interference estimation and compensation. The invention solves the problems that the existing control method mostly depends on super-full-state measurement and the constraint of the attack angle cannot be guaranteed in a priori manner in a complex flight environment.

Description

Hypersonic aircraft high-safety anti-interference control method considering limited attack angle
Technical Field
The invention relates to the field of control of hypersonic aircrafts, in particular to a hypersonic aircraft high-safety anti-interference control method considering the limitation of an attack angle, and mainly solves the problem of hypersonic aircraft safety and stability control considering the intake characteristic of a scramjet engine under a complex flight environment.
Background
The hypersonic Aerocraft (AHV) has the advantages of rapid response capability, strong penetration capability, strong destruction capability, high maneuvering operation and accurate striking capability, has the advantages of rapidness, remote striking, height and the like, and can reach any place around the world within 1-2 hours to complete the containment and destruction of an enemy target. The flying range of the existing aircraft is exceeded in the flying height, the flying height reaches more than 30 kilometers, and the cruising flight can be carried out in the near space at the edge of the atmosphere.
The flight control system is a nerve center of the hypersonic aircraft and is a key for guaranteeing cruise flight and accurate terminal hitting tasks. However, the complex unknown flight environment, the unknown kinematic model of the mechanism and the strict control constraint provide unprecedented challenges for the current control theory and method. In addition, the scramjet engine is extremely sensitive to the control precision of the flight attack angle, and the engine can be flamed out due to slight large deviation, so that great hidden danger is brought to the safety and stability of the aircraft. Most of the currently reported AHV flight control methods are established under a full-state feedback control framework, and are assisted by robust self-adaption and sliding mode control to realize accurate tracking of height/speed, so that the control performance of the strategies is severely restricted if high-precision and high-cost key flight state sensors are highly dependent and unexpected faults occur in the flight process, and even control instability is caused. Furthermore, existing studies lack explicit consideration for angle of attack constraints and it is difficult to ensure that the through-flight angle of attack state is within the safety envelope. Therefore, the design problem of the AHV controller under the condition of considering attack angle constraint and incomplete measurement is developed, and the method has obvious engineering practical value.
Disclosure of Invention
The invention provides a hypersonic aircraft high-safety anti-interference control method considering the limitation of an attack angle, aiming at solving the problems that the existing control method mostly depends on hypersonic full-state measurement and the constraint of the attack angle cannot be guaranteed in a complex flight environment in advance.
The invention is realized by the following technical scheme: a hypersonic aircraft high-safety anti-interference control method considering the limited attack angle comprises the following steps:
(1) establishing an AHV longitudinal motion/dynamic model containing external interference:
Figure BDA0002443548590000021
wherein V is velocity, h is altitude, gamma is track inclination, α is attack angle, Q is pitch angle velocity, phi is accelerator opening, delta iseFor rudder deflection angle, fjAnd gj(j ═ V, γ, α, Q) represent lumped interference and AHV nominal dynamics, respectively, defined as follows:
Figure BDA0002443548590000022
Figure BDA0002443548590000023
Figure BDA0002443548590000024
Figure BDA0002443548590000025
wherein, m and IyyRespectively representing the mass and the moment of inertia of the aircraft, g representing the gravitational constant, Δ representing the disturbance of the aerodynamic coefficient, djeDenotes external disturbance, p is 0.5 ρaV2Representing dynamic pressure, pa＝ρa0exp(-(h-h0)/hs) Denotes the air density, pa0Is a height of h0Air density of hour, h0Representing the initial altitude, h, of the aircraftsDenotes the height of the reference surface, S denotes the area of the reference surface, zTC represents the thrust moment arm length and the average aerodynamic chord length, and T, D, L, M represents the thrust force,Drag, lift, and pitching moment, which are the states and input functions of the system, are defined as:
Figure BDA0002443548590000026
wherein, CT,Φ,CT,CD,CL,CM,
Figure BDA0002443548590000027
Represents a pneumatic parameter;
(2) constructing a full-loop matching/non-matching disturbance observer by combining a minimum parameter learning neural network MLPNN and an extended state observer aiming at a height subsystem, and designing a minimum parameter learning neural network approximator aiming at a speed subsystem:
Figure BDA0002443548590000031
Figure BDA0002443548590000032
wherein the content of the first and second substances,
Figure BDA0002443548590000033
representing altitude estimation error, altitude estimation value, track inclination angle estimation value, attack angle estimation value and pitch angle speed estimation value
Figure BDA0002443548590000034
Denotes ω0Which represents the bandwidth of the observer,
Figure BDA0002443548590000035
representing the estimated value of the lumped interference of each channel, n representing the number of hidden layer nodes of the MLPNN, Oji(ej) Representing the Gaussian basis function of each channel, cjiTo accept domain centers, bjRepresenting a basis function width; e.g. of the typejFor tracking errors of each channel, Γj,kwjAdaptively updating the design parameters of the law for the neural weight;
(3) introducing a barrier Lyapunov function, constructing an attack angle limited feedback controller to ensure that the response of the attack angle is within a safety range, and realizing accurate tracking control on a given height/speed command under an output feedback framework through interference estimation and compensation:
first, the speed subsystem controller is designed:
Figure BDA0002443548590000036
wherein k isVRepresenting the controller gain, eV(t)＝V-VdFor velocity channel tracking error, VdWhich is representative of the speed reference signal,
Figure BDA0002443548590000037
representing a velocity channel lumped interference estimate;
secondly, designing a virtual control law of a height and track inclination angle channel:
Figure BDA0002443548590000038
wherein the content of the first and second substances,
Figure BDA0002443548590000039
and
Figure BDA00024435485900000310
representing the virtual control law, kh、kγFor controller gain, eh(t)＝h-hd、
Figure BDA00024435485900000311
Respectively representing the tracking errors of the altitude channel and the track inclination angle channel, hdRepresenting a height reference signal, in order to constrain the angle of attack within a preset envelope function, the following barrier Lyapunov function is designed:
Figure BDA0002443548590000041
wherein k (t) kae-rt+kbIs an envelope function, and ka＞kb＞0，ka+kbRepresenting the initial value, k, of the envelope functionbRepresents the envelope function stable value, r represents the convergence time constant,
Figure BDA0002443548590000042
representing an attack angle channel tracking error, and designing a virtual control law of an attack angle subsystem as follows based on an obstacle Lyapunov function:
Figure BDA0002443548590000043
finally, designing a controller for a pitch angle rate channel:
Figure BDA0002443548590000044
wherein k isα,kQWhich is indicative of the gain of the controller,
Figure BDA0002443548590000045
representing the pitch rate channel tracking error,
Figure BDA0002443548590000046
representing the pitch rate channel lumped disturbance estimate.
Specifically, aiming at the problem that the existing performance-preserving control excessively depends on hypersonic flight state measurement and cannot theoretically ensure that the flight state of a hypersonic flight vehicle is considerable, an extended state observer and an MLP neural network approximator are combined in the design process to construct a full-loop matching/non-matching state observer so as to reconstruct the AHV flight state and multi-source interference on line; for the difficult problem that the constraint of the attack angle cannot be guaranteed in a priori under the complex flight environment, a barrier Lyapunov function is introduced, and an attack angle limited feedback controller is constructed to guarantee that the response of the attack angle is within a safety range.
Compared with the prior art, the invention has the following beneficial effects: the hypersonic aircraft high-safety anti-interference control method considering the limited attack angle has the advantages that: compared with the existing full-state feedback AHV control strategy, the method eliminates the excessive dependence on a high-cost and high-precision flight state sensor on the premise of not deteriorating the control performance; compared with the existing AHV neural control, the method can obtain the safety constraint characteristics of low online calculation complexity and strong attack angle; the method can realize high-safety control on the hypersonic aircraft under the premise of considering the limited attack angle, and can realize accurate tracking control on a given altitude/speed instruction and effective constraint of the attack angle.
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FIG. 1 is a flow chart of a hypersonic aircraft high-safety anti-interference control method considering the limited attack angle.
Detailed Description
The present invention is further illustrated by the following specific examples.
A hypersonic aircraft high-safety anti-interference control method considering the limited attack angle comprises the following steps:
(1) establishing an AHV longitudinal motion/dynamic model containing external interference:
Figure BDA0002443548590000051
wherein V is velocity, h is altitude, gamma is track inclination, α is attack angle, Q is pitch angle velocity, phi is accelerator opening, delta iseFor rudder deflection angle, fjAnd gj(j ═ V, γ, α, Q) represent lumped interference and AHV nominal dynamics, respectively, defined as follows:
Figure BDA0002443548590000052
Figure BDA0002443548590000053
Figure BDA0002443548590000054
Figure BDA0002443548590000055
wherein m is 300 and Iyy86722.54 for aircraft mass and moment of inertia, g 1.41 × 1016Representing the gravitational constant, Δ representing the disturbance of the aerodynamic coefficient, dveD is used for representing the external interference of the speed subsystem and the external interference of the track inclination subsystem as 1γe＝0.005sin(0.021πt)exp(-0.03t)-0.001sin(0.02πt)f2Indicating, external disturbance of angle of attack subsystem, by dαe＝0.01+0.05sin(0.21πt)exp(-0.03t)+0.01f2+0.01f3Representation, pitch angular velocity subsystem external disturbance by dQe＝0.01+2sin(0.02πt)f1-f3Denotes that p is 0.5 ρaV2The dynamic pressure is represented by the pressure of the fluid,
Figure BDA0002443548590000061
t represents time, ρa＝ρa0exp(-(h-h0)/hs) 0.000067429exp (- (h-85000)/2135.8) represents the air density, ρa00.000067429 is height h0Air density of hour, h085000 denotes the initial altitude of the aircraft, hs2135.8 denotes the height of the reference surface, S17 denotes the area of the reference surface, zT8.36, c-17, respectively, the thrust moment arm length and the mean aerodynamic chord length, T, D, L, M, respectively, the thrust, drag, lift, and pitch moments, which are the states and input functions of the system, defined as:
Figure BDA0002443548590000062
(2) constructing a full-loop matching/non-matching disturbance observer by combining a minimum parameter learning neural network MLPNN and an extended state observer aiming at a height subsystem, and designing a minimum parameter learning neural network approximator aiming at a speed subsystem:
Figure BDA0002443548590000063
Figure BDA0002443548590000064
wherein the content of the first and second substances,
Figure BDA0002443548590000065
representing altitude estimation error, altitude estimation value, track inclination angle estimation value, attack angle estimation value and pitch angle speed estimation value
Figure BDA0002443548590000066
Denotes ω0The bandwidth of the observer is denoted 500,
Figure BDA0002443548590000067
an estimated value representing the lumped interference of each channel, n-9 represents the number of hidden layer nodes of the MLPNN, Oji(ej) Representing the Gaussian basis function of each channel, cji5 is the center of the acceptance domain, bj2 denotes the basis function width; e.g. of the typejFor tracking errors of each channel, ΓV＝40,Γγ＝9610,Γα＝14610,ΓQ1057610 is the adaptive gain of MLPNN, and the design parameter of the neural weight adaptive updating law is kwV＝1,kwγ＝0.1,kwα＝0.01,kwQ＝1×10-3；
(3) Introducing a barrier Lyapunov function, constructing an attack angle limited feedback controller to ensure that the response of the attack angle is within a safety range, and realizing accurate tracking control on a given height/speed command under an output feedback framework through interference estimation and compensation:
first, the speed subsystem controller is designed:
Figure BDA0002443548590000071
wherein k isV42.55 denotes the controller gain, eV(t)＝V-VdFor velocity channel tracking error, VdWhich is representative of the speed reference signal,
Figure BDA0002443548590000072
representing a velocity channel lumped interference estimate;
secondly, designing a virtual control law of a height and track inclination angle channel:
Figure BDA0002443548590000073
wherein the content of the first and second substances,
Figure BDA0002443548590000074
and
Figure BDA0002443548590000075
representing the virtual control law, kh＝2.1、kγ2.3 is the controller gain, eh(t)＝h-hd、
Figure BDA0002443548590000076
Respectively representing the tracking errors of the altitude channel and the track inclination angle channel, hdRepresenting a height reference signal, in order to constrain the angle of attack within a preset envelope function, the following barrier Lyapunov function is designed:
Figure BDA0002443548590000077
wherein k (t) kae-rt+kb＝3e-t+0.1 is the envelope function, and ka＞kb＞0，ka+kbRepresenting the initial value, k, of the envelope functionbRepresents the envelope function stable value, r-1 represents the convergence time constant,
Figure BDA0002443548590000078
representing an attack angle channel tracking error, and designing a virtual control law of an attack angle subsystem as follows based on an obstacle Lyapunov function:
Figure BDA0002443548590000079
finally, designing a controller for a pitch angle rate channel:
Figure BDA00024435485900000710
wherein k isα＝2.5、kQThe controller gain is denoted by 15,
Figure BDA00024435485900000711
representing the pitch rate channel tracking error,
Figure BDA00024435485900000712
representing the pitch rate channel lumped disturbance estimate.
The scope of the invention is not limited to the above embodiments, and various modifications and changes may be made by those skilled in the art, and any modifications, improvements and equivalents within the spirit and principle of the invention should be included in the scope of the invention.

Claims (1)

1. A hypersonic aircraft high-safety anti-interference control method considering the limited attack angle is characterized by comprising the following steps: the method comprises the following steps:
(1) establishing an AHV longitudinal motion/dynamic model containing external interference:
Figure FDA0002443548580000011
wherein V is velocity, h is altitude, gamma is track inclination, α is attack angle, Q is pitch angle velocity, phi is accelerator opening, delta iseFor rudder deflection angle, fjAnd gj(j ═ V, γ, α, Q) represent lumped interference and AHV nominal dynamics, respectively, defined as follows:
Figure FDA0002443548580000012
Figure FDA0002443548580000013
Figure FDA0002443548580000014
Figure FDA0002443548580000015
wherein, m and IyyRespectively representing the mass and the moment of inertia of the aircraft, g representing the gravitational constant, Δ representing the disturbance of the aerodynamic coefficient, djeDenotes external disturbance, p is 0.5 ρaV2Representing dynamic pressure, pa＝ρa0exp(-(h-h0)/hs) Denotes the air density, pa0Is a height of h0Air density of hour, h0Representing the initial altitude, h, of the aircraftsDenotes the height of the reference surface, S denotes the area of the reference surface, zTC represents the thrust moment arm length and the mean aerodynamic chord length, respectively, and T, D, L, M represents the thrust, drag, lift, and pitch moments, respectively, which are the state and input functions of the system, defined as:
Figure FDA0002443548580000021
wherein, CT,Φ,CT,CD,CL,CM,
Figure FDA0002443548580000022
Represents a pneumatic parameter;
(2) constructing a full-loop matching/non-matching disturbance observer by combining a minimum parameter learning neural network MLPNN and an extended state observer aiming at a height subsystem, and designing a minimum parameter learning neural network approximator aiming at a speed subsystem:
Figure FDA0002443548580000023
Figure FDA0002443548580000024
wherein the content of the first and second substances,
Figure FDA0002443548580000025
representing altitude estimation error, altitude estimation value, track inclination angle estimation value, attack angle estimation value and pitch angle speed estimation value
Figure FDA0002443548580000026
Denotes ω0Which represents the bandwidth of the observer,
Figure FDA0002443548580000027
representing the estimated value of the lumped interference of each channel, n representing the number of hidden layer nodes of the MLPNN, Oji(ej) Representing the Gaussian basis function of each channel, cjiTo accept domain centers, bjRepresenting a basis function width; e.g. of the typejFor tracking errors of each channel, Γj,kwjAdaptively updating the design parameters of the law for the neural weight;
(3) introducing a barrier Lyapunov function, constructing an attack angle limited feedback controller to ensure that the response of the attack angle is within a safety range, and realizing accurate tracking control on a given height/speed command under an output feedback framework through interference estimation and compensation:
first, the speed subsystem controller is designed:
Figure FDA0002443548580000028
wherein k isVRepresenting the controller gain, eV(t)＝V-VdFor velocity channel tracking error, VdWhich is representative of the speed reference signal,
Figure FDA0002443548580000029
representing a velocity channel lumped interference estimate;
secondly, designing a virtual control law of a height and track inclination angle channel:
Figure FDA0002443548580000031
wherein the content of the first and second substances,
Figure FDA0002443548580000032
and
Figure FDA0002443548580000033
representing the virtual control law, kh、kγFor controller gain, eh(t)＝h-hd、
Figure FDA0002443548580000034
Respectively representing the tracking errors of the altitude channel and the track inclination angle channel, hdRepresenting a height reference signal, in order to constrain the angle of attack within a preset envelope function, the following barrier Lyapunov function is designed:
Figure FDA0002443548580000035
wherein k (t) kae-rt+kbIs an envelope function, and ka＞kb＞0，ka+kbRepresenting the initial value, k, of the envelope functionbRepresents the envelope function stable value, r represents the convergence time constant,
Figure FDA0002443548580000036
representing an attack angle channel tracking error, and designing a virtual control law of an attack angle subsystem as follows based on an obstacle Lyapunov function:
Figure FDA0002443548580000037
finally, designing a controller for a pitch angle rate channel:
Figure FDA0002443548580000038
wherein k isα,kQWhich is indicative of the gain of the controller,
Figure FDA0002443548580000039
representing the pitch rate channel tracking error,
Figure FDA00024435485800000310
representing the pitch rate channel lumped disturbance estimate.
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CN112415895B (en) * 2020-11-20 2022-09-23 南京邮电大学 Multi-HFVs (high frequency video sequences) distributed attack angle consistent safety controller
CN113093769A (en) * 2021-03-29 2021-07-09 西北工业大学 Active disturbance rejection control method for perching and falling of fixed-wing unmanned aerial vehicle
CN114859712A (en) * 2022-04-17 2022-08-05 西北工业大学 Aircraft guidance control integrated method facing throttle constraint
CN114859712B (en) * 2022-04-17 2023-08-01 西北工业大学 Aircraft guidance control integrated method oriented to throttle constraint
CN116513467A (en) * 2023-04-27 2023-08-01 华中科技大学 High-speed aircraft optimal control method considering air inlet safety
CN116513467B (en) * 2023-04-27 2023-12-26 华中科技大学 High-speed aircraft optimal control method considering air inlet safety
CN117826617A (en) * 2024-03-04 2024-04-05 西北工业大学 Intelligent network model-based sliding mode control method and device for preset performance of aircraft
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