a computer based autorotation trainer edward bachelder, ph.d. bimal l. aponso dongchan lee, ph.d....

A COMPUTER BASED AUTOROTATION TRAINER

Edward Bachelder, Ph.D.Bimal L. Aponso

Dongchan Lee, Ph.D.

Systems Technology, Inc.Hawthorne, CA

Presented at:

2005 International Helicopter Safety SymposiumSeptember 26-29, 2005, Montreal, Quebec, Canada

26-29 September 2005 2005 IHSS, Montreal, Canada 2

OVERVIEW

Motivation and concept

Technical approach

Testing and validation

Example autorotations

Computer Based Autorotation Trainer concept


MOTIVATION

For a safe outcome, helicopter autorotation requires precise and time-critical maneuvering in multiple axes.

Consequences of inappropriate timing and magnitude of control inputs can be fatal.

An autorotation trainer that could demonstrate proper control technique would be beneficial for pilot training and safety.

An autorotation trainer should allow pilots to preview and rehearse autorotations from entry conditions throughout the flight envelope.


AUTOROTATION SEQUENCE(Entry from Hover)

b.

c. d.

a.

a.) Entry b.) Stabilization c.) Maximum Flare d.) Touchdown.


THE HUMAN ELEMENT

Humans prefer to operate linear, decoupled systems to nonlinear, coupled systems Human improvisation to unfamiliar conditions is relatively

easy

Human response is:

1. More repeatable

2. Less prone to operator noise


THE HUMAN ELEMENT

Helicopter dynamics during autorotation are highly nonlinear and coupled

Nonlinear examples:

1. Lift vs rotor speed

2. Lift vs airspeed

Coupling examples:

1. Rotor speed and airspeed both affect lift

2. Collective affects rotor speed, cyclic both airspeed and rotorspeed

Scanning technique critical for coordinating proper controls sequence During glide: Airspeed, Nr, ball, radalt

In flare: Nr, pitch, radalt


AUTOROTATION:IT’S LIKE HERDING CATS


TECHNICAL APPROACH:THE “OPTIMAL PILOT” CONCEPT

Apply optimal control theory to compute optimal trajectories and control inputs required for safe autorotation or one-engine inoperative (OEI) situations – the Optimal Pilot.

The Optimal Pilot will demonstrate autorotation trajectories over a broad range of initial and final conditions and rotorcraft configurations.

Visually integrate and display optimal inputs with the helicopter’s critical states and outside (OTW) view to provide a “sight picture.”

Preview and practice autorotations in a flight simulator using a Flight Director type display to advise the pilot of the optimal control inputs.


TECHNICAL APPROACH:OPTIMIZATION METHOD

Two-point boundary value problem – minimize objective (cost) function.

Transformation to parameter optimization problem using Direct-Collocation.

Continuous solution discretized in time using “nodes.”

Rotorcraft equations-of-motion and other non-linear constraints applied at each node.

Parameter optimization problem was solved using a commercially available Sequential Quadratic Programming (SQP) algorithm -- SNOPT

SNOPT is very well suited for near real-time generation of control commands, exhibiting stable and robust behavior for numerous entry conditions and roughly-estimated starting trajectories.


TECHNICAL APPROACH:PROBLEM FORMULATION

Cost function includes: Sink-rate and forward speed at touchdown

Desired touchdown distance or flight time minimization (for OEI situation only)

Weightings on penalty terms were tuned to provide robust solutions across a wide range of autorotation entry conditions.

Longitudinal only, controls were collective and pitch attitude.

Constraints: Rotorcraft equations-of-motion (represented by non-linear point-mass model).

Rotor speed overspeed and droop limits.

Pitch and collective control limits.

Maximum achievable sink rate.

Maximum pitch rate

Touchdown pitch attitude (to prevent tail strike)


TECHNICAL APPROACH:INTEGRATED DISPLAY & FLIGHT DIRECTOR


TRAINING METHOD

Compensatory tracking

Compensatory tracking with feedforward cues

Precognitive


TESTING & VALIDATION:REAL-TIME IMPLEMENTATION


TESTING & VALIDATION:FLIGHT TRAINING DEVICE

Testing performed on a fixed-base FTD by Frasca International.

Wide field-of-view visual display.

High-fidelity cockpit controls and instrument panel.

Simulated helicopter was a Bell-206L-4.

Rotorcraft mathematical model with adequate fidelity for pilot training throughout the flight envelope including autorotation.

FAA approved under 14 CFR Parts 61 and 141.


TESTING & VALIDATION:DEVELOPMENT PROCESS

Point-mass model parameters were identified to match the flight simulation model during autorotation. Primarily scaling of pitch and collective from optimal solution to

longitudinal cyclic and collective on the simulator.

Validated using fully-coupled autorotations A flare law was added to take over from optimal guidance during final

flare and landing.

Simple lateral feedback control system was implemented to maintain heading and roll attitude.


TESTING & VALIDATION:EVALUATION METHOD

Optimizer continuously updates optimal solution based on rotorcraft states obtained from simulator.

Update is stopped when engine is failed.

Procedure: Fly to required entry condition.

Stabilize and wait for a stable optimal solution.

Fail engine and enter automated autorotation.

Autorotation trajectory flown is based on the solution just prior to engine failure.

Safe or crash landing determined by the FTD simulation model.


TESTING & VALIDATION:EVALUATED ENTRY CONDITIONS

600

550

500

450

400

350

300

250

200

150

100100

90

80

70

60

50

40

30

20

10

00 10 20 30 40 50 60 70 80 130

Indicated Airspeed (kts)

Ski

d H

eig

ht A

bove

Su

rfac

e (f

t)

Ski

d H

eig

ht A

bov

e S

urfa

ce (

ft)

4150 lbsand below

AVOID OPERATION INSIDEBOUNDARY LINES

Above 4150 lbs to 4450 lbs

4150 lbs and below

Light WeightMedium WeightHeavy Weight

(sm

all s

cale

)

(larg

e sc

ale)


TESTING & VALIDATION:FULLY-COUPLED AUTOROTATIONS

(400 Ft and 100 Ft Hover Entry)


TESTING & VALIDATION:CONCLUSIONS

Optimal pilot concept was validated on the Frasca FTD.

Optimal guidance allowed safe autorotation from well within the “avoid” regions of the Height-Velocity envelope.

Ability to train a pilot on autorotation technique using the flight director display was also demonstrated (results presented at AHS Forum 61, Grapevine, TX).

Incorporate Optimal Pilot concept in a CBT to allow pilots to preview autorotations.


COMPUTER BASED AUTOROTATION TRAINER:EXAMPLE AUTOROTATIONS

Autorotations flown by the optimal pilot (optimal commands are coupled to rotorcraft controls).

Show “extreme” entry conditions to illustrate the effectiveness of the concept.

Time history data: altitude (H, ft), airspeed (V, kts), pitch attitude (, degrees), vertical velocity (w, fpm), rotor speed (, %), collective (c, %).

Bell 206 Model; Power failure at time = 0.

Video clips show OTW sight picture and optimal pitch attitude/collective commands.


AUTOROTATION CBT:CONTROL INPUT PREVIEW

Example cueing display for an autorotation from a 200ft hover entry

Pitch attitude preview on right, collective on left.

Tick marks show 1 second time intervals.

Pitch attitude cue indicates immediate pitch down followed by a steep pitch up with a final nose-over to avoid tail strike.

Collective cueing indicates immediate lowering of collective with collective pull at the end of the maneuver.


EXAMPLE AUTOROTATIONS:ENTRY CONDITIONS

H-V flight envelope shows “avoid” regions for Bell 206L-4.

Example autorotations shown for:

Heavy weight (4500 lbs), 400 ft hover entry (within avoid region).

Heavy weight (4500 lbs), 80 ft/60 kts entry (knee point of avoid region).

Medium weight (3600 lbs), 200 ft hover entry (within avoid region).

Medium weight (3600 lbs), 20 ft/40 kts entry (outside avoid region).

600

550

500

450

400

350

300

250

200

150

100100

90

80

70

60

50

40

30

20

10

00 10 20 30 40 50 60 70 80 130

Indicated Airspeed (kts)

Ski

d H

eigh

t Abo

ve S

urfa

ce (

ft)

Ski

d H

eigh

t Abo

ve S

urfa

ce (

ft)

4150 lbsand

below

AVOID OPERATION INSIDEBOUNDARY

LINES

Above 4150 lbs to 4450 lbs

4150 lbs and below

Medium Weight

Heavy Weight

(sm

all

sca

le)

(larg

e sc

ale

)


EXAMPLE AUTOROTATION TIME HISTORY(HEAVY WEIGHT, 400 FT HOVER ENTRY)

(Touchdown: 18 kts, 248 fpm)


EXAMPLE AUTOROTATION VIDEO(HEAVY WEIGHT, 400 FT HOVER ENTRY)



EXAMPLE AUTOROTATION TIME HISTORY(HEAVY WEIGHT, 80 FT/60 KT ENTRY)



EXAMPLE AUTOROTATION VIDEO (HEAVY WEIGHT, 80FT/60KT ENTRY)



EXAMPLE AUTOROTATION TIME HISTORY(MEDIUM WEIGHT, 200 FT HOVER ENTRY)



EXAMPLE AUTOROTATION VIDEO (MEDIUM WEIGHT, 200 FT HOVER ENTRY)



EXAMPLE AUTOROTATION TIME HISTORY(MEDIUM WEIGHT, 20FT/40KT ENTRY)



EXAMPLE AUTOROTATION VIDEO (MEDIUM WEIGHT, 20FT/40KT ENTRY)



AUTOROTATION CBT CONCEPT Objectives:

Provide pilots with a preview of the control inputs and trajectory required for safe autorotation from entry conditions across the flight envelope.

Provide pilots with an OTW sight picture of the autorotation.

Allow pilots to rehearse autorotations in an interactive environment.

CBT configuration: Preset rotorcraft model parameters (for specific rotorcraft) or allow user to setup the

rotorcraft model.

User sets up entry flight condition (speed, altitude, weight, wind, etc).

Allow user to adjust cost and constraint parameters (allowable rotor droop, for example)?

CBT Output: OTW scene with or without superimposed optimal trajectory information.

Other external views to demonstrate trajectory and rotorcraft state information

Time history information


AUTOROTATION CBT:NEXT STEPS

Evaluate Industry interest and required functionality and features for: PC based CBT (preview autorotations on the desktop).

PC based flight simulation training aid (provide cueing during flight simulation).

Refine optimal pilot algorithm: Automatic point mass parameter estimation

Winds

Develop a graphical user interface. Validate further using high-fidelity moving-base flight

simulator.

a computer based autorotation trainer edward bachelder, ph.d. bimal l. aponso dongchan lee, ph.d....

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