final presentation of a. falcoz phd activities: march 16-09 – esa/estec

46
1/44 Laboratoire de l’Intégration du Matériau au Système IMS - UMR 5131 CNRS – Département LAPS Université Bordeaux I http://www.laps.u-bordeaux1.fr/aria - Phd student: Alexandre Falcoz - Academical supervisors: - Dr. David Henry (HDR) - Pr. Ali Zolghadri - Industrial supervisors: - Eric Bornschlegl (ESA / ESTEC) - Martine Ganet (EADS Astrium) P P A A S S L L ARIA ARIA On the design of a robust model-based On the design of a robust model-based fault diagnosis unit fault diagnosis unit for Reusable Launch Vehicles for Reusable Launch Vehicles Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC [email protected]

Upload: maj

Post on 02-Feb-2016

34 views

Category:

Documents


2 download

DESCRIPTION

L. A. P. S. Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC. Laboratoire de l’Intégration du Matériau au Système IMS - UMR 5131 CNRS – Département LAPS Université Bordeaux I. http://www.laps.u-bordeaux1.fr/aria. ARIA. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

1/44

Laboratoire de l’Intégration du Matériau au SystèmeIMS - UMR 5131 CNRS – Département LAPS

Université Bordeaux I http://www.laps.u-bordeaux1.fr/aria

- Phd student: Alexandre Falcoz

- Academical supervisors: - Dr. David Henry (HDR) - Pr. Ali Zolghadri

- Industrial supervisors: - Eric Bornschlegl (ESA / ESTEC) - Martine Ganet (EADS Astrium)

PPAA SSLLARIAARIA

On the design of a robust model-based On the design of a robust model-based fault diagnosis unitfault diagnosis unit

for Reusable Launch Vehiclesfor Reusable Launch Vehicles

Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

[email protected]

Page 2: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

2/44

• Statement of the problem

- RLV mission presentation – faulty situations,- RLV mission presentation – faulty situations,- Why model-based fault diagnosis??- Why model-based fault diagnosis??- requirements of the fault diagnosis unit, - requirements of the fault diagnosis unit,

• Diagnosis of the RLV actuator faults

. . Auto-landing phase

- modelling of the HL-20 dynamics - modelling of the HL-20 dynamics - formulation of the fault diagnosis problem : H- formulation of the fault diagnosis problem : H ∞ ∞ /H/H- - settingsetting

- post-analysis of the results - experimental results,- post-analysis of the results - experimental results,

. . TAEM Phase Some new results Some new results

- a more sophisticated GNC and modelling process- a more sophisticated GNC and modelling process- design – robust performances – simulation results- design – robust performances – simulation results

• Faults characterizationFaults characterization

- methodology description,- methodology description,- simulation results,- simulation results,

OUTLINE

Page 3: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

3/44

Statement of the problem

Page 4: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

4/44

Runway

Yrunway

Xrunway

Orbiter ground track

TEP

HAC radius

NEP

Hypersonic phase

Zrunway

TAEM phase

Autolanding phase

Injection point

Splitted into 3 successive paths:

120 km Mach 2 hypersonic

Mach 2 Mach 0.5 TAEM

Mach 0.5 touch-down Landing

Earth Horizon

Atmospheric re-entry presentation

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Page 5: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

5/44

Begin Begin constant “G”constant “G”

pulluppullup

InterceptInterceptinner glideslopeinner glideslope

RunwayRunway

Runway plane

Inner glideslopeInner glideslopeflight path angleflight path angle

RunwayRunwaythresholdthreshold

Constant “G”Pullup maneuver

ExtendedExtendedParabolicParabolictrajectorytrajectory

AimpointAimpoint

TouchdownTouchdown

FinalFinal flareflare

Outer Glideslope Outer Glideslope flight path angleflight path angle

Autolanding Autolanding handoverhandover HL-20HL-20

Auto-Landing path characterized by:

Restricted operating flight envelope (True air speed, Mach-AOA trim map,…),

Fault occurrence prominent risk of stall

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Atmospheric re-entry presentation

Page 6: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

6/44

Why model-based fault-diagnosis?

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

global optimization of the spacecraft/aircraft design programs:

. Reduction of the in placed hardware redundancy

reduction of the maintenance costs and times,

reduction of the vehicles empty mass: . aeronautic applications: operating cost reduction (airline price ticket?? )

. space applications: increase of the orbital payload (for launcher) satellite cycle life.

decrease of the mission costs

because sometimes we have not the choice:

Military UAV applications with stringent weight constraints:

actuators and sensors reduced to the bare necessities ,

no hardware/software redundancy to diagnose and recover faulty situations Model-based FDI/FTC techniques appear to

be an attractive solution.

Mass

autonomy

Mod

el-b

ased

FDIR

FDIR

/ ha

rdaw

re

dup

licat

ion

Model-based algorithms:

Why? «mass free and non intrusive Intelligent sensors »

How?data fusion of already available measurements for the design of residual generators (activities similar to control design process) resulting in a software FDI filter

Great Advantages: Perturbations/uncertainties modelling

Possibility to distinguish between faults and various operating conditions

Page 7: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

7/44

To be a potential candidate: TheTo be a potential candidate: The fault diagnosis strategy must fault diagnosis strategy must meet the following requirements:meet the following requirements:

non detection and false alarms rates must be extremely rare (ideally zero), whilst guaranteeing, at the same time, a large fault coverage with a low detection time delay,

- exogeneous disturbances: wind gusts, turbulences, measurement noises,

guidance signals,

- endogeneous disturbances: innacurate knowledge of the vehicle parameters (mass, Center-of-

gravity, inertia, aerodynamic coefficients)

the performances must be guaranteed over the whole vehicle flight trajectory

Two different way: Monte-Carlo simulations Generalized structured singular value

Robustness constraints to be met:

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Requirements of the fault diagnosis unit

-Systematic post-analysis procedure

- Mathematical proof of the robust performances (CNS!)

- provide the worst combination of the considered uncertainty parameters!

bridge exists: if -tests fails then Monte Carlo tests fails also!!

Advantage: - test is less time consuming

- Probabilistic proof of robust performances,

- How many simulations are needed to ensure

that the worst combination has been drawed?

analysis must be understood as a powerful tool for:

1: the a posteriori checkout of the FDI/controller robust performances

2: a driving lines fo the synthesis!!

3: a driving lines for ‘targeted’’ Monte

Carlo analysis

g/

Page 8: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

8/44

Diagnosis of the HL20 actuator faults- Application to the auto-landing phase  -

– Modelling

– Problem setting

– Solution of the problem

– Experimental results

Page 9: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

9/44

Residual generators

Decision

making

Faulty actuator

Nonlinear estimation

General overview of the Faut Detection Isolation and Identification architecture uncertainties

Navigation

Path

planner

Guidance loop Flight controllerVehicle dynamics

FDIR

Requirements of the fault diagnosis unit

Page 10: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

10/44

Actuator faulty situations- selection and modelling -

Page 11: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

11/44

HL-20 modelling

Vehicle dynamics:

Hypothesis:

• Non-rotative and flat earth:

• RCS not used during the landing phase:

• Inertia matrix assumed to be constant and diagonal:

with:

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Page 12: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

12/44

Modélisation du HL20: coefficients aérodynamiques (1/3)

• Strored into Simulink look up tables,• need to derive an analytical model

Page 13: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

13/44

Aerodynamic coefficients in “clean configuration”

• 2-Dimensional mapping using SVD decomposition

with:

modelling error

HL-20 modelling: Aerodynamic coefficients (1/2)

with:

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Page 14: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

14/44

Aerodynamic components linked to the aero-surfaces deflections and body angular rates:

• polynomial interpolation

• sensitivity analysis of the modelling errors

Integration of the modelling errors:

Approximation error

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

HL-20 modelling: Aerodynamic coefficients (2/2)

Page 15: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

15/44

with:

Nonlinear representation of the HL20 dynamics:

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

HL-20 modelling

(1)

Page 16: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

16/44

Question: Do the remaining healthy control effectors are able to maintain the vehicle control following an actuator fault?

Consider the model given by equation (1). The problem of finding a non-saturated control input combination which ensures the static equilibrium of the vehicle around its center-of-gravity can be formulated according to the following minimization problem:

Problem formulation:

Selection of the faulty scenarios to be studied: non-destabilizing faults!!

Impact of faults on the system

Page 17: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

17/44

Fault free situation Faulty situation:

Faulty situation:

free -30° -15° 0° 15° 30°

free

-30°

-15°

15°

30°

Impact of faults on the system

Page 18: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

18/44

Diagnosis filters synthesis

Page 19: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

19/44

Faults impact modelling –Left and right wing flaps faults *

1 – abnormal behavior of the control signals:

2 –abnormal variation of the aerodynamic coefficients due to the GNC performance level: depends on the use GNC

Modelling

Ex 2: runaway of the ith actuator:

Abnorrmal variation following a faultAbnorrmal variation following a fault

* Faults which satisfy the trimmability conditions

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Ex 1: jamming of the ith actuator:

Landing phaseTAEM phase

Page 20: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

20/44

Polynomial function depending on the reference flight velocity: i.e.

Linearization around the reference flight trajectory:

hypothesis: slow variation of the reference flight velocity during the Auto-landing phase

LPV LTI (uncertain)

Modelling

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Page 21: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

21/44

Procedure: Open-loop frequency domain (principal gain) and time domain (poles) analysis depending on :

Modelling

Model:

A posteriori checkout of the LTI hypothesis

Can we use an appropriated, single and simplified model for the design of the fault diagnosis algorithm?

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Page 22: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

22/44

Formulation and resolution of the fault diagnosis design problem

Page 23: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

23/44

++--

++

++

FiP

KyM

uM

)M,M(P uiyi2

F

Generate a residuals vector such as:

robust against exogeneous disturbances robust against exogeneous disturbances (measurement noises, winds, guidance signals)(measurement noises, winds, guidance signals)

sensitive wrt faults to detect sensitive wrt faults to detect

guarantying robust performances for all the considered guarantying robust performances for all the considered uncertainties uncertainties (mass, inertia, aerodynamic coefficients,…)(mass, inertia, aerodynamic coefficients,…)

context

context

Looking for an optimal static combination of all available Looking for an optimal static combination of all available measurements (i.e. compute measurements (i.e. compute My, Mu) My, Mu) andand a dynamic filtera dynamic filter F F for filtering for filtering purpose to make r:purpose to make r:

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Formulation of the fault diagnosis problem

Page 24: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

24/44

Let be a stable and invertible dynamic filter associated to the sensitivity objectives such as:

Let be a stable and invertible dynamic filter associated to the robustness objectives such as:

with:with:

Synthesis objectives formulation: ‘’shaping filters’’

Robustness objectives:

Sensitivity objectives :

SDP problem in My, Mu, AF,BF,CF,DFSDP problem in My, Mu, AF,BF,CF,DF

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Formulation of the fault diagnosis problem

(D. Henry & A. Zolghadri, 2005):

Page 25: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

25/44

)s(P

)s(

Performances post-analysis

sufficient condition in the synthesis process is not taken into account during the synthesis procedure: an a priori choice for reduced FDI filters (less time and consuming FDI algorithms) A posteriori checkout of the LTI hypothesis

Do the robustness requirements against d and sensitivity objectives w.r.t f are fulfilled and all along the flight trajectory? Generalized structured singular value

)(sF

)(sK

1fW

1dW

Let consider the scheme of Fig (b). Let and two fictitious uncertainty blocks introduced to close the loop between respectively d and r and f and r. Let then, the robustness and sensitivity objectives are achieved iff:

Theorem (D. Henry & A. Zolghadri, 2005):

yM

uM

)s(d

)s(f

)(sN

Fig.b

df

Maximisation part

Minimisation part

Page 26: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

26/44

Evaluation of for different vehicle flight velocities along the reference flight trajectory taking into account the uncertainties (i.e. a robust performances analysis test for for FDI algorithm generalized to any LTI FDI algorithm, see (Henry 2007)

achievement of the robustness/sensitivity objectives w.r.t the considered exogeneous disturbances vector and model uncertainties,

The diagnosis filter performances are guaranteed all along the flight trajectory, i.e

Filters order: 9

Performances post-analysis

every 2 m/s 30 LFT

Page 27: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

27/44

Temporal simulations

Page 28: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

28/44

Temporal simulations: 300 Monte-Carlo runs

• implementation of the two dedicated diagnosis filters into the simulator,• implementation of a Wald sequential test for the decision making issue:

- False alarm probability:- Non detection probability:

Temporal simulations

Page 29: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

29/44

Fault on the Left wing flap: 300 Monte-Carlo runs

Temporal simulations

Fault on the Right wing flap: 300 Monte-Carlo runs

Page 30: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

30/44

Diagnosis of the HL20 actuator faults- Application to the TAEM phase  -

– Aerodynamics modelling

– Problem setting - preliminary

Page 31: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

31/44

Residual generatorsDecision

making

Faulty actuator

Position control loop

FDI

Path

planner

Position control loop

Attitude control loop

Allocation

GNC

uncertainties

Navigation

Vehicle dynamics

-

-

- -

Outer loop

-

-

Inner loop

+

Position control loop algorithm

TAEM GNC/FDIR architecture

Page 32: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

32/44

Residual generatorsDecision

making

Faulty actuator

Attitude Control loop

FDI

Path

planner

Position control loop

Attitude control loop

Allocation

GNC

uncertainties

Navigation

Vehicle dynamics

-

-

+ +

Outer loop

-

-

Inner loop

-

s

)(IK ref1

Attitude control loop algorithm

TAEM GNC/FDIR architecture

Page 33: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

33/44

Residual generators

Decision

making

Faulty actuator

Allocation Algorithm

FDI

Path

planner

Position control loop

Attitude control loop

Allocation

GNC

uncertainties

Navigation

Vehicle dynamics

On-line Allocation algorithm

1

2

Analytical model of the aerodynamic coefficients use of Neural Network

Vector coming from Guidance & Control loops

Off-line precomputed and parameterized w.r.t to the dynamic pressure Previous control input vector

TAEM GNC/FDIR architecture

Page 34: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

34/44

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Robust stability analysis of the GNC architecture

Evaluation the GNC robust performances for the considered parameter uncertainties and all along the reference flight trajectory: every 10 m/s 40 LFT

Does the closed-loop system remains stable for all values of in the considered variation range?

)s(M i

i

)s(Pi

i

)s(K i

Robust stability of the designed GNC is “guaranteed” all along the flight trajectory

Page 35: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

35/44

Aerodynamic database modelling

Aerodynamic coefficients modelling by means of neural network:

Two kind of nonlinear dependency:

1: Terms having a nonlinear dependency wrt to the mach number and

number of neurons in the hidden layer

number of inputs

Hidden layer Outer layer

2: Terms having a nonlinear dependency wrt to the mach number, and

Page 36: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

36/44

2 dimensional aerodynamic terms: clean configuration

3 dimensional aerodynamic terms linked to the actuator components

Aerodynamic database modelling

Page 37: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

37/44

Extraction of a ‘judicious’ certain LTI model of the vehicle dynamics:

Objective design formulation:

Fault diagnosis problem formulation and resolution of the SDP problem

Post-analysis – analysis procedure)s(N i

id

f

1

2

3

4Gridding of the flight trajectory

every 5 m/s so that:

LFT

Formulation of the fault diagnosis problem

Page 38: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

38/44

Evaluation of for different vehicle flight velocities along the reference flight trajectory

achievement of the robustness/sensitivity objectives w.r.t the considered exogeneous disturbances vector and model uncertainties,

The diagnosis filter performances are guaranteed all along the flight trajectory, i.e

Performances post-analysis

every 5 m/s 80 LFT

Page 39: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

39/44

Some preliminary results……in detection

Temporal simulations

Some a posteriori important conclusion about the “TAEM feasibility” study:

A need of modelling more accurately the faults impact Isolation task is not performed at this

time! The LTI technique seems to be appropriated ( -test reveals robust performances)

Jamming of the left wing flapRunaway of the left wing flap

Page 40: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

40/44

Actuator faults characterisation

Page 41: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

41/44

Faults estimation

Nonlinear state-space model used for the estimation process:

with:

et denote respectively the process and measurements noises which are assumed to be uncorrelated white noise processes with covariance matrices Q et R such as:

Objective: Estimate the position of the unknown inputs using the following nonlinear observer-scheme:• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Page 42: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

42/44

Particle Swarm Optimization algorithm (James Kennedy and Russell Eberhart)

Integrated in the class of evolutionary algorithms and very efficient to deal with multi-parameters, non-linear and discrete-type optimization problems,

Algorithm quite easy to understand, to code and to use.

Problematic: Optimization of the EKF-based estimator parameters, i.e. Q and R

Off-line Minimization of the root mean square of the state estimate errors

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

Faults estimation

Considered methodology:

Page 43: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

43/44

Simulation results

Right wing flap jamming Left wing flap runaway

Page 44: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

44/44

Conclusion Fault Detection and Isolation of the HL20 actuator

Design of two diagnosis filters of order 9 for Fault detection and isolation during AL phasePerformances analysis of the filters using the function along the flight trajectory

Faulty situations determined following a trimmability deficiency analysis

Estimation of the faulty deflections once the FDI task has been achieved

EKF-based estimator (DD1 filter)

• Statement of Atmospheric

re-entry problem

• Faulty scenarios

• Diagnosis of the HL-20

actuators

• Conclusion & perspectives

IF it is very carefully chosen: A single LTI model is sufficient to deal with the FDI task during the A-L and TAEM phases

LPV techniques have not to be excluded!! But a trade-off between the design complexity, the onboard computational burden and the FDI performances must be studied.

Page 45: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

45/44

Thanks for your attention

Page 46: Final Presentation of A. Falcoz Phd activities: March 16-09 – ESA/ESTEC

46/44

Residual generators

Decision

making

Faulty actuator

Nonlinear estimation

General overview of the Faut Detection Isolation and Identification architecture uncertainties

Navigation

Path

planner

Guidance loop Flight controllerVehicle dynamics

FDIR

Requirements of the fault diagnosis unit