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An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers Sara K. Scarritt, Belinda G. Marchand, Michael W. Weeks AIAA Guidance, Navigation, and Control Conference & Exhibit 10-13 August 2009, Chicago, IL AIAA 2009-6104 1

An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

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Page 1: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

An Autonomous Onboard Targeting

Algorithm using Finite Thrust

Maneuvers

Sara K. Scarritt, Belinda G. Marchand, Michael W. Weeks

AIAA Guidance, Navigation, and Control Conference & Exhibit

10-13 August 2009, Chicago, IL

AIAA 2009-6104

1

Page 2: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Introduction

Onboard guidance for Orion lunar return

Two-level targeting algorithm

Based on linear system theory

Designed for impulsive maneuvers

In a main engine failure scenario, impulsive approximation

invalid

Adapt two-level targeter to incorporate finite burns while

retaining its simplicity

2 2

Page 3: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Classical Impulsive Level I Process Goal: Position Continuity Only Control Variables: DV’s

BEFORE LEVEL I

AFTER LEVEL I

Page 4: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Classical Level II Process: Goal: Meet Specified Constraints (e.g. Velocity Continuity),

Control Variables: Time & Position of Patch States

BEFORE LEVEL II

IMPLEMENTATION

IN THE N/L SYSTEM

LEVEL II:

LINEAR CORRECTION

Page 5: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

T

kr

1k

k

T

Level 1: Impulsive vs. Finite Burn

5

1

Constraint:

Control Variables: ,

k

k Tt

r 0

u1

Constraint:

Control Variables:

k

k

D

r 0

v

IMPULSIVE FINITE BURN kr

1kDv

1k

k

11 1

g

m

m

r

v

x

u

6 1

rx

v

Page 6: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Variational Equations:

Impulsive vs. Finite Burn

6

, 1 , 1 1 1 1

, 1 , 1 1 1 1

k k k kk k k k k k

k k k kk kk k k k

A Bt t

C Dt t

r v r v

v a v a

IMPULSIVE

FINITE BURN

, 1 , 1 , 1 , 1 , 1

, 1 , 1 , 1 , 1 , 1

, 1 , 1 , 1 , 1 , 1

, 1 , 1 , 1 , 1 , 1

T

T T

T

T k T k T k T k T kT T T

T k T k T k T k T kT T T

T k T k T k T k T kT g T

T k T k T k T k T kg g T

T g T

A B E F Gt

C D H I Jt

K L M N Om m t

P Q R S Tm m t

t

r v

v a

u u

1

1 1

1 1 1

1 1 1

1 1

1

, 1 , 1 , 1 , 1 , 11 1 1

k

k k

k k k

k k k

k g k

g g k

T k T k T k T k T kk k k

t

t

m m t

m m t

U V W X Y t

r v

v a

u u

, 1 , 1 1 1 1

, 1 , 1 1 1 1

k k k kk k k k k k

k k k kk kk k k k

A Bt t

C Dt t

r v r v

v a v a

, 1 , 1 1 1 1

, 1 , 1 1 1 1

k k k kk k k k k k

k k k kk kk k k k

A Bt t

C Dt t

r v r v

v a v a

, ,

, ,

k T k Tk k k T T T

k T k Tk k T Tk T

A Bt t

C Dt t

r v r v

v a v a

Page 7: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Level 1 Targeting Direct from TEI-3 to Earth entry

Entry targets:

Geodetic Altitude (km) 121.92

Longitude (deg) 175.6365

Geocentric Azimuth (deg) 49.3291

Geocentric Flight Path Angle (deg) -5.86

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Page 8: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Level II Algorithm:

Impulsive vs. Finite Burn

8

k

v

k

v

1k

k

1k

1 2 1

0 0 1 1

Constraints: , , , , , , , , , , v

Control Var , ,iables: , , ,,

jn TEI

j

n n

h

t t t

D D D D D

V = v v v A =

b = r r r

k

v

k

v

1k

k

1k

T

IMPULSIVE FINITE BURN

1

T

M

TM MM

D D D

V

V Vb

A A

b

bbA

Page 9: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Variational Equations:

Impulsive vs. Finite Burn

9

, 1 , 1 1 1 1

, 1 , 1 1 1 1

k k k kk k k k k k

k k k kk kk k k k

A Bt t

C Dt t

r v r v

v a v a

IMPULSIVE

FINITE BURN

, 1 , 1 , 1 , 1 , 1

, 1 , 1 , 1 , 1 , 1

, 1 , 1 , 1 , 1 , 1

, 1 , 1 , 1 , 1 , 1

T

T T

T

T k T k T k T k T kT T T

T k T k T k T k T kT T T

T k T k T k T k T kT g T

T k T k T k T k T kg g T

T g T

A B E F Gt

C D H I Jt

K L M N Om m t

P Q R S Tm m t

t

r v

v a

u u

1

1 1

1 1 1

1 1 1

1 1

1

, 1 , 1 , 1 , 1 , 11 1 1

k

k k

k k k

k k k

k g k

g g k

T k T k T k T k T kk k k

t

t

m m t

m m t

U V W X Y t

r v

v a

u u

, 1 , 1 1 1 1

, 1 , 1 1 1 1

k k k kk k k k k k

k k k kk kk k k k

A Bt t

C Dt t

r v r v

v a v a

, 1 , 1 1 1 1

, 1 , 1 1 1 1

k k k kk k k k k k

k k k kk kk k k k

A Bt t

C Dt t

r v r v

v a v a

, ,

, ,

k T k Tk k k T T T

k T k Tk k T Tk T

A Bt t

C Dt t

r v r v

v a v a

Page 10: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Total Cost Constraint:

Impulsive vs. Finite Burn

10

v | |k k k

D v v

0v ln 1 kg T k

k sp

k

m t tI g

m

D

v , ,k k T kf t t mD

1 1

1 1

, , ,

, , ,

k k k k k k

k k k k k k

t t

t t

v v r r

v v r r

IMPULSIVE

FINITE BURN

1

0

1

[ ]n

k g burn jj

m m m t

D

Page 11: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Main Engine Simulation Initial guess data

Epoch: 4-Apr-2024 15:30:00 TDT

Initial mass: 20339.9 kg (total fuel =

8063.65 kg)

Main Engine Thrust: 33,361.6621 N

Main Engine Isp: 326 sec

State (J2000 Moon-centered inertial

frame):

X: -1236.7970783385588 km

Y: 1268.1142350088496 km

Z: 468.38317094160635 km

Vx: 0.0329108058365355 km/sec

Vy: 0.589269803607714 km/sec

Vz -1.528058717568413 km/sec

Entry constraints:

Geodetic Altitude (km): 121.92

Longitude (deg): 175.6365

Geocentric Azimuth (deg): 49.3291

Geocentric Flight Path Angle (deg): -

5.86

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Page 12: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Results (1/2)

12 MCI Frame Perspective

Earth

Moon

Page 13: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Results (2/2)

Comparison of finite burn and impulsive algorithms:

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Page 14: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Auxiliary Engine Simulation

Same initial guess data and constraints

Assume main engine failure after TEI-1

TEI-2 and TEI-3 performed using auxiliary engines:

Auxiliary Engine Thrust: 4,448.0 N

Auxiliary Engine Isp: 309 sec

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Page 15: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Results

Maneuver and final constraint data:

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Page 16: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Lunar Cycle Simulations

Simulations run for 10 different days spanning February 2024

Patch points from converged impulsive runs

Initial lunar orbit of 100 km, targeting altitude (121.9 km)

and flight path angle (-5.86o)

Auxiliary engines used for TEI-2 and TEI-3

Page 17: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Results

Page 18: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Delayed Patch Points

Patch points associated with specific epoch

Targeter must converge even if the patch points are not

current

Using February 1 input file from previous example, initial

epoch delayed for (a) 3 hours and (b) 12 hours

Page 19: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Results

Page 20: An Autonomous Onboard Targeting Algorithm using Finite Thrust Maneuvers

Conclusions and Future Work

Two-level targeting algorithm developed for finite burn

maneuvers

Algorithm successfully targets lunar return trajectory

Using main engines

Using auxiliary engines following simulated failure of main

engines after TEI-1

Future work

Implementing thruster steering law

Automated patch point selection

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