aeroelastic analysis and in- flight identification of … analysis and inflight ident… ·...

11

AEROELASTIC ANALYSIS AND IN-FLIGHT IDENTIFICATION OF THE

VECTOR- P UAV

David Fernando Castillo Zúñiga ([email protected])Jonatas Sant Anna Santos ([email protected])

Adolfo Gomes Marto ([email protected])Roberto Gil Annes da Silva([email protected])

Luiz Carlos Sandoval Góes ([email protected])

Instituto Tecnológico de Aeronáutica - ITA, Praça Marechal Eduardo Gomes 50, Vila das Acácias, 12228 – 900 São Paulo, Brasil.

LSALaboratório de Sistemas Aeronáuticos

22

Objectives

NUMERICAL AEROELASTIC ANALYSIS

IN-FLIGHT TEST

COMPARATION

CONCLUTIONS

Aeroelastic Analysis and Comparison with In-Flight Testing of the Vector- P UAV


33

Objetives

• Implementation of a Flight Dynamics Laboratory at ITA,with resources for determination of aerodynamiccharacteristics and aeroelastic behavior of an unmannedvehicle (UAV). Validation of aeroelastic flutter prediction.Validation of the aerodynamic model and application toin flight performance and flight control system.

• Present experimental results and coparison of anumerical aeroelastic analysis for Vector-P UAV taking amodal information as input.

• Comparison of Ground Vibration Test (GVT) with testresults obtained by operational modal analysis (OMA)after collected aeroelastic in-flight test.



INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

4Aeroelastic Analysis and Comparison with In-Flight Testing of the Vector- P UAV

Vector-P (Didatic Flight Plataform)

Wingspan 2.6 m

Fuselage Length 1.525 m

Max Speed 185 Km/hEngine 3 W 2-stroke reverse rotation gasoline engine.

Max Range 775 Km, depending on fuel on board

Cruise Speed 129 Km/h

Max Altitude 3 Km

Max Endurance 6 hours depending on fuel and payload on board

Max Takeoff Weight 34 Kg

Empty Weight 23 Kg

Max Fuel 12.3 liters

Fuel Per Hour 2.3 liters

Landing Speed 74 Km/h

Max Payload Weight 11.3 Kg, with fuel for one hour

Payload Vol. (Internal) (225 x 225 x 685) mm

The Vector-P is made mainly of composite material, with an almost square fuselage,wing flaps with no dihedral, two vertical stabilizers, horizontal tail and a tail boom


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

55

INTRODUÇÃO

FUNDAMENTAÇÃO TEÓRICA

METODOLOGIA

RESULTADOS

CONCLUSÕES


Identificação e Controle de um Veículo Aéreo Não Tripulado: Vector-P

Vector-P

UAVS

Telemaster

66

Vector-P FTILSA

Laboratório de Sistemas Aeronáuticos

INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Flight Test Instrumentation

1) PC-104 Anemometric Data Acquisition System (ICASIM)2) 4 channel pot interface (deflection control surfaces + throtle)3) AHRS Crossbow 400 (u, v, w, p, q, r, Euler angles)4) GPS antenna5) Four hole probe - data Boom (alpha, beta, Vtas, H)

77

Guidance & Navigation SystemLSALaboratório de Sistemas Aeronáuticos

INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Micropilot® Autopilot

Piloto automático MP2028g da MicroPilot®

• Mission prgramming• Groun station and comunication - plataform HORIZON• Autonomous flight (way points)• Flight simulation and HIL• AP control parameter tuning• in flight monitoring

MicroPilot® is a well known Canadian enterprise that produces AP for smal UAVs.

88

Micropilot Control LoopLSA


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES

Vector-P Control System

Autopilot Micropilot®

99

Vector-P System IdentificationLSA


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES

Vector-P Identification System

M4V OUTPUT-ERROR METHODOLOGY

1010

Vector-P System IdentificationLSALaboratório de Sistemas Aeronáuticos

INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Manouvers

1111


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Comparação de sinais de entradas no domínio da frequência

Input Power Spectral Density

1212


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES

Identification of the Vector-P

Manoeuver Tuning for Persistent Excitation

Doublet Multistep 3-2-1-1

ωn is the natural frequency (rad/s ) of the mode to be excited.

fC é the frequency (Hz) of the mode to be excited.

1313


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Ponta de prova anemométrica :• Até 100 Hz• Protocolo de comunicação RS-485• 10-18 V

Unidade Inercial AHRS-400CC-200• Tecnologia MEMs• Formato digital RS-232

Potenciômetros:Medição da deflexão das superfícies.

GPS 18x - Garmin:• Latitude, Longitude e Altitude• Velocidade Inercial• Taxa 5 Hz• Comunicação Serial

Compact-Rio: Sistema reconfigurável embarcado de aquisição e controle• Recebe e envia dados analógicos ,

digitais e seriais• Programação em LabView: FPGA e RT

Instrumentação

Atual do Vector-P

1414



INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Longitudinal Dynamic Model

1515


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Aerodynamic Model

Stability and Control Aerodynamic Derivatives

1616



INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Aircraft Model

Vetor de saída, estados e controle

Parâmetros desconhecidos

1717



INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Output Error Method

JATEGAONKAR, R. V., Flight Vehicle System Identification: A Time Domain Methodology, Progress in Astronautics and Aeronautics, Vol. 216, AIAA, Reston, VA, 2006.

Likelihood Cost Function

Covariance Matrix

1818


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Output Error Method

Gauss-Newton Algorithm

Hessian Matrix

Parameter up-date

Cost functionderivative

1919

Fundamentação TeóricaIdentificação de SistemasLSA


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


4Ms (Manobras, Métodos, Modelo e Medição)

Output Error Method

Algoritmo Heuristic Search

2020

ResultadosExperimentaisLSA


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Comparação entre dados de voo e resposta do modelo comparâmetros estimados ( , resposta computada; – – – –,dados de voo).

0 2 4 6-2

0

2

q mt(s)

0 2 4 6-0.5

0

0.5

ao

a1_m

t(s)

0 2 4 6-0.5

0

0.5

m

t(s)0 2 4 6

660

680

700

h m

t(s)

0 2 4 625

30

35

Vt_

m

t(s)

Processo de Identificação 1

2121


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 10 20 30 40 50 60 70 80 90-6000

-5500

-5000

-4500

-4000

Cos

t J(

)

Iteration i

Cost function evolution

Evolução da função custo


ResultadosExperimentais

2222


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 2 4 6 8-2

0

2

q mt(s)

0 2 4 6 8-0.5

0

0.5

ao

a1_m

t(s)

0 2 4 6 8-0.5

0

0.5 m

t(s)0 2 4 6 8

640

660

680

h m

t(s)

0 2 4 6 830

35

Vt_

m

t(s)




2323


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 10 20 30 40 50 60 70 80 90-6600

-6400

-6200

-6000

-5800

Cos

t J(

)

Iteration i





2424


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 5 10-1

0

1

q m

t(s)0 5 10

-0.5

0

0.5

ao

a1_m

t(s)

0 5 100

0.5

1 m

t(s)0 5 10

690

700

710

720

h m

t(s)

0 5 1025

30

35

Vt_

m

t(s)




2525


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 10 20 30 40 50 60-10000

-8000

-6000

-4000

-2000

Cos

t J(

)

Iteration i





2626


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 2 4 6 8-1

0

1

q m

t(s)0 2 4 6 8

-0.5

0

0.5

ao

a1_m

t(s)

0 2 4 6 80

0.5

1 m

t(s)0 2 4 6 8

710

720

730

740

h m

t(s)

0 2 4 6 825

30

35

Vt_

m

t(s)




2727


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


0 10 20 30 40 50 60-9000

-8000

-7000

-6000

-5000

Cos

t J(

)

Iteration i





2828


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES



Validação do Modelo

Parâmetros estimados e valor médio para validação do modelo

Validação do modelo identificado com valores da média dos parâmetros estimados

2929


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Teste de validação, comparação entre dados de voo e resposta do modeloidentificado ( , resposta computada; – – – –, dados de voo).

0 2 4 6 8-2

0

2

q m (r

ad/s

)

t(s)0 2 4 6 8

-0.5

0

0.5

ao

a1_m

(rad)

t(s)

0 2 4 6 8-0.5

0

0.5 m

(rad)

t(s)0 2 4 6 8

680

700

720

h m(m

)

t(s)

0 2 4 6 825

30

35

Vt_

m(m

/s)

t(s)



3030


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES




Acurácia Estatística dos Parâmetros Estimados:Critério Crámer-Rao bonds

Incertezas paramétricas

3131


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES




Análise de Resíduos: Critério Goodness of Fit

Incerteza das variáveis de saída

3232


INTRODUÇÃO


METODOLOGIA

RESULTADOS

CONCLUSÕES


Teste de Validação 2c11, dinâmica de período curto, análise da variável θ( , resposta computada; ––––, dados de voo ± tolerância)

0 1 2 3 4 5 6 7 8-0.2

0

0.2

0.4

0.6

m (r

ad)

t(s)

0 1 2 3 4 5 6 7 8-0.4

-0.2

0

0.2

0.4

p (r

ad)

t(s)



Tolerância de ±1,5°em θ especificada pela agência FAA

Processo de validação Proof-of-Match

3333

Determination of the Aeroelastic Characteristics of Vector-P


FEM

GVT

Aeroelastic Numerical Analysis

In-flight Testing

Wind Tunnel Testing

AeroelasticCharateristics


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

3434

Equação de Movimento AeroelásticaLSA


2∞ 0 2∞ 0

Q Φ G G Φ

2 1 ∞ 0

2

22

∞ 0

p-k method: Laplace adimentional parameter:

Φ

Φ Φ

Φ Φ

G-method : it has firts order damping terms . It generalizes k and p-k methods

K-method: artificial damping ig as stability measure:

Eingenvalue problem : force equilibrum of the aeroelastic system forces

∞

Aerodynamic generalized force matrix in modal domain

Dynamic pressure

displacements in function of modal matrix and generalized coordinates

Generalized mass matrix

Generalized stiffness matrix

Solution Methods


Obtained fromGTV

Obtained usingZAERO Software

INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

ASE method : aeroelastic system as states space system

3535

Numerical aeroelastic analysis: an eingenvalue problem


V-g-f & H-V diagrams


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

3636

GVT identified modal charateristics


Free-free suportMass configuration:31.5 kg


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

Mode Frequency (Hz) Damping (%)1st Symmetric Tail-Booms Bending Mode 7.56 1.45

1st Anti-symmetric Tail- Boom Bending Mode 8.67 2.02 1st Symmetric Wing Bending Mode 10.3 1.72

1st Anti-symmetric Wing Bending Mode 21.7 1.55 2nd Anti-symmetric Bending Mode 34.6 4.10 1st Anti-symmetric Torsional Mode 49.5 3.67

1st Symmetric Torsional Mode 55.2 4.32

Modal charateristics estimatedby Polymax method

3737

Aerodynamic representation using ZAERO

Cruciform838 elements

Flat plate with gap552 elements

Flat plate624 elements



INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

ZAERO uses ZONA 6 method: an unsteady finite element potential aerodynamic approach

Three different fusselage representation:

3838

“Spline” Method 2D & 3D

An interpolation surface iscreated by a least of 3 structural points

Interpolated vibration modes in aerodynamicdomain



INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

3939

Numerical aeroelastic analysis: solution parameters

Número Mach 0.1 Vmin [m/s] 0.50 Vmax [m/s] 1000

Frequências reduzidas 0.05; 0.08; 0.10; 0.11; 0.12; 0.14; 0.16; 0.18; 0.20; 0.25; 0.50; 0.75; 1.00; 1.20; 1.40; 2.00; 3.00; 4.00; 5.00

Altitude Densidade Nível do mar 1.225

1100 m 1.090 2000 m 1.004 3000 m 0.907

ASE: Foram usados 3 estados aerodinâmicos


• g and ASE methods


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

4040

Vf = 256.9 m/sFf =8.15 HzQf = 35.5 MPa

Mach: 0.1H= 1100 m

Main participation of the first 3 modes

V-g-f diagram


Outside of flightenvelope


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

4141

Flutter mode

Análise Aeroelástica e Comparação com Ensaio em Voo de uma Aeronave Não Tripulada


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS


Fuselage Representation Vf [m/s] Ff [Hz]

Cruciform 256.95 8.15 Flat Plate with gap 264.167 8.08

Flat Plate 252.99 8.23

Effect of the fusselage aerodynamic representation

Mach: 0.1H= 1100 m


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS


240 245 250 255 260 265 270 275 2800

500

1000

1500

2000

2500

3000

Velocity [m/s]

Alti

tude

[m]

g- Method ASE Method

FLUTTER

NOFLUTTER

g-method ASE Method Altitude Density (Kg/m3) Vf (m/s) ff (Hz) Vf (m/s) ff (Hz)Sea level 1.225 246.60 8.11 241.11 8.14 1100 m 1.090 256.95 8.15 251.98 8.18 2000 m 1.004 265.56 8.17 260.65 8.19 3000 m 0.907 277.23 8.18 271.95 8.21

Flutter velocity and its associated frequency increase with altitude growing

Effect of altitude


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

4444

Anemometer probe :• Bandwidth:100 Hz• Communication protocole RS-485• 10-18 V

Accelerometers DC-PCB• Mean senstivity :200 mV/g• Faixa linear : 10g• 5-20 V• Bandwidth: 100Hz

Compact-RIO:reconfigurableembedded control and acquisitionsystem• User-programmable FPGA

Inertial Unity AHRS-400CC-200MEMs TecnologyDigital Format RS-232

In-flight test: data acquisition system and accelerometers placement

GPS-Garmim



INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS


In-flight test manouvers and spectral parameters

Manouver: to keep fixed a flight condition, leaving the aircraft under atmospheric disturbance. The duration of each operation for a certain speed was set at 120 s.

Mass: 27 Kg

Velocity set: 25, 30, 35, 40, 45, 50 [m/s]

Vector-P flight envelope

• Max velocity : 51.4 m/s• Cruising velocity: 35.8 m/s

Sample Frequency Windows type Number of points Overlap

1000 hz Hanning 2100 50%

Spectral parameters: Welch method


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

46

Análise Modal Operacional (OMA)-Decomposição no domínio da Frequência (FDD)

∗

1

∗

∗

1

∗

∗

∗

∗

Assuming the input as a random signal with zero mean white noise distribution:

Relationship between input and output:

Partial function FRF expantion in terms of poles and residues :


GYYOnly output


Hermitian matrixDiagonal elements: APSD

Off-diagonal elements: CSPD

INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

47

Operational Modal Analysis(OMA)-Frequency Domain Deconposition(FDD)

Φ Σ Φ

Φ Φ

∗ ∗ ∗

∗

Σ 1,…… . ,

Φ 1 2 3 . . .

Considering a lightly damped model where the contribution of the model at a particular frequency is limited to a finite number:

Applying SVD technique for the above expression:

Modal shapes aproximattion.



INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS


0 5 10 15 20 25 30-40

-20

0

20

40

60

Frequência [Hz]

db[d

b[(m

/s2 )2 /H

Z]]

0 5 10 15 20 25 30-30

-20

-10

0

10

20

30

40

Frequêncy [Hz]

db[(m

/s2 )2 /H

Z]

50 m/s

45 m/s

40m/s

35 m/s

30 m/s

25 m/s

Main Singular Value

Second SingularValue

Two relevant peaks: Tail-booms bendindand Wing bending

Weak second singular values

FDA/OMA Singular Values


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS


-1.5

-1

-0.5

0 -1.5-1

-0.50

0.51

1.5

-0.5

0

0.5

Y [m]X [m]

-1.5

-1

-0.5

0 -1,5-1,0

-0,50

0,51.0

1,5

-1

0

1

Y [m]

X [m]

Wing bendingTail-booms bending

OMA identified modes

1st Symmetric Tail-Booms Bending 1st Wing Bending Velocity (m/s) Frequency [Hz] Damping (%) Frequency [Hz] Damping (%)

50 9.28 - 12.21 - 45 9.28 - 12.45 4.47 40 9.28 5.05 12.45 4.02 35 9.28 5.39 12.69 4.34 30 9.28 5.05 12.45 4.77 25 9.03 4.58 12.21 4.93


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

50

Comparison between numerical and experimental aeroelastic approaches


Offset by different test mass

distribution.

No significativevariations with

velocity

Offset by inherentstrutural damping


INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

51

Vector-P in its actual configuration is not flexible enough to carryaeroelastic studies. It was only marginally possible to characterizeaeroelastically the Vector-P flight envelope. The characterizationwas done by means of an aeroelastic numerical analysis based inexperimental modal information (GVT), and compared with flighttest/OMA using only the modal responses of the system. Thetrends of the modal frequencies as a function of velocity predictednumerically were validated with OMA results. It was found thatthere are aeroelastic instabilities in the Vector-P flight envelope.

The FDD/OMA technique proved to be very useful for identificationof resonant frequencies given the ability to point to the modes thatdominate in specific frequency. It was observed limitations in theestimation of modal damping and therefore it is advisable toestimate this parameter with other techniques (ex., EFDD-Enhanced Frequency Domain decomposition).

Conclusions



INTRODUTION


IN-FLIGHTTEST

COMPARATION

CONCLUTIONS

52

Acknowlegdements

• This work was supported in part by CNPq-Conselho Nacional deDesenvolvimento Científico e Tecnológico – Brazil.

• The authors of this paper acknowledges the partial support from theInstituto Nacional de Ciência e Tecnologia - Estruturas Inteligentes emEngenharia, INCT-EIE.

• The Authors would like to acknowledge Professor Airton NabarretePh.D., Eng. Jany Lima, Eng. Jonatas Sant´Anna M. Sc. and all whocontributed in some way for this work.



53

References

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• Castillo Zúñiga, D. F., 2009. “Subsonic Wing Aircraft FlutterAnalysis ”. Degree Final Work (Mechanical Engineering) -Universidad del Valle, Cali, Colombia.

• Castillo Zúñiga, D. F. and Góes, L. C. S., 2012. “Modal Testing of the Vector-P Unmanned Aerial Vehicle” . InProccedings of the 7th Brazilian Congress of Mechanical Enginnering - CONEM2012. São Luiz de Maranhão, Brazil.

• Castillo Zúñiga, D. F.,1981 “Aeroelastic Analysis and Comparison with In-Flight Testing of Unmanned aerial Vehicles”.Master thesis (Flight Mechanics and Control) - Instituto Tecnologico de Aeronáutica, São Jose dos Campos, Brazil.

• Follador, R.., De Souza, C. E., Marto, A. G., Da Silva, R. G. A. and Góes, L. C. S., 2009. “Comparison of in-fligthmeasured and computed aeroelastic damping: modal identification procedures and modeling approaches”. InProccedings of the International Forum On Aeroelasticity And Structural Dynamics - IFASD2009, Seattle, USA.

• Kitahara, W. T.,1981. “Medium aircraft in-Flight flutter testing”. Final degree work (Aeronautic Engineering) -Instituto Tecnologico de Aeronáutica, São Jose dos Caampos, Brazil.

• Mastroddi, F., Coppotelli, G. and Cantella, A., 2010. “Aeroelastic identification of a flying UAVs by output only datawith applications on vibration passive control”. In Proccedings of the 51st AIAA/ASME/ASCE/AHS/ASC Structures,Structural Dynamics And Materials Conference. Orlando, USA.

• Peña, D. C. B., Góes, L. C. S., Santos, J. S. and Guzman, L. E. S., 2011. “Implementation and validation of amicropilot control system for Vector-P aircraft in flight level”. In Proccedings of the 9st Latin American RoboticsSymposium, And Ieee Colombian Conference On Automatic Control. Bogota, Colombia.

• Suzus, U., 2008. “Aeroelastic analysis of an unmanned aerial vehicle”. Thesis (M.Sc in Mechanical Engineering) -Middle East Tecnhical University, Ankara.

• Weisshaar, A. T., Nam, C. and Batista Rodriguez, A., 1998. “Aeroelastic tailoring for improved UAV performance”. InProccedings of the 39st AIAA Structures, Structural Dynamics, And Materials Conference. Long Beach, USA.

• Weissharr, T. A., 2001. “Aeroelasticity's role in innovative UAV design and optimization—the way things ought to be”.In Proccedings of the 41st Annual Israel Conference On Aerospace Sciences. Tel Aviv and Haifa, Israel.

• ZONA Technology. ZAERO theoretical manual. Scottsdale, 2008.



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