CN105035311A - Aircraft gust alleviation self-adaptive feed-forward control system - Google Patents

Abstract

The invention relates to an aircraft gust alleviation self-adaptive feed-forward control system. The aircraft gust alleviation self-adaptive feed-forward control system comprises a disturbance passage, a control passage and a disturbance identification passage; a discrete transfer function of the control passage is identified by adopting an identification method, and the disturbance identification passage is established on the basis of the discrete transfer function; a disturbance identified by the disturbance identification passage is used as a feedback calculation input for the coefficient calculation of a feed-forward controller, the feed-forward controller is designed by virtue of an FIR model, so that a compensation effect is improved, the control efficiency is increased, and the requirement of the aircraft gust alleviation self-adaptive feed-forward control is maximally satisfied.

Description

A kind of aircraft gust alleviation adaptive feedforward control system

Technical field

The present invention relates to a kind of aircraft gust alleviation adaptive feedforward control system, particularly a kind of aircraft gust alleviation adaptive feedforward control system, belongs to flying vehicles control technical field.

Background technology

In order to reduce transport plane to the impact of environment and the efficiency improving aircraft, following solution is high aspect ratio light weight aircraft.For Altitude Long Endurance Unmanned Air Vehicle, determine that it must adopt high aspect ratio low weight configuration because high-altitude lower density and its low wing carry characteristic.Rigid motion frequency and the structural elasticity oscillation frequency of this two classes aircraft are close, to seriously excite the vibration of its structure when a wind gust is encountered, this greatly will reduce riding quality (for transport plane) and affect road-holding property, even cause structural failure.

When the partial information of fitful wind information and system is known, general feedback control is better than for feed forward control disturbance compensation.Ideally, feed forward control can eliminate the impact of measurable disturbance completely.Non-time delay between disturbance response and control and compensation during employing feed forward control.

The invention of airborne laser detection sensor (Lightdetectionandranging, LIDAR) is carried out gust load alleviation provide prerequisite for being applied feedforward controller with using.Also some other instrument, the three-dimensional weather radar of the IntuVue as Honeywell, also can be used for the collection carrying out fitful wind information.

In existing feed forward control, as shown in Figure 1, w in figure _gt () is aircraft front fitful wind, for the fitful wind signal that laser acquisition sensor detects, be w _gbeing similar to of (t), H is the transfer function between gust disturbances and aircraft respond, and G is accurate transfer function between flying vehicles control actuator and its response, the approximate of-G, G _cfor feedforward controller, sef-adapting filter is feedforward controller G _ccoefficient is provided.U (t) and u _at () is respectively M signal, x (t) and y (t) are respectively the output response of disturbance passage and control channel, and e (t) is response error, be x (t) with y's (t) and.In this adaptive feedforward controls, adopt the response of aircraft under controller action, namely e (t) is used as the calculating input of feedforward controller coefficient, and such feedforward controller is to the compensation of aircraft based on closed loop response, and compensating action is less than normal.

Summary of the invention

Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, provide a kind of aircraft gust alleviation adaptive feedforward control system, adopt discrimination method to pick out the discrete transfer function of control channel, build perturbed Newton method passage based on this discrete transfer function; The disturbance adopting perturbed Newton method passage to pick out calculates input as the feedback of feedforward controller coefficient, and utilize FIR (finite impulse response (FIR)) model to design feedforward controller, thus increase compensating action, improve control efficiency, meet the demand that aircraft gust alleviation adaptive feedforward controls to the full extent.

Technical solution of the present invention is: a kind of aircraft gust alleviation adaptive feedforward control system, comprises disturbance passage, control channel and perturbed Newton method passage;

Described disturbance channel reception fitful wind signal w _gt (), and output disturbance response signal x (t), control channel receives fitful wind test signal and export control response signal y (t);

Described perturbed Newton method channel reception response error signal e (t), output disturbance response identification signal and input to control channel as feedback signal, output response y (t) sum of output response x (t) that described response error signal e (t) is disturbance passage and control channel, described perturbed Newton method passage is by formula:

$\hat{x}\left(t\right)=\frac{1}{A\left(q^{-1}\right)}\left(A\right(q^{-1}\left)e\right(t)-q^{-d}B(q^{-1}\left)u\right(t\left)\right)$

Provide, wherein q ^-1for delay operator, q ^-1u (t)=u (t-1), u (t) are flying vehicles control actuator incoming signal, A (q ^-1) and B (q ^-1) by formula:

$\hat{G}\left(q^{-1}\right)=\frac{q^{-d}B\left(q^{-1}\right)}{A\left(q^{-1}\right)}$

Provide, for the approximate function of exact transfer function G between the input of flying vehicles control actuator and flying vehicles control channel response.

The approximate function of exact transfer function G between described flying vehicles control actuator input and flying vehicles control channel response detailed process is:

I (), under aircraft trim condition, control actuator input test signal u (t) to aircraft carrys out maneuvering and control rudder face, the response signal y (t) of record-setting flight device control channel;

(ii) with u (t) for input, y (t) for exporting, the approximate function of exact transfer function G between the input of identification flying vehicles control actuator with flying vehicles control channel response signal specifically by formula: $y\left(t\right)\≈-\hat{G}\left(q\right)u\left(t\right)$ Provide, wherein $\hat{G}\≈-G.$

Described identification is completed by the tfest function in MATLAB software.

The sinusoidal signal that described test signal u (t) adopts frequency to increase in time; Specifically by formula:

u(t)＝u ₀+u _A(2πft)

Provide, wherein u ₀constant value, u _afor the amplitude of incoming signal, f is the instantaneous frequency of t, by formula:

f＝f ₀t

Provide, wherein f ₀it is constant value.

Described control channel comprises laser acquisition sensor, filter sef-adapting filter, feedforward controller and control actuator;

Described laser acquisition sensor receives the fitful wind test signal w of input _g(t), and the fitful wind signal that will detect send to feedforward controller and filter described filter with the fitful wind signal recorded for input, output signal u _at (), to sef-adapting filter, sef-adapting filter is according to the output signal u received _a(t) and disturbance response identification signal calculate the coefficient of feedforward controller and export to feedforward controller, feedforward controller is according to the coefficient received and fitful wind signal produce feed-forward control signals u (t) and export to control actuator and perturbed Newton method passage, control actuator and carry out feed forward control according to the feed-forward control signals u (t) received.

Described feedforward controller is the feedforward controller based on FIR model.

Described feedforward controller discrete transfer function G _cz () is specifically by formula:

$G_c\left(z\right)=\underset{k=1}{\overset{n}{\Σ}}{L}_k{B}_k\left(z\right)$

Provide, wherein B _kz () is basic function, L _kfor coefficient comes from sef-adapting filter, n is feedforward controller exponent number given in advance, and z is discrete transfer function variable;

Basic function B _kz () is by formula:

B _k(z)＝z ^-k,k＝1,2,...,n

Provide.

Described L _kobtained by adaptive algorithm, try to achieve coefficient vector L (N)=[L that each basic function corresponding to time step N exports ₁(N), L ₂(N) ..., L _n(N)] concrete steps are:

(1) initialization coefficient vector L (0)=[0,0 ..., 0], P (0)=δ ^-1i, wherein δ is constant, and it is unit matrix that δ is greater than 0, I;

(2) when time step N, the coefficient L (N) that each basic function exports is calculated, specifically by formula:

$L\left(N\right)=L(N-1)+k\left(N\right)\stackrel{\‾}{\mathrm{\ϵ}}\left(N\right)$

Provide, wherein k (N) is gain vector, by formula:

$k\left(N\right)=\frac{\mathrm{\π}\left(N\right)}{\mathrm{\λ}+{\mathrm{\Φ}}^T\left(N\right)\mathrm{\π}\left(N\right)}$

Provide, π (N) is by formula:

π(N)＝P(N-1)Φ(N)

Provide, P (N) is inverse correlation matrix, by formula:

P(N)＝λ ^-1P(N-1)-λ ^-1k(N)Φ ^T(N)P(N-1)

Provide, λ is forgetting factor, 0< λ≤1; the output of each basic function in FIR model when being time step N;

ε (N) is by formula:

ε(N)＝e(N)-L ^T(N-1)Φ(N)

Provide, e (N) is the response of the aircraft when time step N.

The present invention's beneficial effect is compared with prior art:

System in the present invention utilizes the transfer function of control channel to build perturbed Newton method passage, and the disturbed value recognized by perturbed Newton method passage is as value of feedback, for resolving of feedforward controller coefficient, with utilize disturbance channel response signal and control channel response signal sum in existing method, namely the closed loop response of aircraft is compared as value of feedback, increase compensating action, improve control efficiency.

Accompanying drawing explanation

Fig. 1 is existing feed forward control block diagram;

Fig. 2 is gust alleviation control block diagram of the present invention;

Fig. 3 is the FIR controller model schematic diagram that the present invention adopts;

Fig. 4 is the dimensional airfoil illustraton of model in the embodiment of the present invention;

Fig. 5 is sinusoidal signal schematic diagram in the embodiment of the present invention;

Fig. 6 is the response schematic diagram of aerofoil profile in the embodiment of the present invention;

Fig. 7 is " 1-cos " fitful wind schematic diagram in the embodiment of the present invention;

Fig. 8 is the controller response schematic diagram under " 1-cos " fitful wind;

Fig. 9 is for controlling the deflection schematic diagram of rudder face under " 1-cos " fitful wind;

Figure 10 is VonK á rm á n fitful wind schematic diagram in the embodiment of the present invention;

Figure 11 is the response schematic diagram under VonK á rm á n fitful wind Airfoil pitching open-loop response and the controller adopting FIR_e pattern layout control;

Figure 12 adopts the controller of FIR_e pattern layout and the controller aerofoil profile response contrast schematic diagram of FIR_x pattern layout under VonK á rm á n fitful wind;

Figure 13 is under VonK á rm á n fitful wind, based on the control flaps deflecting facet schematic diagram of the controller of FIR_e pattern layout and the controller of FIR_x pattern layout.

Detailed description of the invention

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is further described in detail.

As shown in Figure 2, as can be seen from Figure 2, the system in the present invention comprises disturbance passage, control channel and perturbed Newton method passage to the gust alleviation control block diagram that the present invention adopts;

Described disturbance channel reception fitful wind signal w _gt (), and output disturbance response signal x (t), control channel receives fitful wind test signal and export control response signal y (t);

Described perturbed Newton method channel reception response error signal e (t), output disturbance response identification signal and input to control channel as feedback signal, output response y (t) sum of output response x (t) that described response error signal e (t) is disturbance passage and control channel, described perturbed Newton method passage is by formula:

$\hat{x}\left(t\right)=\frac{1}{A\left(q^{-1}\right)}\left(A\right(q^{-1}\left)e\right(t)-q^{-d}B(q^{-1}\left)u\right(t\left)\right)$

Provide, wherein q ^-1for delay operator, q ^-1u (t)=u (t-1), u (t) are flying vehicles control actuator incoming signal, A (q ^-1) and B (q ^-1) by formula:

$\hat{G}\left(q^{-1}\right)=\frac{q^{-d}B\left(q^{-1}\right)}{A\left(q^{-1}\right)}$

Provide, for the approximate function of exact transfer function G between the input of flying vehicles control actuator and flying vehicles control channel response.

Described control channel comprises laser acquisition sensor, filter sef-adapting filter, feedforward controller and control actuator;

Described laser acquisition sensor receives the fitful wind test signal w of input _g(t), and the fitful wind signal that will detect send to feedforward controller and filter described filter with the fitful wind signal recorded for input, output signal u _at (), to sef-adapting filter, sef-adapting filter is according to the output signal u received _a(t) and disturbance response identification signal produce the coefficient of feedforward controller and export to feedforward controller, feedforward controller is according to the coefficient received and fitful wind test signal produce feed-forward control signals u (t) and export to control actuator and perturbed Newton method passage, control actuator and carry out feed forward control according to the feed-forward control signals u (t) received.Adopt feed forward control, responsive corrections can be carried out in advance when aircraft encounter fitful wind.

Common feed forward control method is using the input of e (t) as sef-adapting filter, and this will reduce the effect of feedforward compensation.Hereinbefore adaptive feedforward control method basis adds perturbed Newton method passage, by identification approximate disturbance out as the input of sef-adapting filter.

For desirable feedforward controller

$G_{c_i}=-{\mathrm{HG}}^{-1}---\left(1\right)$

But in engineering reality, be generally difficult to the exact transfer function obtaining controlled object, generally take method below.

1, algorithmic derivation

First, in control actuator input test signal u (t), obtain corresponding aircraft response y (t), respond according to incoming signal and output the approximate function adopting the linear dimensions identification model tfest Function identification in business software MATLAB to go out transfer function G wherein

$\hat{G}\left(q^{-1}\right)=-\frac{q^{-d}B\left(q^{-1}\right)}{A\left(q^{-1}\right)}\&ap;-G\left(q^{-1}\right)---\left(2\right)$

Q ^-1be delay operator, wherein algorithm is x (t)=q ^-1x (t-1), x (t) are the response in t sample point moment, and x (t-1) is t-1 moment, the i.e. response in next sample point moment.

Can obtain according to the relation in control block diagram

$u_a\left(t\right)=\hat{G}\left(q^{-1}\right){\hat{w}}_g\left(t\right)---\left(3\right)$

With

x(t)＝H(q ^-1)w _g(t)(4)

Can be drawn by formula (2), (3), (4) simultaneous

$x\left(t\right)\&ap;-\frac{H\left(q^{-1}\right)}{G\left(q^{-1}\right)}{u}_a\left(t\right)---\left(5\right)$

Therefore for the coefficient of system feed forward control by with u _at () is input, x (t) adopts adaptive algorithm to calculate for exporting.

In actual applications, because response error e (t) records easily via sensor, often adopt e (t) as the input of sef-adapting filter, namely adopt following formula

$e\left(t\right)=-\frac{H\left(q^{-1}\right)}{G\left(q^{-1}\right)}{u}_a\left(t\right)---\left(6\right)$

Carry out the coefficient of computing controller, wherein fIR model is adopted to be similar in the present invention.Because e (t) differs comparatively large usually with disturbance response x (t), this will affect control efficiency.This method, by increasing perturbed Newton method passage, obtains approximate disturbance its derivation is as follows

e(t)＝x(t)+y(t)(7)

$y\left(t\right)=G\left(q^{-1}\right)u\left(t\right)\&ap;q^{-d}\frac{B\left(q^{-1}\right)}{A\left(q^{-1}\right)}u\left(t\right)---\left(8\right)$

z(t)＝A(q ^-1)e(t)-q ^-dB(q ^-1)u(t)≈A(q ^-1)x(t)(9)

Can be drawn by formula (7), (8), (9) simultaneous

$\hat{x}\left(t\right)=\frac{1}{A\left(q^{-1}\right)}z\left(t\right)\&ap;x\left(t\right)---\left(10\right)$

$\hat{x}\left(t\right)=\frac{1}{A\left(q^{-1}\right)}\left(A\right(q^{-1}\left)e\right(t)-q^{-d}B(q^{-1}\left)u\right(t\left)\right)\&ap;x\left(t\right)$

2, controller

Controller G is thought in this method _cfor linear time invariant system, based on FIR model construction, its discrete transfer function G _cz () can be write as

$G_c\left(z\right)=\underset{k=1}{\overset{n}{\&Sigma;}}{L}_k{B}_k\left(z\right)---\left(11\right)$

Wherein B _kz () is basic function, L _kcome from the sef-adapting filter in control block diagram for coefficient, n is the exponent number of controller given in advance, and z is discrete transfer function variable.

Basic function B in this method _kz () adopts following formula:

B _k(z)＝z ^-k,k＝1,2,...,n，(12)

This basic function is FIR model.Adopt the controller model G of FIR model _cbe illustrated in fig. 3 shown below,

3, adaptive algorithm

Adaptive algorithm can control rudder face amplitude according to response magnitude corresponding real-time adjustment during flight experience fitful wind, slow down gust response, adaptive algorithm adopts index weight to return least-squares algorithm, and employing the method carrys out the coefficient L in calculating formula (11) and Fig. 3 _k(k=1,2 ..., n).First a cost function is defined

$\mathrm{\&epsiv;}\left(N\right)=\underset{i=1}{\overset{N}{\&Sigma;}}{\mathrm{\&lambda;}}^{N-i}|\hat{e}\left(i\right){|}^2,0<\mathrm{\&lambda;}\&le;1,N=1,2,---\left(13\right)$

Wherein N is the quantity of time step, and λ is forgetting factor, it is the response of aircraft with output r (i) of the FIR model error when time step i, namely

$\hat{e}\left(i\right)=\hat{x}\left(i\right)-r\left(i\right)=\hat{x}\left(i\right)-L^T\left(N\right)\mathrm{\&Phi;}\left(i\right)---\left(14\right)$

Wherein vector the output of each basic function in i time step FIR model, L (N)=[L ₁(N), L ₂(N) ..., L _n(N)] be the coefficient of each basic function that N time step is corresponding, or be called tap-weight vector.Adaptive algorithm comprises the following steps:

(1) initialization, initialization coefficient vector L (0)=[0,0 ..., 0], P (0)=δ ^-1i, wherein δ is constant, and it is unit matrix that δ is greater than 0, I;

(2) iteration, when time step N, calculates the coefficient L (N) that each basic function exports, specifically by formula:

$L\left(N\right)=L(N-1)+k\left(N\right)\stackrel{\&OverBar;}{\mathrm{\&epsiv;}}\left(N\right)$

Provide, wherein k (N) is gain vector, by formula:

$k\left(N\right)=\frac{\mathrm{\&pi;}\left(N\right)}{\mathrm{\&lambda;}+{\mathrm{\&Phi;}}^T\left(N\right)\mathrm{\&pi;}\left(N\right)}$

Provide, π (N) is by formula:

π(N)＝P(N-1)Φ(N)

Provide, P (N) is inverse correlation matrix, by formula:

P(N)＝λ ^-1P(N-1)-λ ^-1k(N)Φ ^T(N)P(N-1)

Provide, λ is forgetting factor, 0< λ≤1; Φ (N)=[u _a1(N), u _a2(N) ..., u _an(N) output of each basic function in FIR model when being] time step N;

ε (N) is by formula:

ε(N)＝e(N)-L ^T(N-1)Φ(N)

Provide, e (N) is the response of the aircraft when time step N.

Specific embodiment

For the gust alleviation of dimensional airfoil, step and effect that application the method carries out the control of aircraft gust alleviation are described.

The model of dimensional airfoil is illustrated in fig. 4 shown below, b half chord length in Fig. 4, and cb is the distance of chord length mid point to rudder face rotating shaft, and e.a. is aerofoil profile elastic axis position, and c.g. is aerofoil profile center-of-gravity position, a _hfor chord length mid point is to the ratio of aerofoil profile elastic axis distance with b, x _αthe distance of aerofoil profile elastic axis to aerofoil profile center of gravity and the ratio of b, α is aerofoil profile luffing angle, and h is aerofoil profile sink-float distance, and δ is aerofoil profile control surface deflection angle, K _αand K _ξbe respectively the torsional stiffness of aerofoil profile sink-float rigidity and relative resilient axle.This aerofoil profile has sink-float and pitching two degree of freedom.

This case study on implementation adopts its pitch freedom of middle controller major control of the present invention.In the implementation case, correlation parameter is as shown in table 1:

Table 1

Variable	Numerical value
		B (rice)	0.175
a h	-0.3333
		x α	0.09

For testing the control effects of middle controller of the present invention, fitful wind model considers " 1-cos " and VonK á rm á n two kinds.First test the multicycle " 1-cos " fitful wind, free speed of incoming flow is 8 meter per seconds.

(1) sinusoidal signal u (t) is adopted to control the input δ of rudder face as aerofoil profile, identification G,

The sinusoidal signal that described test signal u (t) adopts frequency to increase in time; Specifically by formula:

u(t)＝u ₀+u _A(2πft)

Provide, wherein u ₀constant value, u _afor the amplitude of incoming signal, f is the instantaneous frequency of t, by formula:

f＝f ₀t

Provide, wherein f ₀be constant value, f needs to cover interested frequency limit.

U ₀get 0, u _athe scope of getting 1, f is 0-8Hz.As shown in Figure 5, under above-mentioned battle array wind action, as shown in Figure 6, as can be seen from Figure 6, pitching mode is fully energized in the response of aerofoil profile for the schematic diagram of sinusoidal signal.

With u (t) for input, with u (t) be input, y (t) be tfest Function identification G in output employing MATLAB software, number of poles is taken as 7, and zero point, quantity was taken as 6.Thus can obtain for $\hat{G}\left(z^{-1}\right)=\frac{0.0040z^{-1}-0.0231z^{-2}+0.0560z^{-3}-0.0725z^{-4}+0.0528z^{-5}-0.0205z^{-6}+0.0033z^{-7}}{1-6.7760z^{-1}+19.6600z^{-2}-31.6800z^{-3}+30.6100z^{-4}-17.7300z^{-5}+5.7000z^{-6}-0.7849z^{-7}}$

(2) structure of perturbed Newton method passage

Previous step has picked out the Approximation Discrete transfer function of control channel, can obtain:

A(z ^-1)＝1-6.7760z ^-1+19.6600z ^-2-31.6800z ^-3+30.6100z ^-4-17.7300z ^-5+5.7000z ^-6-0.7849z ^-7

B(z ^-1)＝0.0040z ^-1-0.0231z ^-2+0.0560z ^-3-0.0725z ^-4+0.0528z ^-5-0.0205z ^-6+0.0033z ^-7

d＝0

Adopt A (z ^-1), B (z ^-1) and d build perturbed Newton method passage.

(3) basic function B is constructed _kz () and CONTROLLER DESIGN, adopt the method in formula (12) to construct basic function B _kz (), carrys out CONTROLLER DESIGN according to Fig. 3.

Gust alleviation effect

(1) " 1-cos " fitful wind

That first tests " 1-cos " fitful wind slows down effect, and as shown in Figure 7, wherein fitful wind intensity is 1m/s to fitful wind schematic diagram, and fitful wind length is 1.75m.Hereinafter, the controller adopting the 20 rank FIR pattern layouts calculating input with the closed loop response of aerofoil profile for sef-adapting filter is represented with FIR_e, controller of the present invention is represented, namely with the controller that identification passage identification disturbance is out 20 rank FIR pattern layouts of sef-adapting filter calculating input with FIR_x.Under above-mentioned fitful wind effect, as shown in Figure 8, solid line openloop is aerofoil profile open loop pitching response for aerofoil profile pitching open-loop response and the response of the pitching under two kinds of controllers control.As can be seen from Fig. 8, after adopting two kinds of controllers, aerofoil profile pitching response amplitude is reduced, and it is more more obvious than adopting the gust alleviation effect of FIR_e controller to adopt FIR_x controller of the present invention, and gust response amplitude is significantly less than the gust response amplitude adopting FIR_e controller.The deflection of corresponding control rudder face as shown in Figure 9.

(2) VonK á rm á n fitful wind

That tests VonK á rm á n fitful wind slows down effect, and as shown in Figure 10, peak gust speed is 0.7m/s to fitful wind schematic diagram.Under this fitful wind effect, as shown in figure 11, solid line openloop is aerofoil profile open loop pitching response to the pitching response under aerofoil profile pitching open-loop response and FIR_e and FIR_x controller control.As can be seen from Figure 11, after adopting FIR_e controller, aerofoil profile pitching response amplitude reduces.Adopt the fitful wind pitching response contrast of FIR_e controller and FIR_x controller of the present invention as shown in figure 12, as can be seen from Figure 12, from whole structure, FIR_x adaptive feedforward controller of the present invention is better than the gust alleviation effect of FIR_e controller.The standard deviation that open loop and controller action Airfoil respond is as shown in table 3, also this conclusion can be drawn from the standard deviation of following table 3, adopt FIR_e controller to make gust response amplitude standard deviation reduce by 29.2%, use controller of the present invention to make gust response amplitude standard deviation reduce by 34.3%.

Table 3

Open loop or controller type

Standard deviation [deg]

Open loop	0.2165
		FIR_e controller	0.1533
FIR_x controller	0.1357

As shown in figure 13, in this figure, solid line is the control surface deflection of FIR_x controller to corresponding controller control surface deflection, and dash line is the control surface deflection of FIR_e controller of the present invention.

The content be not described in detail in specification sheets of the present invention belongs to the known technology of professional and technical personnel in the field.

Claims (8)

1. an aircraft gust alleviation adaptive feedforward control system, is characterized in that: comprise disturbance passage, control channel and perturbed Newton method passage;

Described disturbance channel reception fitful wind signal w _gt (), and output disturbance response signal x (t), control channel receives fitful wind test signal and export control response signal y (t);

Described perturbed Newton method channel reception response error signal e (t), output disturbance response identification signal and input to control channel as feedback signal, output response y (t) sum of output response x (t) that described response error signal e (t) is disturbance passage and control channel, described perturbed Newton method passage is by formula:

$\hat{x}\left(t\right)=\frac{1}{A\left(q^{-1}\right)}\left(A\right(q^{-1}\left)e\right(t)-q^{-d}B(q^{-1}\left)u\right(t\left)\right)$

Provide, wherein q ^-1for delay operator, q ^-1u (t)=u (t-1), u (t) are flying vehicles control actuator incoming signal, A (q ^-1) and B (q ^-1) by formula:

$\hat{G}\left(q^{-1}\right)=\frac{q^{-d}B\left(q^{-1}\right)}{A\left(q^{-1}\right)}$

Provide, for the approximate function of exact transfer function G between the input of flying vehicles control actuator and flying vehicles control channel response.

2. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 1, is characterized in that: the approximate function of exact transfer function G between described flying vehicles control actuator input and flying vehicles control channel response detailed process is:

(2-1) under aircraft trim condition, control actuator input test signal u (t) to aircraft carrys out maneuvering and control rudder face, the response signal y (t) of record-setting flight device control channel;

(2-2) with u (t) for input, y (t) for exporting, the approximate function of exact transfer function G between the input of identification flying vehicles control actuator with flying vehicles control channel response signal specifically by formula: $y\left(t\right)\&ap;-\hat{G}\left(q\right)u\left(t\right)$ Provide, wherein $\hat{G}\&ap;-G.$

3. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 2, is characterized in that: described identification is completed by the tfest function in MATLAB software.

4. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 1 and 2, is characterized in that: the sinusoidal signal that described test signal u (t) adopts frequency to increase in time; Specifically by formula:

u(t)＝u ₀+u _A(2πft)

Provide, wherein u ₀constant value, u _afor the amplitude of incoming signal, f is the instantaneous frequency of t, by formula:

f＝f ₀t

Provide, wherein f ₀it is constant value.

5. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 1 and 2, is characterized in that: described control channel comprises laser acquisition sensor, filter sef-adapting filter, feedforward controller and control actuator;

Described laser acquisition sensor receives the fitful wind test signal w of input _g(t), and the fitful wind signal that will detect send to feedforward controller and filter described filter with the fitful wind signal recorded for input, output signal u _at (), to sef-adapting filter, sef-adapting filter is according to the output signal u received _a(t) and disturbance response identification signal calculate the coefficient of feedforward controller and export to feedforward controller, feedforward controller is according to the coefficient received and fitful wind signal produce feed-forward control signals u (t) and export to control actuator and perturbed Newton method passage, control actuator and carry out feed forward control according to the feed-forward control signals u (t) received.

6. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 5, is characterized in that: described feedforward controller is the feedforward controller based on FIR model.

7. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 5 or 6, is characterized in that: described feedforward controller discrete transfer function G _cz () is specifically by formula:

$G_c\left(z\right)=\underset{k=1}{\overset{n}{\&Sigma;}}{L}_k{B}_k\left(z\right)$

Provide, wherein B _kz () is basic function, L _kfor coefficient comes from sef-adapting filter, n is feedforward controller exponent number given in advance, and z is discrete transfer function variable;

Basic function B _kz () is by formula:

B _k(z)=z ^-k, k=1,2 ..., n provides.

8. a kind of aircraft gust alleviation adaptive feedforward control system according to claim 7, is characterized in that: described L _kobtained by adaptive algorithm, try to achieve coefficient vector L (N)=[L that each basic function corresponding to time step N exports ₁(N), L ₂(N) ..., L _n(N)] concrete steps are:

(8-1) initialization coefficient vector L (0)=[0,0 ..., 0], P (0)=δ ^-1i, wherein δ is constant, and it is unit matrix that δ is greater than 0, I;

(8-2) when time step N, the coefficient L (N) that each basic function exports is calculated, specifically by formula:

$L\left(N\right)=L(N-1)+k\left(N\right)\stackrel{\&OverBar;}{\mathrm{\&epsiv;}}\left(N\right)$

Provide, wherein k (N) is gain vector, by formula:

$k\left(N\right)=\frac{\mathrm{\&pi;}\left(N\right)}{\mathrm{\&lambda;}+{\mathrm{\&Phi;}}^T\left(N\right)\mathrm{\&pi;}\left(N\right)}$

Provide, π (N) is by formula:

π(N)＝P(N-1)Φ(N)

Provide, P (N) is inverse correlation matrix, by formula:

P(N)＝λ ^-1P(N-1)-λ ^-1k(N)Φ ^T(N)P(N-1)

Provide, λ is forgetting factor, 0< λ≤1; the output of each basic function in FIR model when being time step N;

ε (N) is by formula:

ε(N)＝e(N)-L ^T(N-1)Φ(N)

Provide, e (N) is the response of the aircraft when time step N.