CN106292294A - Shipborne UAV auto landing on deck based on model reference self-adapting control controls device - Google Patents

Abstract

The invention discloses a kind of Shipborne UAV auto landing on deck based on model reference self-adapting control and control device, belong to aviation aircraft and control technical field.Apparatus of the present invention include: warship instruction and downslide reference trajectory generation module, for according to position relative with Shipborne UAV, naval vessel and absolute location information, generate three-dimensional downslide reference trajectory signal and speed command signal；Model reference adaptive flight control modules, model reference self-adapting control algorithm is utilized to generate the flight control signal of Shipborne UAV so that the practical flight track of Shipborne UAV and speed Tracking three-dimensional downslide reference trajectory signal and the speed command that warship instruction is generated with downslide reference trajectory generation module.This invention is applicable to fixed-wing people's carrier-borne aircraft and unmanned carrier-borne aircraft.Compared to existing technology, the present invention need not the calculating of leading law, controls warship more accurate, and control system is simpler, and realtime control is good.

Description

Shipborne UAV auto landing on deck based on model reference self-adapting control controls device

Technical field

The present invention relates to a kind of Shipborne UAV auto landing on deck based on model reference self-adapting control and control device, belong to Aviation space flight controls technical field.

Background technology

" warship " in the present invention includes that runway blocks the landing approach such as warship, net collision recovery, in the principle of control method On there is versatility.

Carrier-borne aircraft is as the important weapon strength of aircraft carrier, and its key technology is how to be guaranteed in very pacifying under rugged environment The most accurate the warship.Owing to warship environment is very severe, unmanned plane all can warship product by the perturbation action such as mother ship carrier motion, stern air-flow The biggest raw impact, be significantly greatly increased carrier-borne aircraft warship difficulty, had a strong impact on warship safety.Naval vessel rides the sea process In, owing to being affected by wave, swell and wind, warship body will produce the deck of the forms such as pitching, driftage, rolling, dipping and heaving Motion, cause on naval vessel warship point be Three Degree Of Freedom moving point, drastically influence difficulty and the safety of warship.Marine changeable In the environment of, carrier-borne aircraft on naval vessel warship time, stern flow perturbation is also to affect its key factor warship performance.Marching into the arena Warship section, with the reduction of flight speed, flying angle the most all can exceed the critical angle of attack, is in speed unstable region, makes guarantor Hold flight path and become extremely difficult.Meanwhile, Shipborne UAV itself is a complicated control object, has non-linear, no The characteristics such as definitiveness, multivariate, close coupling.The change of the interference of complex environment factor, flying height and state and modeling are by mistake The factors such as difference together constitute the uncertain factor of Shipborne UAV System.

Current automated carrier landing system (ACLS), is generally made up of equipment on warship and airborne equipment two parts.Warship Upper part has a tracking radar, stabilized platform, high-speed computer, display device, Data-Link coding/transmitter, Data-Link watch-dog, Flight path monitor etc..Machine upper part has Data-Link receiver, receiver decoder, autopilot coupler, automatically flies Control system, auto-throttle controller, radar booster etc..Auto landing on deck control method generally uses to be made TRAJECTORY CONTROL loop For external loop, gesture stability loop and speed controlling as inner looping, TRAJECTORY CONTROL loop is based on track following control information, knot Close deck motion prediction and compensated information, after tracking controller, generate attitude and speed command signal, be sent to flight control System processed, flight control system demands follows the tracks of these command signals, to obtain desired track, attitude and speed, wherein inside and outside The design of circuit controls rule is all based on conventional single-loop method for designing, such as PID control method.But, it is adaptable to unmanned plane The application report that auto landing on deck system (ACLS) is not disclosed.

In summary, existing carrier-borne aircraft auto landing on deck controls technology and generally there is system complex, poor real, hardware Seek high defect.

Summary of the invention

The technical problem to be solved is to overcome prior art not enough, it is provided that a kind of adaptive based on model reference The Shipborne UAV auto landing on deck that should control controls device, it is not necessary to the calculating of leading law, warship more accurate, control system Simpler, realtime control is good.

The present invention solves above-mentioned technical problem the most by the following technical solutions:

A kind of Shipborne UAV auto landing on deck based on model reference self-adapting control controls device, and this device includes: Warship instruction and downslide reference trajectory generation module, for believing according to position relative with Shipborne UAV, naval vessel and absolute position Breath, generates three-dimensional downslide reference trajectory signal and speed command signal；

Model reference adaptive flight control modules, utilizes model reference self-adapting control algorithm to generate Shipborne UAV Flight control signal so that the practical flight track of Shipborne UAV and speed Tracking warship instruction and generated with downslide reference trajectory Three-dimensional downslide reference trajectory signal that module is generated and speed command.

Preferably, in model reference adaptive flight control modules, for the name of reference model is controlled Matrix Estimation ValueK₂T () carries out the adaptive updates rule design in accordance with the following methods of online updating and obtains:

Orderω (t)=[Δ x^T(t),Δr^T(t)]^T, Δ r is reference-input signal, and Δ x is shape State vector, then output tracking error

E (t)=Δ y (t)-Δ y_m(t),

In formula, Δ y, Δ y_mThe system of being respectively output, reference model output；

Defining new error signal is

ε (t)=ξ_m(s) h (s) [e] (t)+Ψ (t) ξ (t),

In formula, h (s)=1/f (s), f (s) are Stable Polynomials, and Ψ (t) is Ψ^*=K_pEstimated value, K_pFor high-frequency gain Matrix, ξ_mS () is the Interactive matrix of reference model, ξ (t)=Θ^T(t)ζ(t)-h(s)[Δu](t)；

Order

ζ (t)=h (s) [ω] (t)

The newest error signal is converted into

$\mathrm{\ϵ}\left(t\right)={\mathrm{\Ψ}}^{*}{\widetilde{\mathrm{\Θ}}}^T\mathrm{\ζ}\left(t\right)+\widetilde{\mathrm{\Ψ}}\left(t\right)\mathrm{\ξ}\left(t\right)$

In formula,

Then, the adaptive updates rule controlling matrix parameter is designed as:

${\stackrel{\·}{\mathrm{\Θ}}}^T\left(t\right)=\frac{-S_p\mathrm{\ϵ}\left(t\right){\mathrm{\ζ}}^T\left(t\right)}{m^2\left(t\right)}$

$\stackrel{\·}{\mathrm{\Ψ}}\left(t\right)=\frac{-{\mathrm{\Γ\ϵ\ξ}}^T\left(t\right)}{m^2\left(t\right)}$

In formula, Γ=Γ^T＞ 0, S_pRepresent reversible permanent Matrix.

Preferably, the input signal of model reference adaptive flight control modules includes: four longitudinal directions of Shipborne UAV Quantity of state flight speed V, angle of attack α, pitch rate q, pitching angle theta；Five horizontal stroke lateral quantity of state sideslip angle betas, rollings Corner speed p, yawrate r, roll angle φ, yaw angle ψ；The speed of warship instruction and the output of downslide reference trajectory generation module Degree instruction V_cAnd downslide reference trajectory signal X_EATDc(t),Y_EATDc(t),Z_EATDc(t)；

The output signal of model reference adaptive flight control modules includes: accelerator open degree Δ δ_T, elevator drift angle Δ δ_e、 Aileron drift angle δ_a, rudder δ_r；

Flight Control Law in model reference adaptive flight control modules includes longitudinal and horizontal crabbing control law, logical Cross following methods design to obtain:

The first step, based on following vertical linear model

$\left[\begin{array}{c}\mathrm{\Δ}\stackrel{\·}{V}\\ \mathrm{\Δ}\stackrel{\·}{\mathrm{\α}}\\ \mathrm{\Δ}\stackrel{\·}{q}\\ \mathrm{\Δ}\stackrel{\·}{\mathrm{\θ}}\\ \mathrm{\Δ}\stackrel{\·}{H}\end{array}\right]=A_{lon}\left[\begin{array}{c}\mathrm{\Δ}V\\ \mathrm{\Δ}\mathrm{\α}\\ \mathrm{\Δ}q\\ \mathrm{\Δ}\mathrm{\θ}\\ \mathrm{\Δ}H\end{array}\right]+B_{lon}\left[\begin{array}{c}\mathrm{\Δ}{\mathrm{\δ}}_e\\ {\mathrm{\Δ\δ}}_T\end{array}\right]$

${\mathrm{\Δy}}_{lon}=C_{lon}{x}_{lon}=\left[\begin{array}{ccccc}1& 0& 0& 0& 0\\ 0& 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\Δ}V\\ \mathrm{\Δ}\mathrm{\α}\\ \mathrm{\Δ}q\\ \mathrm{\Δ}\mathrm{\θ}\\ \mathrm{\Δ}H\end{array}\right]$

Judge the relative order l of transfer function matrix_i, i=1,2, calculate high-frequency gain matrix

$K_p=\left[\begin{array}{c}{c}_{1,lon}{A}_{lon}^{l_1-1}{B}_{lon}\\ c_{2,lon}{A}_{lon}^{l_2-1}{B}_{lon}\end{array}\right]$

Ensure as nonsingular；In formula, A_lon、B_lon、C_lonThe vertical linear sytem matrix described for variable symbol, c_1,lon、 c_2,lonIt is respectively C_lonThe 1st row and the 2nd row；

Second step, according to the relative order l of transfer function matrix_i, i=1,2, choose Interactive matrixWherein p_1i,p_2iExpect limit for longitudinal system, thus design following reference model

Δy_m,lon(t)=W_m,lon(s)[Δr_lon](t)

In formula, Δ r_ion(t)=[0, Δ H_EATDc]^T,

3rd step, calculates Longitudinal Flight Control Law

$\left[\begin{array}{c}\mathrm{\Δ}{\mathrm{\δ}}_e\left(t\right)\\ \mathrm{\Δ}{\mathrm{\δ}}_T\left(t\right)\end{array}\right]=K_{1,lon}^T\left(t\right)\left[\begin{array}{c}\mathrm{\Δ}V\left(t\right)\\ \mathrm{\Δ}\mathrm{\α}\left(t\right)\\ \mathrm{\Δ}q\left(t\right)\\ \mathrm{\Δ}\mathrm{\θ}\left(t\right)\\ \mathrm{\Δ}H\left(t\right)\end{array}\right]+K_{2,lon}\left(t\right)\left[\begin{array}{c}0\\ \mathrm{\Δ}{H}_{EATDc}\left(t\right)\end{array}\right]$

Wherein,K_2,lonT () is the control matrix of online updating；

4th step, based on following horizontal lateral linear model

$\left[\begin{array}{c}\stackrel{\·}{\mathrm{\β}}\\ \stackrel{\·}{p}\\ \stackrel{\·}{r}\\ \stackrel{\·}{\mathrm{\φ}}\\ \stackrel{\·}{\mathrm{\ψ}}\\ \stackrel{\·}{y}\end{array}\right]=A_{lat}\left[\begin{array}{c}\mathrm{\β}\\ p\\ r\\ \mathrm{\φ}\\ \mathrm{\ψ}\\ y\end{array}\right]+B_{lat}\left[\begin{array}{c}{\mathrm{\δ}}_a\\ {\mathrm{\δ}}_r\end{array}\right]$

$y_{lat}=C_{lat}{x}_{lat}=\left[\begin{array}{cccccc}1& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\β}\\ p\\ r\\ \mathrm{\φ}\\ \mathrm{\ψ}\\ y\end{array}\right]$

Judge the relative order l of transfer function matrix_i, i=1,2, calculate high-frequency gain matrix

$K_p=\left[\begin{array}{c}{c}_{1,lat}{A}_{lat}^{l_1-1}{B}_{lat}\\ c_{2,lat}{A}_{lat}^{l_2-1}{B}_{lat}\end{array}\right]$

Ensure as nonsingular；In formula, A_lat、B_lat、C_latFor horizontal lateral linear sytem matrix, c_1,lat、c_2,latIt is respectively C_lat The 1st row and the 2nd row；

5th step, according to the relative order l of transfer function matrix_i, i=1,2, choose Interactive matrixWherein p_1i,p_2iExpect limit for horizontal lateral system, thus design is following with reference to mould Type

y_m,lat(t)=W_m,lat(s)[r_lat](t)

In formula, r_lat(t)=[0, Y_EATDc]^T,

6th step, calculates horizontal crabbing control law

$\left[\begin{array}{c}{\mathrm{\δ}}_a\left(t\right)\\ {\mathrm{\δ}}_r\left(t\right)\end{array}\right]=K_{1,\mathrm{lat}}^T\left(t\right)\left[\begin{array}{c}\mathrm{\β}\left(t\right)\\ p\left(t\right)\\ r\left(t\right)\\ \mathrm{\φ}\left(t\right)\\ \mathrm{\ψ}\left(t\right)\\ y\left(t\right)\end{array}\right]+K_{2,\mathrm{lat}}\left(t\right)\left[\begin{array}{c}0\\ Y_{\mathrm{EATDc}}\left(t\right)\end{array}\right]$

Wherein,K_2,latT () is the control matrix of online updating.

Preferably, warship instruction to include with the input signal of downslide reference trajectory generation module: naval vessel runway or glide path Azimuth (ψ_S+λ_ac), wherein ψ_SFor azimuth, naval vessel, λ_acFor angled deck angle；Warship instruction raw with downslide reference trajectory The output signal becoming module includes: speed command V_cAnd downslide reference trajectory signal X_EATDc(t),Y_EATDc(t),Z_EATDc(t)。

Further.Warship instruction and make formation speed instruction V using the following method with downslide reference trajectory generation module_cUnder and Sliding reference trajectory signal X_EATDc(t)、Y_EATDc(t)、Z_EATDc(t):

After capture glide path, according to the known initial height-Z that glides_EA0, gliding angle γ_c, gliding speed V_c, calculate warship Time

$t_d=\frac{Z_{EA0}}{V_c{\mathrm{sin\γ}}_c}$

With glide path length

$R_A=V_c{t}_d=\frac{Z_{EA0}}{{\mathrm{sin\γ}}_c};$

Then calculate with the three-dimensional downslide reference trajectory under preferable the warship point earth axes as initial point:

$\left\{\begin{array}{c}{X}_{EATDc}\left(t\right)=V_c(t-t_d){\mathrm{cos\γ}}_{c}cos({\mathrm{\ψ}}_S+{\mathrm{\λ}}_{ac})\\ Y_{EATDc}\left(t\right)=V_c(t-t_d){\mathrm{cos\γ}}_c\sin ({\mathrm{\ψ}}_S+{\mathrm{\λ}}_{ac})\\ Z_{EATDc}\left(t\right)=-H_{EATDc}\left(t\right)=-V_c(t-t_d){\mathrm{sin\γ}}_c\end{array}\right..$

Compared to existing technology, the method have the advantages that

(1) present invention is according to position relative with Shipborne UAV, naval vessel and absolute location information, warship in line computation and refers to Make signal, generate Shipborne UAV downslide reference trajectory, and control Shipborne UAV tracking benchmark rail by flight control system Mark；Compared with prior art, it is possible to increase Shipborne UAV and the concertedness on naval vessel.

(2) present invention designs flight controller under Shipborne UAV model parameter and structure uncertain condition, from theory The output signal of the output signal asymptotic tracking reference model of the upper uncertain linear system of guarantee model, and then tracking parameter is defeated Enter signal, i.e. Shipborne UAV height, flight path and speed can follow the tracks of reference trajectory and speed, finally realize glide paths with Track, thus can accurately complete warship task.Therefore, the present invention can control parameter by on-line control, have the strongest adaptive should be able to Power and robust performance, and tradition auto landing on deck system uses classical control method to design, and relies on the accurate model of carrier-borne aircraft, Adaptivity is lacked for systematic uncertainty and external disturbance.

(3) present invention does not has the calculating of leading law, and flight control system is directly adaptive by design by trajectory error Control law is answered to be reduced or eliminated so that the design of flight control system becomes simpler.

Accompanying drawing explanation

Fig. 1 represents that present invention Shipborne UAV based on model reference self-adapting control auto landing on deck controls the principle of device Block diagram；

Fig. 2 represent Shipborne UAV warship during height track following design sketch；

Fig. 3 represent Shipborne UAV warship during speed controlling design sketch；

In figure, solid line represents expected value curve, and dotted line represents actual value curve.

Detailed description of the invention

Below in conjunction with the accompanying drawings technical scheme is described in detail:

Present invention Shipborne UAV based on model reference self-adapting control auto landing on deck controls principle such as Fig. 1 institute of device Showing, it is made up of with downslide reference trajectory generation module, adaptive flight control system module two parts warship instruction.

Warship instruction and downslide reference trajectory generation module

The input signal of this module includes: the azimuth (ψ of naval vessel runway or glide path_S+λ_ac), wherein ψ_SFor orientation, naval vessel Angle, λ_acFor angled deck angle.

The output signal of this module includes three-dimensional downslide reference trajectory signal X_EATDc(t),Y_EATDc(t),Z_EATDc(t) and speed Degree command signal V_c.Wherein, downslide reference trajectory signal, speed command signal export to adaptive flight control system module.

The first step, carrier-borne aircraft capture glide path, it is known that initially glide height-Z_EA0, gliding angle γ_c, gliding speed V_c, calculate The warship time

$t_d=\frac{Z_{EA0}}{V_c{\mathrm{sin\γ}}_c}---\left(1\right)$

With glide path length

$R_A=V_c{t}_d=\frac{Z_{EA0}}{{\mathrm{sin\γ}}_c}---\left(2\right)$

Second step, calculates with the three-dimensional downslide reference trajectory under preferable the warship point earth axes as initial point

$\left\{\begin{array}{c}{X}_{EATDc}\left(t\right)=V_c(t-t_d){\mathrm{cos\γ}}_{c}cos({\mathrm{\ψ}}_S+{\mathrm{\λ}}_{ac})\\ Y_{EATDc}\left(t\right)=V_c(t-t_d){\mathrm{cos\γ}}_c\sin ({\mathrm{\ψ}}_S+{\mathrm{\λ}}_{ac})\\ Z_{EATDc}\left(t\right)=-H_{EATDc}\left(t\right)=-V_c(t-t_d){\mathrm{sin\γ}}_c\end{array}\right.---\left(3\right)$

Model reference adaptive flight control modules

The input signal of this module includes: the longitudinal quantity of state x=of the Shipborne UAV of sensor feedback four (V, α, β, p, q,r,φ,θ,ψ,X,Y,H)^TFlight speed V, angle of attack α, pitch rate q, pitching angle theta；Five horizontal strokes of sensor feedback Lateral quantity of state sideslip angle beta, roll angle speed p, yawrate r, roll angle φ, yaw angle ψ；Warship instruction and glide The speed command V of reference trajectory generation module output_c, downslide reference trajectory signal X_EATDc(t),Y_EATDc(t),Z_EATDc(t)。

The output signal of this module includes: accelerator open degree Δ δ_T, elevator drift angle Δ δ_e, aileron drift angle δ_a, rudder δ_r.It is sent to actuator, thus controls carrier-borne aircraft flight.

Detailed process is: first calculate Longitudinal Flight Control Law (first, second and third step), secondly calculates horizontal crabbing control System rule (fourth, fifth, six steps).

The first step, based on following vertical linear model

$\left[\begin{array}{c}\mathrm{\Δ}\stackrel{\·}{V}\\ \mathrm{\Δ}\stackrel{\·}{\mathrm{\α}}\\ \mathrm{\Δ}\stackrel{\·}{q}\\ \mathrm{\Δ}\stackrel{\·}{\mathrm{\θ}}\\ \mathrm{\Δ}\stackrel{\·}{H}\end{array}\right]=A_{lon}\left[\begin{array}{c}\mathrm{\Δ}V\\ \mathrm{\Δ}\mathrm{\α}\\ \mathrm{\Δ}q\\ \mathrm{\Δ}\mathrm{\θ}\\ \mathrm{\Δ}H\end{array}\right]+B_{lon}\left[\begin{array}{c}\mathrm{\Δ}{\mathrm{\δ}}_e\\ {\mathrm{\Δ\δ}}_T\end{array}\right]---\left(4\right)$

${\mathrm{\Δy}}_{lon}=C_{lon}{x}_{lon}=\left[\begin{array}{ccccc}1& 0& 0& 0& 0\\ 0& 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\Δ}V\\ \mathrm{\Δ}\mathrm{\α}\\ \mathrm{\Δ}q\\ \mathrm{\Δ}\mathrm{\θ}\\ \mathrm{\Δ}H\end{array}\right]---\left(5\right)$

Judge the relative order l of transfer function matrix_i, i=1,2, calculate high-frequency gain matrix

$K_p=\left[\begin{array}{c}{c}_{1,lon}{A}_{lon}^{l_1-1}{B}_{lon}\\ c_{2,lon}{A}_{lon}^{l_2-1}{B}_{lon}\end{array}\right]---\left(6\right)$

Ensure as nonsingular.In formula, A_lon、B_lon、C_lonThe vertical linear sytem matrix described for variable symbol, c_1,lon、 c_2,lonIt is respectively C_lonThe 1st row and the 2nd row.

Second step, according to the relative order l of transfer function matrix_i, i=1,2, choose Interactive matrixWherein p_1i,p_2iExpect limit for longitudinal system, thus design following reference model

Δy_m,lon(t)=W_m,lon(s)[Δr_lon](t) (7)

In formula, Δ r_lon(t)=[0, Δ H_EATDc]^T,

3rd step, calculates Longitudinal Flight Control Law

$\left[\begin{array}{c}\mathrm{\Δ}{\mathrm{\δ}}_e\left(t\right)\\ \mathrm{\Δ}{\mathrm{\δ}}_T\left(t\right)\end{array}\right]=K_{1,lon}^T\left(t\right)\left[\begin{array}{c}\mathrm{\Δ}V\left(t\right)\\ \mathrm{\Δ}\mathrm{\α}\left(t\right)\\ \mathrm{\Δ}q\left(t\right)\\ \mathrm{\Δ}\mathrm{\θ}\left(t\right)\\ \mathrm{\Δ}H\left(t\right)\end{array}\right]+K_{2,lon}\left(t\right)\left[\begin{array}{c}0\\ \mathrm{\Δ}{H}_{EATDc}\left(t\right)\end{array}\right]---\left(8\right)$

Wherein,K_2,lonT (), for controlling matrix, carries out online updating according to reference model adaptive control algorithm.

4th step, based on following horizontal lateral linear model

$\left[\begin{array}{c}\stackrel{\·}{\mathrm{\β}}\\ \stackrel{\·}{p}\\ \stackrel{\·}{r}\\ \stackrel{\·}{\mathrm{\φ}}\\ \stackrel{\·}{\mathrm{\ψ}}\\ \stackrel{\·}{y}\end{array}\right]=A_{lat}\left[\begin{array}{c}\mathrm{\β}\\ p\\ r\\ \mathrm{\φ}\\ \mathrm{\ψ}\\ y\end{array}\right]+B_{lat}\left[\begin{array}{c}{\mathrm{\δ}}_a\\ {\mathrm{\δ}}_r\end{array}\right]---\left(9\right)$

$y_{lat}=C_{lat}{x}_{lat}=\left[\begin{array}{cccccc}1& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\β}\\ p\\ r\\ \mathrm{\φ}\\ \mathrm{\ψ}\\ y\end{array}\right]---\left(4\right)$

Judge the relative order l of transfer function matrix_i, i=1,2, calculate high-frequency gain matrix

$K_p=\left[\begin{array}{c}{c}_{1,lat}{A}_{lat}^{l_1-1}{B}_{lat}\\ c_{2,lat}{A}_{lat}^{l_2-1}{B}_{lat}\end{array}\right]---\left(5\right)$

Ensure as nonsingular.In formula, A_lat、B_lat、C_latFor horizontal lateral linear sytem matrix, c_1,lat、c_2,latIt is respectively C_lat The 1st row and the 2nd row.

5th step, according to the relative order l of transfer function matrix_i, i=1,2, choose Interactive matrixWherein p_1i,p_2iExpect limit for horizontal lateral system, thus design is following with reference to mould Type

y_m,lat(t)=W_m,lat(s)[r_lat](t) (6)

In formula, r_lat(t)=[0, Y_EATDc]^T,

6th step, calculates horizontal crabbing control law

$\left[\begin{array}{c}{\mathrm{\δ}}_a\left(t\right)\\ {\mathrm{\δ}}_r\left(t\right)\end{array}\right]=K_{1,lat}^T\left(t\right)\left[\begin{array}{c}\mathrm{\β}\left(t\right)\\ p\left(t\right)\\ r\left(t\right)\\ \mathrm{\φ}\left(t\right)\\ \mathrm{\ψ}\left(t\right)\\ y\left(t\right)\end{array}\right]+K_{2,lat}\left(t\right)\left[\begin{array}{c}0\\ Y_{EATDc}\left(t\right)\end{array}\right]---\left(7\right)$

Wherein,K_2,latT (), for controlling matrix, carries out online updating according to reference model adaptive control algorithm.

Model reference self-adapting control algorithm

For following linear system

$\mathrm{\Δ}\stackrel{\·}{x}\left(t\right)=A\mathrm{\Δ}x\left(t\right)+B\mathrm{\Δ}u\left(t\right),\mathrm{\Δ}y\left(t\right)=C\mathrm{\Δ}x\left(t\right)---\left(8\right)$

In formula, Δ x is state vector, and Δ u is dominant vector, and Δ y is output vector, and A, B, C are sytem matrix.

Structure reference model is

${\mathrm{\Δy}}_m\left(t\right)=W_m\left(s\right)\[\mathrm{\Δ}r\]\left(t\right),W_m\left(s\right)={\mathrm{\ξ}}_m^{-1}\left(s\right)---\left(9\right)$

In formula, ξ_mS () is Interactive matrix.

The purpose controlled is the output Δ y of desirable system output Δ y track reference model_m, therefore build control law structure For

$\mathrm{\Δ}u\left(t\right)=K_1^T\left(t\right)\mathrm{\Δ}x\left(t\right)+K_2\left(t\right)\mathrm{\Δ}r\left(t\right)---\left(10\right)$

In formula, Δ r is reference-input signal,K₂T () is that name controls matrixEstimated value.

Control matrix in the case of model parameter is completely known, in design name control lawMeet as follows Equality condition

$G_c\left(s\right)=C{(sI-A-{\mathrm{BK}}_1^{*T})}^{-1}{\mathrm{BK}}_2^{*}=W_m\left(s\right),W_m\left(s\right)={\mathrm{\ξ}}_m^{-1}\left(s\right)---\left(17\right)$

Then ensure that the output Δ y of system output Δ y perfect tracking reference model_m.But, model parameter is uncertain Under situation, it is impossible to obtain name and control matrixTherefore estimated value can only be usedK₂T () substitutes, estimated value needs profit Online updating is carried out by following adaptive algorithm.

Orderω (t)=[Δ x^T(t),Δr^T(t)]^T, then output tracking error

E (t)=Δ y (t)-Δ y_m(t) (18)

Defining new error signal is

ε (t)=ξ_m(s)h(s)[e](t)+Ψ(t)ξ(t) (19)

In formula, h (s)=1/f (s), f (s) are Stable Polynomials, and Ψ (t) is Ψ^*=K_pEstimated value.

Order

ζ (t)=h (s) [ω] (t), ξ (t)=Θ^T(t)ζ(t)-h(s)[Δu](t) (11)

The newest error signal is converted into

$\mathrm{\ϵ}\left(t\right)={\mathrm{\Ψ}}^{*}{\widetilde{\mathrm{\Θ}}}^T\mathrm{\ζ}\left(t\right)+\widetilde{\mathrm{\Ψ}}\left(t\right)\mathrm{\ξ}\left(t\right)---\left(12\right)$

In formula, $\widetilde{\mathrm{\Ψ}}\left(t\right)=\mathrm{\Ψ}\left(t\right)-{\mathrm{\Ψ}}^{*}.$

Then, the adaptive updates rule controlling matrix parameter is designed as

${\stackrel{\·}{\mathrm{\Θ}}}^T\left(t\right)=\frac{-S_p\mathrm{\ϵ}\left(t\right){\mathrm{\ζ}}^T\left(t\right)}{m^2\left(t\right)}---\left(13\right)$

$\stackrel{\·}{\mathrm{\Ψ}}\left(t\right)=\frac{-{\mathrm{\Γ\ϵ\ξ}}^T\left(t\right)}{m^2\left(t\right)}---\left(14\right)$

In formula, Γ=Γ^T＞ 0,

Correlation theory according to multivariate reference model adaptive control algorithm principle proves, it is known that this algorithm ensure that The boundedness of each variable of linear system, output can the output of asymptotic tracking reference model.

In order to verify that the Shipborne UAV auto landing on deck that the present invention proposes controls device effect, move with the longitudinal direction of certain unmanned plane As a example by mechanics and kinematics model, adding deck motion compensation last 10 second moment in reference trajectory, main simulation parameter sets Put such as table 1 below:

Table 1

Being verified by the numerical simulation under MATLAB software platform, result shows invented Shipborne UAV auto landing on deck Controlling device can make Shipborne UAV follow the tracks of downslide reference trajectory accurately, thus successfully completes warship task.

Claims (5)

1. a Shipborne UAV auto landing on deck based on model reference self-adapting control controls device, it is characterised in that this dress Put and include: warship instruction and downslide reference trajectory generation module, for according to position relative with Shipborne UAV, naval vessel and exhausted To positional information, generate three-dimensional downslide reference trajectory signal and speed command signal；

Model reference adaptive flight control modules, utilizes model reference self-adapting control algorithm to generate the flight of Shipborne UAV Control signal so that the practical flight track of Shipborne UAV and speed Tracking warship instruction and downslide reference trajectory generation module The three-dimensional downslide reference trajectory signal generated and speed command.

2. Shipborne UAV auto landing on deck controls device as claimed in claim 1, it is characterised in that model reference adaptive flies In control module, for the name of reference model is controlled Matrix Estimation valueK₂T () carries out the self adaptation of online updating more New law designs in accordance with the following methods and obtains:

Orderω (t)=[Δ x^T(t),Δr^T(t)]^T, Δ r is reference-input signal, Δ x be state to Amount, then output tracking error

E (t)=Δ y (t)-Δ y_m(t),

In formula, Δ y, Δ y_mThe system of being respectively output, reference model output；

Defining new error signal is

ε (t)=ξ_m(s) h (s) [e] (t)+Ψ (t) ξ (t),

In formula, h (s)=1/f (s), f (s) are Stable Polynomials, and Ψ (t) is Ψ^*=K_pEstimated value, K_pFor high-frequency gain square Battle array, ξ_mS () is the Interactive matrix of reference model, ξ (t)=Θ^T(t)ζ(t)-h(s)[Δu](t)；

Order

ζ (t)=h (s) [ω] (t),

The newest error signal is converted into

$\mathrm{\ϵ}\left(t\right)={\mathrm{\Ψ}}^{*}{\widetilde{\mathrm{\Θ}}}^T\mathrm{\ζ}\left(t\right)+\widetilde{\mathrm{\Ψ}}\left(t\right)\mathrm{\ξ}\left(t\right)$

In formula,

Then, the adaptive updates rule controlling matrix parameter is designed as:

${\stackrel{\·}{\mathrm{\Θ}}}^T\left(t\right)=\frac{-S_p\mathrm{\ϵ}\left(t\right){\mathrm{\ζ}}^T\left(t\right)}{m^2\left(t\right)}$

$\stackrel{\·}{\mathrm{\Ψ}}\left(t\right)=\frac{-{\mathrm{\Γ\ϵ\ξ}}^T\left(t\right)}{m^2\left(t\right)}$

In formula, Γ=Γ^T＞ 0,S_pFor reversible permanent matrix.

3. Shipborne UAV auto landing on deck controls device as claimed in claim 1, it is characterised in that model reference adaptive flies The input signal of control module includes: four longitudinal quantity of state flight speeds V of Shipborne UAV, angle of attack α, angle of pitch speed Rate q, pitching angle theta；Five horizontal stroke lateral quantity of state sideslip angle betas, roll angle speed p, yawrate r, roll angle φ, driftages Angle ψ；The speed command V of warship instruction and the output of downslide reference trajectory generation module_cAnd downslide reference trajectory signal X_EATDc(t), Y_EATDc(t),Z_EATDc(t)；

The output signal of model reference adaptive flight control modules includes: accelerator open degree Δ δ_T, elevator drift angle Δ δ_e, aileron Drift angle δ_a, rudder δ_r；

Flight Control Law in model reference adaptive flight control modules includes longitudinal and horizontal crabbing control law, by with Lower method is designed to:

The first step, based on following vertical linear model

$\left[\begin{array}{c}\mathrm{\Δ}\stackrel{\·}{V}\\ \mathrm{\Δ}\stackrel{\·}{\mathrm{\α}}\\ \mathrm{\Δ}\stackrel{\·}{q}\\ \mathrm{\Δ}\stackrel{\·}{\mathrm{\θ}}\\ \mathrm{\Δ}\stackrel{\·}{H}\end{array}\right]=A_{lon}\left[\begin{array}{c}\mathrm{\Δ}V\\ \mathrm{\Δ}\mathrm{\α}\\ \mathrm{\Δ}q\\ \mathrm{\Δ}\mathrm{\θ}\\ \mathrm{\Δ}H\end{array}\right]+B_{lon}\left[\begin{array}{c}{\mathrm{\Δ\δ}}_e\\ {\mathrm{\Δ\δ}}_T\end{array}\right]$

${\mathrm{\Δy}}_{lon}=C_{lon}{x}_{lon}=\left[\begin{array}{ccccc}1& 0& 0& 0& 0\\ 0& 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\Δ}V\\ \mathrm{\Δ}\mathrm{\α}\\ \mathrm{\Δ}q\\ \mathrm{\Δ}\mathrm{\θ}\\ \mathrm{\Δ}H\end{array}\right]$

Judge the relative order l of transfer function matrix_i, i=1,2, calculate high-frequency gain matrix

$K_p=\left[\begin{array}{c}{c}_{1,lon}{A}_{lon}^{l_1-1}{B}_{lon}\\ c_{2,lon}{A}_{lon}^{l_2-1}{B}_{lon}\end{array}\right]$

Ensure as nonsingular；In formula, A_lon、B_lon、C_lonThe vertical linear sytem matrix described for variable symbol, c_1,lon、c_2,lonPoint Wei C_lonThe 1st row and the 2nd row；

Second step, according to the relative order l of transfer function matrix_i, i=1,2, choose Interactive matrix Wherein p_1i,p_2iExpect limit for longitudinal system, thus design following reference model

Δy_m,lon(t)=W_m,lon(s)[Δr_lon](t)

In formula, Δ r_lon(t)=[0, Δ H_EATDc]^T,

3rd step, calculates Longitudinal Flight Control Law

$\left[\begin{array}{c}\mathrm{\Δ}{\mathrm{\δ}}_e\left(t\right)\\ \mathrm{\Δ}{\mathrm{\δ}}_T\left(t\right)\end{array}\right]=K_{1,lon}^T\left(t\right)\left[\begin{array}{c}\mathrm{\Δ}V\left(t\right)\\ \mathrm{\Δ}\mathrm{\α}\left(t\right)\\ \mathrm{\Δ}q\left(t\right)\\ \mathrm{\Δ}\mathrm{\θ}\left(t\right)\\ \mathrm{\Δ}H\left(t\right)\end{array}\right]+K_{2,lon}\left(t\right)\left[\begin{array}{c}0\\ \mathrm{\Δ}{H}_{EATDc}\left(t\right)\end{array}\right]$

Wherein,K_2,lonT () is the control matrix of online updating；

4th step, based on following horizontal lateral linear model

$\left[\begin{array}{c}\stackrel{\·}{\mathrm{\β}}\\ \stackrel{\·}{p}\\ \stackrel{\·}{r}\\ \stackrel{\·}{\mathrm{\φ}}\\ \stackrel{\·}{\mathrm{\ψ}}\\ \stackrel{\·}{y}\end{array}\right]=A_{lat}\left[\begin{array}{c}\mathrm{\β}\\ p\\ r\\ \mathrm{\φ}\\ \mathrm{\ψ}\\ y\end{array}\right]+B_{lat}\left[\begin{array}{c}{\mathrm{\δ}}_a\\ {\mathrm{\δ}}_r\end{array}\right]$

$y_{lat}=C_{lat}{x}_{lat}=\left[\begin{array}{cccccc}1& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\β}\\ p\\ r\\ \mathrm{\φ}\\ \mathrm{\ψ}\\ y\end{array}\right]$

Judge the relative order l of transfer function matrix_i, i=1,2, calculate high-frequency gain matrix

$K_p=\left[\begin{array}{c}{c}_{1,lat}{A}_{lat}^{l_1-1}{B}_{lat}\\ c_{2,lat}{a}_{lat}^{l_2-1}{B}_{lat}\end{array}\right]$

Ensure as nonsingular；In formula, A_lat、B_lat、C_latFor horizontal lateral linear sytem matrix, c_1,lat、c_2,latIt is respectively C_latThe 1st Row and the 2nd row；

5th step, according to the relative order l of transfer function matrix_i, i=1,2, choose Interactive matrixWherein p_1i,p_2iExpect limit for horizontal lateral system, thus design is following with reference to mould Type

y_m,lat(t)=W_m,lat(s)[r_lat](t)

In formula, r_lat(t)=[0, Y_EATDc]^T,

6th step, calculates horizontal crabbing control law

$\left[\begin{array}{c}{\mathrm{\δ}}_a\left(t\right)\\ {\mathrm{\δ}}_r\left(t\right)\end{array}\right]=K_{1,lat}^T\left(t\right)\left[\begin{array}{c}\mathrm{\β}\left(t\right)\\ p\left(t\right)\\ r\left(t\right)\\ \mathrm{\φ}\left(t\right)\\ \mathrm{\ψ}\left(t\right)\\ y\left(t\right)\end{array}\right]+K_{2,lat}\left(t\right)\left[\begin{array}{c}0\\ Y_{EATDc}\left(t\right)\end{array}\right]$

Wherein,K_2,latT () is the control matrix of online updating.

4. Shipborne UAV auto landing on deck controls device as claimed in claim 1, it is characterised in that warship instruction and downslide benchmark The input signal of Track Pick-up module includes: the azimuth (ψ of naval vessel runway or glide path_S+λ_ac), wherein ψ_SFor orientation, naval vessel Angle, λ_acFor angled deck angle；Warship instruction to include with the output signal of downslide reference trajectory generation module: speed command V_cAnd Downslide reference trajectory signal X_EATDc(t),Y_EATDc(t),Z_EATDc(t)。

5. Shipborne UAV auto landing on deck controls device as claimed in claim 4, it is characterised in that warship instruction and downslide benchmark Track Pick-up module makes formation speed instruction V using the following method_cAnd downslide reference trajectory signal X_EATDc(t)、Y_EATDc(t)、Z_EATDc (t):

After capture glide path, according to the known initial height-Z that glides_EA0, gliding angle γ_c, gliding speed V_c, calculate the warship time

$t_d=\frac{Z_0}{V_c{\mathrm{sin\γ}}_c}$

With glide path length

$R_A=V_c{t}_d=\frac{Z_{EA0}}{{\mathrm{sin\γ}}_c};$

Then calculate with the three-dimensional downslide reference trajectory under preferable the warship point earth axes as initial point:

$\left\{\begin{array}{c}{X}_{EATDc}\left(t\right)=V_c(t-t_d){\mathrm{cos\γ}}_{c}cos({\mathrm{\ψ}}_S+{\mathrm{\λ}}_{ac})\\ Y_{EATDc}\left(t\right)=V_c(t-t_d){\mathrm{cos\γ}}_c\sin ({\mathrm{\ψ}}_S+{\mathrm{\λ}}_{ac})\\ Z_{EATDc}\left(t\right)=-H_{EATDc}\left(t\right)=-V_c(t-t_d){\mathrm{sin\γ}}_c\end{array}\right..$