CN116794976A - Ship-borne aircraft automatic landing control method considering input saturation and output constraint - Google Patents
Ship-borne aircraft automatic landing control method considering input saturation and output constraint Download PDFInfo
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Abstract
The invention provides a carrier-based aircraft automatic landing control method considering input saturation and output constraint, which comprises the following steps: constructing a carrier tail flow model of the aircraft carrier and a carrier motion model of the aircraft carrier; establishing a nonlinear longitudinal motion model of the carrier-based aircraft under an inertial coordinate system; based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, carrying out the design of a height control subsystem, and deducing the elevator control law of the carrier-based aircraft under the saturation condition; the input saturation limitation of the ship-based throttle opening is considered to carry out power compensation subsystem design, and the throttle opening control law under the fixed expected attack angle is deduced; the method comprises the steps of tracking and controlling the expected track of the carrier-based aircraft based on the aircraft elevator control law, and controlling the accelerator opening of the carrier-based aircraft based on the accelerator opening control law so as to control the carrier-based aircraft to automatically carrier. The invention considers uncertainty and input saturation and output constraint caused by pneumatic coefficient model error, and realizes high-precision tracking control of automatic carrier landing of carrier-borne aircraft.
Description
Technical Field
The invention belongs to the technical field of automatic carrier landing of carrier-borne aircraft, and particularly relates to an automatic carrier landing control method of carrier-borne aircraft considering input saturation and output constraint.
Background
The complex atmosphere on the sea surface, the up-and-down fluctuation of the seawater and the interference of the tail flow can bring about larger disturbance to the landing of the carrier-borne aircraft. For safe landing, the carrier-based aircraft needs to overcome the influence of the ship wake flow and accurately track the deck height change caused by wave motion. Furthermore, due to the physical limitations of the aircraft itself, it must be ensured that the carrier-based aircraft can land accurately under the constraints of input saturation and output constraints. Therefore, the carrier-based aircraft automatic landing system not only has stronger robustness and self-adaption capability for wake disturbance, but also needs to have the capability of compensating the constraint effect of the aircraft.
The existing carrier-based aircraft automatic carrier landing control method can be divided into linear control methods, such as: self anti-interference control technology, predictive control technology and H 2 and H∞ Methods, and the like; nonlinear control methods such as: feedback linearization method, nonlinear dynamic inversion method, back-stepping control method, sliding mode control method, etc. Most of the existing control methods do not consider the influence of model uncertainty, input saturation and output constraint on carrier aircraft landing, and consider less influence of the model uncertainty, the input saturation and the output constraint. The invention patent with publication number of CN106502255A discloses a design method and a control method of an automatic carrier landing control system of a carrier-based aircraft, wherein external disturbance is considered in modeling, interference of the carrier-based airflow is considered in a carrier-based airflow inhibition stage, but the interference estimation is incomplete, the influence of input saturation and output constraint is not considered, and the control precision is required to be improved.
Therefore, a new method for controlling the carrier-based aircraft to automatically carrier landing is needed, and meanwhile, the influence of the model uncertainty, input saturation and output constraint on the carrier-based aircraft landing is considered, so that the accuracy of the automatic carrier landing control is further improved.
Disclosure of Invention
In view of the above, the invention provides a carrier-based aircraft automatic landing control method considering input saturation and output constraint, which is used for solving the problem that the carrier-based aircraft automatic landing control does not comprehensively consider the influence of model uncertainty, input saturation and output constraint on carrier landing of the carrier-based aircraft.
The invention discloses a carrier-based aircraft automatic carrier landing control method considering input saturation and output constraint, which comprises the following steps:
constructing a carrier tail flow model of the aircraft carrier and a carrier motion model of the aircraft carrier;
calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model;
establishing a nonlinear longitudinal motion model of the carrier-based aircraft under an inertial coordinate system;
based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, carrying out the design of a height control subsystem by considering the uncertainty caused by the pneumatic coefficient model error and the input saturation and output constraint limit of the carrier-based aircraft elevator, and deducing the control law of the carrier-based aircraft elevator under the output constraint condition;
estimating uncertainty and external interference caused by a carrier aircraft pneumatic coefficient modeling error, and carrying out power compensation subsystem design by considering input saturation limitation of the carrier aircraft throttle opening, and deducing an throttle opening control law under a fixed expected attack angle;
and carrying out tracking control on the expected track of the carrier-based aircraft based on the aircraft elevator control law, and carrying out carrier-based power compensation control based on the accelerator opening control law so as to control the carrier-based aircraft to automatically carrier.
On the basis of the above technical solution, preferably, calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model specifically includes:
acquiring the height change h of a ship deck according to an aircraft carrier motion model 1s And vessel pitch variation θ 1s ；
Height change h of a ship deck 1s And vessel pitch variation θ 1s Determining the ideal landing point height h 1 ：
h 1 ＝h 1s +l d ·θ 1s
According to the ideal landing point height h 1 Calculating the expected track height h of the carrier-based aircraft:
h＝h 0 +V 0 tsinγ s +h 1
wherein ,h0 Is the initial altitude of the aircraft, V 0 Is the initial speed of the carrier-borne aircraft, tFor time, gamma s Desired track pitch angle for aircraft, l d Is deck length.
On the basis of the above technical solution, preferably, the building the nonlinear longitudinal motion model of the carrier-based aircraft specifically includes:
considering wind disturbance influence, the airspeed V and the airspeed attack angle alpha of the carrier-borne aircraft meet the following relation:
α＝α k +α w
wherein ,Vk Is the speed of the plane relative to the ground, gamma and theta respectively represent the inclination angle and pitch angle of the carrier-based plane track, alpha k For the angle of attack of the ground speed alpha w Represents the wind speed attack angle and satisfiesw＝(u w ,v w ,w w ) Is the wind speed.
Defining the ideal landing point height conversionTrack pitch angle control amount x 2 Control amount of pitch angle rate x =γ 3 Control amount x of earth velocity attack angle =q 4 ＝α k The nonlinear longitudinal motion model of the carrier-based aircraft is:
wherein ,g 2 ＝1，
in the above-mentioned formula(s), and />D, is the system uncertainty 1 、d 3 、d 4 and d4 Are all external interference, delta e Is aircraft elevator control law and accelerator opening control law delta T Q is pitch rate, ρ is air density, V is airspeed, + is>Is pneumatic chord length, S is wing area, < ->Are all pneumatic coefficients related to the angle of attack alpha, < >>Delta as a first order derivative of the reference angle of attack f For flap deflection angle I yy For moment of inertia of the aircraft about the y-axis, delta t Is the model error delta of the accelerator opening M As part of the model error, m is the aircraft mass, L 0 For aircraft lift, T max Is the maximum thrust of the aircraft.
On the basis of the above technical solution, preferably, the method for deriving the control law of the ship-based aircraft elevator specifically includes:
first control equation in nonlinear longitudinal motion model for carrier aircraftLet x be 1c Is x 1 Defining the error z 1 ＝x 1 -x 1c Then z 1 The differentiation of (2) is as follows:
virtual control variables for designing track pitch angles
wherein k1 、ζ 1 As a matter of design parameters,is to interference d 1 Estimate of-> and μ1 Output constraints are considered:
wherein ,k0 As a matter of design parameters,k c1 (t) is x 1 Time-varying upper and lower bounds of (t), p (z) 1 ) As an auxiliary function of the auxiliary,is a time-varying barrier function;
order theObtaining ∈k by a first order filter>Then-> wherein τ2 Is a parameter of a first order filter;
second control equation in nonlinear longitudinal motion model for carrier aircraftDefinition error->Then z 2 The differentiation of (2) is as follows:
virtual control variables for designing pitch rate
wherein k2 Is a designed parameter;
order theObtaining ∈k by a first order filter>Then->
Nonlinear for carrier-based aircraftThird control equation in longitudinal motion modelConsider the input saturation problem sat (delta) e ) Define error->Then z 3 The differentiation of (2) is as follows:
wherein g3N G is g 3 Known term in Deltag 3 ＝g 3 -g 3N ；
Approximation estimation using a first RBF neural networkThe method comprises the following steps:
wherein Θ3 * Is the optimal weight value phi of the first RBF neural network 3 Epsilon as a gaussian radial basis function of the first RBF neural network 3 As an error term,obtaining z 3 ：
Design assistance systemCounteracting the effect of input saturation on control behavior:
defining correction error v 3 ：
Then get
wherein D3 To take into account the input saturation sat (delta) e ) And external disturbance d 3 Is a disturbance of (1):
ship-borne aircraft elevator control law delta under saturation condition e The method comprises the following steps:
wherein ,for the estimation of the first RBF neural network weight, and (2)>To interference D 3 Is a function of the estimate of (2).
On the basis of the technical proposal, the interference d is preferably 1 Estimation of (a)The update rate of (2) is:
wherein and />Is a control parameter; />Is prediction error, ++> Is a control parameter;
estimation of first RBF neural network weightTo interference D 3 Estimate of->The update rates of (a) are respectively:
wherein , and />For controlling parameters +.>For prediction error-> Is a control parameter.
On the basis of the above technical solution, preferably, the estimating the uncertainty and the external interference caused by the modeling error of the aerodynamic coefficient of the carrier-based aircraft, and taking the input saturation limit of the carrier-based throttle opening into consideration to perform power compensation subsystem design, the deriving the throttle opening control law under the fixed expected attack angle specifically includes:
fourth control equation in nonlinear longitudinal motion model for carrier aircraftConsidering the input saturation limit problem sat (delta) suffered by the ship-borne throttle opening T ) Using the unknown function representing the uncertainty of the system in the second RBF neural network estimation equation +.>The method comprises the following steps:
wherein ε4 As an error term,
definition errorThen z 4 The differentiation of (2) is as follows:
wherein D4 In order to be an external disturbance,g 4N g is g 4 Known term in Deltag 4 ＝g 4 -g 4N ；
Building a class of auxiliary system assistance systemsTo counteract the effect of input saturation on control behavior:
defining a corrected tracking error v 4 ＝z 4 -ξ 4 Obtaining
Then, the throttle opening control law delta T Can be designed as follows:
in the formula ,k4 、ζ 4 In order to design the parameters of the device,for the estimation of the weights of the second RBF neural network, and (2)>To interference D 4 Is a function of the estimate of (2).
Based on the above technical solution, preferably, the second RBF neural network weight is estimatedTo interference D 3 Estimate of->The update rates of (a) are respectively:
wherein , and />Is a control parameter; />For prediction error-> Is a control parameter.
In a second aspect of the invention, a carrier-based aircraft automatic landing control system taking input saturation and output constraints into account is disclosed, the system comprising:
and the aircraft carrier model building module: the method is used for constructing a carrier tail flow model of the aircraft carrier and a carrier motion model of the aircraft carrier;
the carrier-based aircraft model building module: the method is used for calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model; establishing a nonlinear longitudinal motion model of the carrier-based aircraft under an inertial coordinate system;
and the height control module is used for: the system is used for carrying out the design of a height control subsystem based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, taking the uncertainty caused by the pneumatic coefficient model error and the input saturation and output constraint limit of the carrier-based aircraft elevator into consideration, and deducing the control law of the carrier-based aircraft elevator under the condition of taking the input saturation and output constraint into consideration;
and the power compensation module is used for: the method is used for estimating uncertainty and external interference caused by the modeling error of the pneumatic coefficient of the carrier-based aircraft, carrying out power compensation subsystem design by considering input saturation limitation of the carrier-based throttle opening, and deducing the throttle opening control law under a fixed expected attack angle;
landing control module: the method is used for tracking and controlling the expected track of the carrier-based aircraft based on the aircraft elevator control law, and carrying out carrier-based power compensation control based on the accelerator opening control law so as to control the carrier-based aircraft to automatically carrier.
In a third aspect of the present invention, an electronic device is disclosed, comprising: at least one processor, at least one memory, a communication interface, and a bus;
the processor, the memory and the communication interface complete communication with each other through the bus;
the memory stores program instructions executable by the processor which the processor invokes to implement the method according to the first aspect of the invention.
In a fourth aspect of the invention, a computer-readable storage medium is disclosed, storing computer instructions that cause a computer to implement the method according to the first aspect of the invention.
Compared with the prior art, the invention has the following beneficial effects:
1) The invention simultaneously considers uncertainty and input saturation and output constraint caused by pneumatic coefficient model errors in the automatic carrier landing control of the carrier-based aircraft, designs the elevator control law of the carrier-based aircraft to carry out height control under the condition of considering the input saturation and the output constraint, designs the accelerator opening control law to carry out power compensation control, and finally realizes the tracking control of the automatic carrier landing of the carrier-based aircraft and improves the control precision;
2) The invention gradually deduces a virtual control law of the aircraft corresponding to the track inclination angle and the pitch angle speed through a backstepping control frame, uses an RBF neural network to estimate uncertainty caused by a pneumatic coefficient model error in a system, considers output constraint suffered by an aircraft elevator, and designs a virtual control variable considering the output constraint through introducing a time-varying barrier function; in consideration of input saturation limitation of the aircraft elevator, an auxiliary system is designed to compensate so as to offset the influence of input saturation on control behavior, and finally, aircraft elevator control law under consideration of input saturation and output constraint is obtained, so that tracking control precision of the carrier-based aircraft on expected tracks is improved;
3) The invention constructs an accelerator opening control law based on a fixed expected attack angle, wherein an RBF neural network and a self-adaptive interference estimation model are used for respectively estimating uncertainty and external interference caused by a carrier aircraft pneumatic coefficient modeling error, and a corresponding auxiliary system is constructed to compensate the accelerator opening of the aircraft in consideration of the fact that the accelerator opening of the aircraft is also limited by input saturation so as to offset the influence of the input saturation on control behaviors, thereby improving the accuracy of carrier aircraft automatic carrier landing control;
4) Compared with the prior art that only track errors are used for adjusting the weights of the neural networks, the method and the device respectively use the prediction errors and the track errors to adaptively update the weights of the first RBF neural network and the second RBF neural network, and experiments prove that the control scheme taking the prediction errors into consideration has higher estimation accuracy on the composite uncertainty of the system, so that the adaptive neural network control scheme has better control performance.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of airspeed, ground speed, and wind speed;
FIG. 2 is a schematic illustration of tail flow halving;
FIG. 3 is a schematic view of the vertical component of the tail flow;
FIG. 4 is a schematic diagram of a tracking trajectory and an asymmetric time-varying output constraint;
FIG. 5 is a schematic diagram of tracking errors and constraint boundaries thereof;
FIG. 6 is a schematic illustration of actual aircraft altitude tracking performance;
FIG. 7 is a schematic view of the angle of attack response;
FIG. 8 is a graph of norms of weights of a neural network;
FIG. 9 is a composite uncertainty η q And its estimated error schematic diagram;
FIG. 10 is a graph of the composite uncertainty η α And its estimation error schematic diagram.
Detailed Description
The following description of the embodiments of the present invention will clearly and fully describe the technical aspects of the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
The invention provides a carrier-based aircraft automatic landing control method considering input saturation and output constraint, which comprises the following steps:
s1, constructing an aircraft carrier tail flow model and an aircraft carrier motion model.
S11, constructing an aircraft carrier tail flow model:
and establishing a model of the ship wake according to an engineering method and the American standard MIL-F-8795C. The ship wake model mainly comprises four parts: random free atmosphere turbulence u 1 ,v 1 ,w 1 Steady state aircraft carrier wake disturbance u 2 ,w 2 Periodic disturbance u induced by aircraft carrier pitching 3 ,w 3 And random ship wake disturbance u 4 ,v 4 ,w 4 。
The overall tail flow disturbance rate is as follows:
fig. 2 shows a horizontal component diagram of the tail flow, and fig. 3 shows a vertical component diagram of the tail flow.
S12, constructing an aircraft carrier offshore motion model:
when the carrier-based aircraft approaches to the carrier, the position of an ideal carrier landing point is continuously changed along with the movement of the aircraft carrier, so that an aircraft carrier offshore movement model needs to be constructed.
The invention approximates the offshore movement of the aircraft carrier by adopting a simple harmonic method, and the method is as follows:
wherein ,h1s Representing the change in the elevation of the deck of a ship in meters, θ 1s The change of the pitching angle of the ship is expressed in degrees.
S2, calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model.
The ship moves, and the ideal landing point also moves along, so that the ideal landing point needs to be tracked. According to the change h of the height of the deck of the ship 1s And change of pitching angle theta of ship 1s Determining the ideal landing point height h 1 ：
h 1 ＝h 1s +l d ·θ 1s
h 1 Is the ideal landing point height, l d Is deck length.
According to the ideal landing point height h 1 Calculating the expected track height h of the carrier-based aircraft:
h＝h 0 +V 0 tsinγ s +h 1
wherein ,h0 Is the initial altitude of the aircraft, V 0 Is the initial speed of the carrier-borne aircraft, t is time, and gamma is calculated s Desired track pitch angle for aircraft, l d Is deck length.
S3, establishing a nonlinear longitudinal motion model of the carrier-based aircraft under the inertial coordinate system.
Establishing a common inertial coordinate system: o (O) g x g y g z g Is an inertial coordinate system built on the earth, O b x b y b z b Is a machine body coordinate system built on the carrier-based aircraft, O k x k y k z k Representing a trackAnd (5) a coordinate system.
Considering wind disturbance influence, the airspeed V and the airspeed attack angle alpha of the carrier-borne aircraft meet the following relation:
α＝α k +α w
wherein ,Vk Is the speed of the plane relative to the ground, gamma and theta respectively represent the inclination angle and pitch angle of the carrier-based plane track, alpha k For the angle of attack of the ground speed alpha w Represents the wind speed attack angle and satisfiesw＝(u w ,v w ,w w ) For wind speed, the wind speed can be expressed in terms of the total tail flow disturbance speed, taking into account the wind disturbance effect.
As shown in FIG. 1, the relationship among airspeed, ground speed and wind speed is schematically represented at O g x g y g z g Under the coordinate system, airspeed V and x g The included angle of the axes is the track inclination angle gamma, and the speed V of the plane relative to the ground k And x g The included angle of the axes is gamma k Airspeed V and velocity V of aircraft relative to ground k The included angle is the wind speed attack angle alpha w 。
Defining the ideal landing point height conversionTrack pitch angle control amount x 2 Control amount of pitch angle rate x =γ 3 Control amount x of earth velocity attack angle =q 4 ＝α k The nonlinear longitudinal motion model of the carrier-based aircraft is:
wherein ,d 1 、d 3 、d 4 and di All are system uncertainties, delta e Is aircraft elevator control law and accelerator opening control law delta T Q is pitch rate, and each symbol has the meaning:
g 2 ＝1
f 4 ＝q
M 1 ＝δ M
in the above formula, ρ is the air density, V is the airspeed,is pneumatic chord length, S is wing area, < -> All being pneumatic coefficients, M, related to the angle of attack alpha 0 、/>M 1 Moment corresponding to different pneumatic coefficients respectively, < ->To the desired angle of attack alpha c First order differentiation of delta f For flap deflection angle I yy For moment of inertia of the aircraft about the y-axis, delta t Is the model error delta of the accelerator opening M As part of the model error, m is the aircraft mass, L 0 For aircraft lift, T max Is the maximum thrust of the aircraft.
S4, based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, the height control subsystem is designed by considering the uncertainty caused by the pneumatic coefficient model error and the input saturation and output constraint limit of the carrier-based aircraft elevator, and the control law of the carrier-based aircraft elevator under the saturation condition is deduced.
The step S4 specifically comprises the following sub-steps:
s41, aiming at a first control equation in a nonlinear longitudinal motion model of the carrier aircraftThe virtual control law of the track inclination angle is designed by considering external interference and output constraint.
Let x be 1c Is x 1 Defining the error z 1 ＝x 1 -x 1c Then z 1 The differentiation of (2) is as follows:
virtual control variables for designing track pitch angles
wherein k1 、ζ 1 For the parameters of the design, t represents time,is to interference d 1 Is estimated by the following adaptive interference estimation model:
wherein Is->Update rate-> and />Is a control parameter->Is the prediction error:
is a control parameter.
and μ1 To take into account the control amount of the output constraint: />
wherein ,k0 As a matter of design parameters, is x 1 Time-varying upper and lower bounds of (t), p (z) 1 ) As an auxiliary function of the auxiliary,is a time-varying barrier function.
Can be expressed as:
x 1c (t) x 1 Is x of the expected value of (2) 1c 。
Order theObtaining ∈k by a first order filter>Then-> wherein τ2 Is a parameter of the first order filter.
S42, aiming at a second control equation in the nonlinear longitudinal motion model of the carrier aircraftA virtual control law of pitch angle speed is designed.
Definition errorThen z 2 The differentiation of (2) is as follows:
virtual control variables for designing pitch rate
wherein k2 Is a designed parameter;
order theObtaining ∈k by a first order filter>Then->τ 3 Is a parameter of the corresponding first order filter.
S43, aiming at a third control equation in a nonlinear longitudinal motion model of the carrier aircraftConsider the input saturation problem sat (delta) e ) And external interference, and performing error estimation.
Definition errorThen z 3 The differentiation of (2) is as follows:
wherein g3N G is g 3 Known term in Deltag 3 ＝g 3 -g 3N ；
Approximation estimation using a first RBF neural networkThe method comprises the following steps:
wherein Θ3 * Is the optimal weight value phi of the first RBF neural network 3 Epsilon as a gaussian radial basis function of the first RBF neural network 3 As an error term,obtain->
Design assistance systemTo counteract the effect of input saturation on control behavior:
defining correction error v 3 ：
Then get
wherein D3 To take into account the input saturation sat (delta) e ) And external disturbance d 3 Is a disturbance of (1):
s44, deducing the ship under saturated conditionControl law delta of elevator of carrier e The method comprises the following steps:
wherein ,k3 、ζ 3 In order to design the parameters of the device,for the estimation of the first RBF neural network weight, and (2)>To interference D 3 Is estimated by adopting the following adaptive interference estimation model:
wherein ,respectively Θ 3 、D 3 Update rate of-> and />In order to control the parameters of the device,for the prediction error:
is a control parameter.
The invention is based on ideal landing point h 1 And generating an expected track of the carrier-based aircraft, gradually deducing a virtual control law of the aircraft corresponding to the track inclination angle and the pitch angle speed through a backstepping control frame, and designing a height control subsystem. The aerodynamic coefficient of the aircraft is obtained by modeling and fitting the aerodynamic coefficient of the aircraft through a large amount of experimental data, and an error exists between the aerodynamic coefficient and the actual aerodynamic coefficient. The invention uses a first RBF neural network to estimate uncertainty caused by pneumatic coefficient model errors in a height control subsystemAnd constructing a self-adaptive interference estimation model to the external interference d 1 、d 3 An estimation is made. An auxiliary system is also designed to compensate in view of the saturation limit of the aircraft elevator. The invention considers the influence of input saturation, output constraint and system uncertainty on the elevator control, finally obtains the control law of the aircraft elevator under the saturation condition, and realizes the high-precision tracking control of the carrier-based aircraft on the expected track.
Furthermore, the present invention uses prediction error simultaneouslyAnd trajectory error v 3 The method and the system for adaptively updating the weight of the first RBF neural network form an adaptive neural network control scheme, and compared with the mode of adjusting the weight of the neural network by only using the track error in the prior art, the control scheme taking the prediction error into consideration has higher estimation precision on the composite uncertainty of the system, so that the adaptive neural network control scheme has better control performance.
S5, estimating uncertainty and external interference caused by a carrier aircraft pneumatic coefficient modeling error, and designing a power compensation subsystem by considering input saturation limitation of the carrier aircraft throttle opening, so as to deduce an accelerator opening control law under a fixed expected attack angle.
Fourth control equation in nonlinear longitudinal motion model for carrier aircraftConsidering the input saturation limit problem sat (delta) suffered by the ship-borne throttle opening T ) Estimating +.f using a second RBF neural network>System uncertainty caused by middle carrier-based aircraft pneumatic coefficient modeling error>The method comprises the following steps:
wherein ε4 As an error term,
definition errorThen z 4 The differentiation of (2) is as follows:
wherein D4 Is external interference alpha c In order to achieve the desired angle of attack,to be a first order derivative of the desired angle of attack,g 4N g is g 4 Known term in Deltag 4 ＝g 4 -g 4N 。
To counteract the effect of input saturation on control behavior, a class of auxiliary system assistance systems is constructedError correction is carried out:
defining a corrected tracking error v 4 ＝z 4 -ξ 4 Obtaining
Then, the throttle opening control law delta T Can be designed as follows:
/>
in the formula ,k4 、ζ 4 In order to design the parameters of the device,for weighting the second RBF neural network 4 Estimate of->To interference D 4 Is estimated by the following adaptive interference estimation model:
wherein ,respectively Θ 4 、D 4 Update rate of-> and />For controlling parameters +.>For the prediction error:
is a control parameter.
The invention is based on a fixed desired angle of attack alpha c The throttle opening control law is constructed, and the power compensation subsystem is designed. Wherein, the uncertainty caused by the modeling error of the aerodynamic coefficient of the carrier-based aircraft is respectively calculated by using the RBF neural network and the adaptive interference estimation modelAnd external disturbance D 4 An estimation is made. In this subsystem, a corresponding auxiliary system is also constructed to compensate for this, considering that the aircraft throttle opening is also subject to input saturation limitations. Similar to the estimation of the first RBF neural network weight, in the estimation of the second RBF neural network weight, the prediction error +.>And trajectory error v 4 The method and the system have the advantages that the weight is updated in a self-adaptive mode, so that the self-adaptive neural network control scheme is formed, and compared with the mode that the weight of the neural network is adjusted by only using the track error in the prior art, the control scheme taking the prediction error into consideration has higher estimation precision on the composite uncertainty of the system.
S6, tracking control of the expected track of the carrier-based aircraft is performed based on the aircraft elevator control law, and accelerator opening control of the carrier-based aircraft is performed based on the accelerator opening control law so as to control the carrier-based aircraft to automatically land on the ship.
The invention considers uncertainty and input saturation and output constraint caused by pneumatic coefficient model error in the automatic carrier landing control of the carrier aircraft, designs the elevator control law of the carrier aircraft to control the height under the saturation condition, designs the accelerator opening control law to perform power compensation control, finally realizes the tracking control of the automatic carrier landing of the carrier aircraft, and improves the control precision.
The method of the present invention will be described with reference to specific examples:
taking F/A-18A as a controlled object, considering 5% model error in the simulation process, and specifically marking as follows: l (L) 1 ＝-5％L，D 1 ＝-5％D，M 1 ＝-5％M，δ t = -5%T. Setting an initial state of the aircraft as: v=69.3 m/s, h= 89.85m, α k =6°, θ=5.5°, γ= -0.5 °, q=0°/s. The angle of the glide slope of the carrier-based aircraft is set to be gamma s ＝-3.5°，γ s The actual expected track inclination angle of the carrier-based aircraft is set to be t=21.71 s. The initial position error of the aircraft and the reference glide slope is e h (0)＝-2m。
In the simulation process, the time-varying barrier function is selected as:
k a1 (t):＝0.1e -0.5t +0.015
k b1 (t):＝0.05e -0.2t +0.015
furthermore, the selection reference output signal is:
wherein V0 ＝69.3m/s。
The control gain parameters of the altitude subsystem and the power compensation subsystem are designed as follows: k (k) 1 ＝1、k 2 ＝2、k 3＝5 and k4 =1.5. Step 3 NN node number N 1 =45, where the number of NN nodes in the power compensation subsystem is selected to be N 2 =49. The parameters of the first order filter and update law are designed as follows: τ 1 ＝0.005，τ 2 ＝0.0125，ζ 1 ＝0.21，ζ 3 ＝ζ 4 ＝0.001，k 10 ＝0.01，
The system uncertainty of the whole carrier-based aircraft control system consists of two parts: unknown function and di . The system uncertainty in the altitude subsystem is η q ＝Δg 3 sat(δ e )+d 3 Uncertainty in the power compensation subsystem isThe invention uses->) To estimate eta q And is provided withAs eta α Is used for the estimation of the estimated value of (a).
The invention relates to a carrier-based aircraft automatic landing control method considering input saturation and output constraint, wherein in the control law deducing process, the weight theta of a first RBF neural network and a second RBF neural network is updated by respectively using a prediction error and a track error 3 、Θ 4 The method of the present invention is designated as "CANCS". Whereas the prior art generally uses only trajectory errors to adjust neural network weights, such as Robust adaptive neural control of flexible hypersonic flight vehicle with dead-zone input nonlinearity of b.xu et al, named "ANCS". Comparing the CANCS of the present invention with ANCS of the prior art, the simulation results are shown in FIG. 4 and FIG. 5, wherein FIG. 4 is tracking trace x 1 And an asymmetric time-varying output constraint diagram, FIG. 5 is a tracking error z 1 And a constraint boundary diagram thereof, and fig. 4 and 5 show tracking performance of both methods. It can find x 1 Remains within the asymmetric time-varying output constraint range throughout the simulation. In addition, comparing the results of the two schemes "CANCS" and "ANCS" can find that the "CANCS" taking into account the prediction error not only has small overshoot, but also has faster convergence speed.
As shown in FIG. 6, a comparative schematic diagram of actual altitude performance of an aircraft, h c And (t) is the ideal track height. The controller of the present invention can cause the system to converge rapidly to the vicinity of the ideal trajectory when the system state is slightly deviated at the initial time. FIG. 7 is a schematic view of the aircraft angle of attack response, α c And (t) is the reference angle of attack. The steady state error of "cancel" that can be found to take into account the prediction error is smaller than that found.
Figure 8 shows norms of neural network weights corresponding to both "ANCS" and "CANCS",the norms of the weight estimation values of the first RBF neural network and the second RBF neural network are compared, and the norms of the weights of the neural networks in the system are obviously reduced after the prediction errors are considered. In addition, to study the estimation ability of unknown functions and interferences in ACLS, a complex uncertainty η was calculated by simulation q and ηα . FIG. 9 shows the composite uncertainty η q And its estimation error diagram,/A->For two uncertainty reference values, +.>For the estimation of error, FIG. 10 is a composite uncertainty η α And its estimation error diagram,/A->For two uncertainty reference values, +.>For estimating the error, it can be seen from fig. 9 and 10 that the estimation error of the "ANCS" is much larger without considering the prediction error. From fig. 8, fig. 9 and fig. 10, it can be found that the control scheme taking the prediction error into consideration has higher estimation accuracy on the composite uncertainty of the system, and further illustrates that the adaptive neural network control scheme of the present invention has better control performance.
Corresponding to the embodiment of the method, the invention also provides a carrier-based aircraft automatic carrier landing control system considering input saturation and output constraint, which comprises:
and the aircraft carrier model building module: the method is used for constructing a carrier tail flow model of the aircraft carrier and a carrier motion model of the aircraft carrier;
the carrier-based aircraft model building module: the method is used for calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model; establishing a nonlinear longitudinal motion model of the carrier-based aircraft under an inertial coordinate system;
and the height control module is used for: the system is used for designing a height control subsystem based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, taking the uncertainty caused by the pneumatic coefficient model error and the input saturation and output constraint limit of the elevator of the carrier-based aircraft into consideration, and deducing the elevator control law of the carrier-based aircraft under the saturation condition;
and the power compensation module is used for: the method is used for estimating uncertainty and external interference caused by a carrier aircraft pneumatic coefficient modeling error, carrying out power compensation subsystem design by considering input saturation and output constraint limits of the carrier aircraft throttle opening, and deducing an accelerator opening control law under a fixed expected attack angle;
landing control module: the method is used for tracking and controlling the expected track of the carrier-based aircraft based on the aircraft elevator control law, and controlling the accelerator opening of the carrier-based aircraft based on the accelerator opening control law so as to control the carrier-based aircraft to automatically carrier.
The system embodiments and the method embodiments are in one-to-one correspondence, and the brief description of the system embodiments is just to refer to the method embodiments.
The invention also discloses an electronic device, comprising: at least one processor, at least one memory, a communication interface, and a bus; the processor, the memory and the communication interface complete communication with each other through the bus; the memory stores program instructions executable by the processor that the processor invokes to implement the aforementioned methods of the present invention.
The invention also discloses a computer readable storage medium storing computer instructions for causing a computer to implement all or part of the steps of the methods of the embodiments of the invention. The storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The system embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, i.e., may be distributed over a plurality of network elements. One of ordinary skill in the art may select some or all of the modules according to actual needs without performing any inventive effort to achieve the objectives of the present embodiment.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. The utility model provides a carrier-borne aircraft automatic landing control method considering input saturation and output constraint, which is characterized in that the method comprises the following steps:
constructing a carrier tail flow model of the aircraft carrier and a carrier motion model of the aircraft carrier;
calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model;
establishing a nonlinear longitudinal motion model of the carrier-based aircraft under an inertial coordinate system;
based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, the uncertainty caused by the pneumatic coefficient model error is considered, the input saturation and the output constraint limit of the carrier-based aircraft elevator are used for carrying out the design of a height control subsystem, and the control law of the carrier-based aircraft elevator under the input saturation and the output constraint is deduced and considered;
estimating uncertainty and external interference caused by a carrier aircraft pneumatic coefficient modeling error, and carrying out power compensation subsystem design by considering input saturation limitation of the carrier aircraft throttle opening, and deducing an throttle opening control law under a fixed expected attack angle;
the method comprises the steps of tracking and controlling the expected track of the carrier-based aircraft based on the aircraft elevator control law, and controlling the accelerator opening of the carrier-based aircraft based on the accelerator opening control law so as to control the carrier-based aircraft to automatically carrier.
2. The method for automatically landing a carrier-based aircraft taking input saturation and output constraint into consideration according to claim 1, wherein the calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model specifically comprises:
acquiring the height change h of a ship deck according to an aircraft carrier motion model 1s And vessel pitch variation θ 1s ；
Height change h of a ship deck 1s And vessel pitch variation θ 1s Determining the ideal landing point height h 1 ：
h 1 ＝h 1s +l d ·θ 1s
According to the ideal landing point height h 1 Calculating the expected track height h of the carrier-based aircraft:
h＝h 0 +V 0 tsinγ s +h 1
wherein ,h0 Is the initial altitude of the aircraft, V 0 Is the initial speed of the carrier-borne aircraft, t is time, and gamma is calculated s Desired track pitch angle for aircraft, l d Is deck length.
3. The method for controlling the carrier-based aircraft landing automatically taking input saturation and output constraint into consideration according to claim 2, wherein the building of the nonlinear longitudinal motion model of the carrier-based aircraft specifically comprises:
considering wind disturbance influence, the airspeed V and the airspeed attack angle alpha of the carrier-borne aircraft meet the following relation:
α＝α k +α w
wherein ,Vk Is the speed of the plane relative to the ground, gamma and theta respectively represent the inclination angle and pitch angle of the carrier-based plane track, alpha k For the angle of attack of the ground speed alpha w Represents the wind speed attack angle and satisfiesw＝(u w ,v w ,w w ) Is the wind speed;
defining the ideal landing point height conversionTrack pitch angle control amount x 2 Control amount of pitch angle rate x =γ 3 Control amount x of earth velocity attack angle =q 4 ＝α k The nonlinear longitudinal motion model of the carrier-based aircraft is:
wherein ,g 2 ＝1，
in the above-mentioned formula(s), and />D, is the system uncertainty 1 、d 3 、d 4 and d4 Are all external interference, delta e Is aircraft elevator control law and accelerator opening control law delta T Q is pitch rate, ρ is air density, V is airspeed, + is>Is pneumatic chord length, S is wing area, < ->All being pneumatic coefficients, M, related to the angle of attack alpha 0 、/>M 1 Moment corresponding to different pneumatic coefficients respectively, < ->To the desired angle of attack alpha c First order differentiation of delta f For flap deflection angle I yy For moment of inertia of the aircraft about the y-axis, delta t Is the model error delta of the accelerator opening M As part of the model error, m is the aircraft mass, L 0 For aircraft lift, T max Is the maximum thrust of the aircraft.
4. The method for controlling the landing of the carrier-based aircraft taking into account input saturation and output constraint according to claim 3, wherein the step of designing the altitude control subsystem taking into account uncertainty caused by a pneumatic coefficient model error and saturation limit imposed on the aircraft elevator, and the step of deriving the control law of the aircraft elevator under the saturation condition specifically comprises the following steps:
first control equation in nonlinear longitudinal motion model for carrier aircraftLet x be 1c Is x 1 Defining the error z 1 ＝x 1 -x 1c Then z 1 The differentiation of (2) is as follows:
virtual control variables for designing track pitch angles
wherein k1 、ζ 1 As a matter of design parameters,is to interference d 1 Estimate of-> and μ1 Output constraints are considered:
wherein ,k0 As a matter of design parameters,is x 1 Time-varying upper and lower bounds of (t), p (z) 1 ) As an auxiliary function of the auxiliary,is a time-varying barrier function;
order theObtaining ∈k by a first order filter>Then-> wherein τ2 Is a parameter of a first order filter;
second control equation in nonlinear longitudinal motion model for carrier aircraftDefinition errorThen z 2 The differentiation of (2) is as follows:
virtual control variables for designing pitch rate
wherein k2 Is a designed parameter;
order theObtaining ∈k by a first order filter>Then->τ 3 Parameters of the corresponding first-order filter;
third control equation in nonlinear longitudinal motion model for carrier aircraftConsider the input saturation problem sat (delta) e ) Define error->Then z 3 The differentiation of (2) is as follows:
wherein g3N G is g 3 Known term in Deltag 3 ＝g 3 -g 3N ；
Approximation estimation using a first RBF neural networkThe method comprises the following steps:
wherein Θ3 * Is the optimal weight value phi of the first RBF neural network 3 Epsilon as a gaussian radial basis function of the first RBF neural network 3 As an error term,obtain->
Design assistance systemCounteracting the effect of input saturation on control behavior:
defining correction error v 3 ：
Then get
wherein D3 To take into account the input saturation sat (delta) e ) And external disturbance d 3 Is a disturbance of (1):
ship-borne aircraft elevator control law delta under saturation condition e The method comprises the following steps:
wherein ,k3 、ζ 3 In order to design the parameters of the device,for the estimation of the first RBF neural network weight, and (2)>To interference D 3 Is a function of the estimate of (2).
5. The method for controlling the automatic carrier landing of the carrier-borne aircraft taking input saturation and output constraint into consideration according to claim 4, wherein the method comprises the following steps of: interference to d 1 Estimation of (a)The update rate of (2) is:
wherein and />Is a control parameter; />Is prediction error, ++> Is a control parameter;
estimation of first RBF neural network weightTo interference D 3 Estimate of->The update rates of (a) are respectively:
wherein , and />For controlling parameters +.>For prediction error-> Is a control parameter.
6. The method for automatically landing a carrier-based aircraft with consideration of input saturation and output constraint according to claim 4, wherein the estimating the uncertainty and the external disturbance caused by the modeling error of the aerodynamic coefficient of the carrier-based aircraft, and the designing of the power compensation subsystem with consideration of the input saturation limit of the carrier-based throttle opening, the deriving of the throttle opening control law under the fixed expected attack angle specifically comprises:
fourth control equation in nonlinear longitudinal motion model for carrier aircraftConsidering the input saturation limit problem sat (delta) suffered by the ship-borne throttle opening T ) Using the unknown function representing the uncertainty of the system in the second RBF neural network estimation equation +.>The method comprises the following steps:
wherein ε4 As an error term,
definition errorThen z 4 The differentiation of (2) is as follows:
wherein D4 In order to be an external disturbance,g 4N g is g 4 Known term in Deltag 4 ＝g 4 -g 4N ；
Building a class of auxiliary system assistance systemsTo counteract the effect of input saturation on control behavior:
defining a corrected tracking error v 4 ＝z 4 -ξ 4 Obtaining
Then, the throttle opening control law delta T Can be designed as follows:
in the formula ,k4 、ζ 4 In order to design the parameters of the device,for the estimation of the weights of the second RBF neural network, and (2)>To interference D 4 Is a function of the estimate of (2).
7. The method for automatic carrier landing control of carrier-borne aircraft taking input saturation and output constraint into consideration as claimed in claim 6, wherein: estimation of second RBF neural network weightsTo interference D 3 Estimate of->The update rates of (a) are respectively:
wherein , and />Is a control parameter; />For prediction error-> Is a control parameter.
8. A carrier-based aircraft automatic landing control system taking input saturation and output constraints into account, the system comprising:
and the aircraft carrier model building module: the method is used for constructing a carrier tail flow model of the aircraft carrier and a carrier motion model of the aircraft carrier;
the carrier-based aircraft model building module: the method is used for calculating the expected track height of the carrier-based aircraft based on the aircraft carrier motion model; establishing a nonlinear longitudinal motion model of the carrier-based aircraft under an inertial coordinate system;
and the height control module is used for: the system is used for carrying out the design of a height control subsystem based on the expected track height and the nonlinear longitudinal motion model of the carrier-based aircraft, taking the uncertainty caused by the pneumatic coefficient model error and the input saturation and output constraint limit of the carrier-based aircraft elevator into consideration, and deducing the control law of the carrier-based aircraft elevator under the input saturation and output constraint;
and the power compensation module is used for: the method is used for estimating uncertainty and external interference caused by a carrier aircraft pneumatic coefficient modeling error, carrying out power compensation subsystem design by considering input saturation and output constraint limits of the carrier aircraft throttle opening, and deducing an accelerator opening control law under a fixed expected attack angle;
landing control module: the method is used for tracking and controlling the expected track of the carrier-based aircraft based on the aircraft elevator control law, and controlling the accelerator opening of the carrier-based aircraft based on the accelerator opening control law so as to control the carrier-based aircraft to automatically carrier.
9. An electronic device, comprising: at least one processor, at least one memory, a communication interface, and a bus;
the processor, the memory and the communication interface complete communication with each other through the bus;
the memory stores program instructions executable by the processor, the processor invoking the program instructions to implement the method of any of claims 1-7.
10. A computer readable storage medium storing computer instructions for causing a computer to implement the method of any one of claims 1 to 7.
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