Download presentation

Presentation is loading. Please wait.

Published byFrancisco Sobers Modified over 3 years ago

1
Benoit Pigneur and Kartik Ariyur School of Mechanical Engineering Purdue University June 2013 Inexpensive Sensing For Full State Estimation of Spacecraft

2
Outline Background & Motivation Methodology Test Cases Conclusion & Future Work Benoit Pigneur - Purdue University2

3
Background & Motivation Next generation/future missions – Increase landing mass (ex: human mission) Benoit Pigneur - Purdue University3

4
Background & Motivation Next generation/future missions – Increase precision landing Benoit Pigneur - Purdue University4

5
Background & Motivation Next generation/future missions – Reduce operational costs – Improve autonomous GNC Benoit Pigneur - Purdue University5

6
Background & Motivation State of the art of GNC algorithms for EDLS Benoit Pigneur - Purdue University6 19602010 MSL: Convex optimization of power-descent 2000 Terminal point controller (Apollo) Numerical Predictor-Corrector Analytical Predictor-Corrector Gravity Turn Profile Tracking

7
Background & Motivation Current 2 main directions in development in sensing and state estimation – Development of better sensor accuracy Ex: Hubble’s Fine Guidance Sensors – Improvement in processing inertial measurement unit data Ex: Mars Odyssey aerobraking maneuver Benoit Pigneur - Purdue University7

8
Background & Motivation Improve sensing and state estimation – Develop next generation of autonomous GNC algorithms – Answer some of the challenges for future missions Reduce costs – Reduce operational cost during spacecraft operational life by increasing the autonomy – Reduce cost by using low SWAP (size weight and power) sensors Benoit Pigneur - Purdue University8

9
Outline Background & Motivation Methodology Test Cases Conclusion & Future Work Benoit Pigneur - Purdue University9

10
Methodology Multiple distributed sensors: Geometric configuration – Low SWAP sensors – Large distribution – Exclude outlier measurement – Combine measurements with geometric configuration Benoit Pigneur - Purdue University10 Center of mass MEMS accelerometers x z y x’ z’ y’ R r’ r

11
Methodology Mathematical model: rigid body with constant mass – Acceleration equation with inertial to non-inertial frame conversion formula – R is the distance in the inertial frame – r’ is the distance in the non-inertial frame (rotating frame) – ω is the angular velocity – is the angular acceleration Benoit Pigneur - Purdue University11

12
Methodology Mathematical model: change of inertia – Inertia -> angular acceleration – Angular velocity -> attitude (Euler angles) 1.Euler equations of motion 2.Kinematic equations Benoit Pigneur - Purdue University12

13
Methodology Mathematical model: – Assuming r’ is constant for a rigid body (accelerometers are fixed in the body frame) – The subscript represents the index of the measurement units – a : linear acceleration of the body in the inertial frame – is the accelerometer position – ω is the angular velocity – is the angular acceleration – is the accelerometer measurement Benoit Pigneur - Purdue University13

14
Outline Background & Motivation Methodology Test Cases Conclusion & Future Work Benoit Pigneur - Purdue University14

15
Test Cases 3 different cases: – Circular 2D orbit – Entry, descent and landing – Change of inertia during descent phase Comparison between nominal trajectory, standard IMU simulation and distributed multi-accelerometers simulation Uncertainty in measurement of acceleration – Error ratio of 1/5 between the standard IMU and the distributed multi-accelerometers Benoit Pigneur - Purdue University15

16
Circular 2D orbit: – Simulation conditions: circular orbit at 95 km altitude around the Moon no external force Test Cases Benoit Pigneur - Purdue University16

17
Test Cases Entry, descent and landing: – Simulation conditions: Moon Starting altitude at 95 km Velocity: 1670 m/s Flight path angle: -10° Benoit Pigneur - Purdue University17

18
Test Cases Entry, descent and landing: change of inertia – Simulation conditions: Thrusters time: ON at 200s, OFF at 270s single-axis stabilization along thrust direction Benoit Pigneur - Purdue University18

19
Outline Background & Motivation Methodology Test Cases Conclusion & Future Work Benoit Pigneur - Purdue University19

20
Conclusion & Future Work Advantages of the proposed method – Low SWAP sensors reduce the cost – Optimal geometric configuration and algorithm improve the state estimation – Distributed sensors (accelerometers) give useful information about flexible and moving parts – The methodology is applicable to different sensors: MEMS accelerometers, CMOS imagers… Benoit Pigneur - Purdue University20

21
Conclusion & Future Work Future Work – Improve estimation algorithm by development of optimal geometric configuration – Develop the technique for more challenging environment (atmospheric disturbances, gravity gradient, magnetic field, solar pressure, ionic winds…) – Develop autonomous GNC based on the improvement of the state estimation – Develop this method for other sensors – Improve the attitude estimation for 3-axis stabilized spacecraft Benoit Pigneur - Purdue University21

22
Questions ? Authors: Benoit Pigneur (speaker): bpigneur@purdue.edu Kartik Ariyur Thanks! Benoit Pigneur - Purdue University22

Similar presentations

OK

BL OOS 12.02.2010GG workshop, Pisa / S.Piero a Grado 2/26/2010, Thales Alenia Space Template reference : 100181670S-EN INTERNAL THALES ALENIA SPACE COMMERCIAL.

BL OOS 12.02.2010GG workshop, Pisa / S.Piero a Grado 2/26/2010, Thales Alenia Space Template reference : 100181670S-EN INTERNAL THALES ALENIA SPACE COMMERCIAL.

© 2018 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google