Design of an Autonomous Decision Support System for High-Level Planning in Nano Satellites ...

113 Pages·2016·5.25 MB·English

Design of an Autonomous Decision
Support System for High-Level Planning in
Nano Satellites Using Logic Programming
Saliha Serdar
Space Engineering, masters level
2017
Luleå University of Technology
Department of Computer Science, Electrical and Space Engineering
Design of an Autonomous Decision
Support System for High-Level
Planning in Nano Satellites Using
Logic Programming
Master Thesis in the course of the study programme
"Master in Space Science and Technology" by
Saliha Serdar
born on April 24th 1991 in Groß-Gerau
Submitted on:
October 11th 2016
Julius-Maximillians-University Luleå Tekniska Universitet
Department of Computer Science Department of Computer Science
Aerospace Information Technology Electrical and Space Engineering
Prof. Dr.-Ing. Hakan Kayal Prof. Dr.Eng. Reza Emami
Prof. Dr. Dietmar Seipel
Statutory declaration
I confirm that this Master’s thesis is my own work and I have documented all sources and
material used. This thesis was not previously presented to another examination board and has
not been published.
Würzburg, 11.10.2016
Contents
Abstract iv
Acknowledgment v
Acronyms vi
1 Introduction 1
2 State of the Art 3
2.1 On-Board Autonomous Science Investigation System for Opportunistic Rover
Science - OASIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 Autonomous Exploration for Gathering Increased Science - AEGIS . . . . . . 4
2.3 Autonomous Science Target Identification and Acquisition - ASTIA . . . . . . 5
2.4 Multi-Rover Integrated Science Understanding System - MISUS . . . . . . . . 6
2.5 Autonomous Sciencecraft Experiment - ASE . . . . . . . . . . . . . . . . . . . 6
2.6 Project for On-Board Autonomy - PROBA . . . . . . . . . . . . . . . . . . . . 7
2.7 Conclusion of the State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . 8
3 Theory 10
3.1 Definition of Decision Support System - DSS . . . . . . . . . . . . . . . . . . . 10
3.2 Logical Programming Language - Prolog . . . . . . . . . . . . . . . . . . . . . 12
3.3 Analytic Hierarchy Process - AHP . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.3.1 Detailed Approach of the Analytical Hierarchy Process . . . . . . . . . 15
3.3.2 Super Decision Software . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3.3 Advantages of AHP over the Simple Scoring Model . . . . . . . . . . . 19
4 Spacecraft Mission Design 21
4.1 SONATE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2 Orbital Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3 Spacecraft Subsystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3.1 On-Board Computer - OBC . . . . . . . . . . . . . . . . . . . . . . . . 23
4.3.2 Power System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Contents ii
4.3.3 Attitude Determination and Control System - ADCS . . . . . . . . . . 25
4.3.4 Thermal Control System . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.3.5 Telemetry, Tracking and Command System - TT&C . . . . . . . . . . . 26
4.3.6 Payload . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5 Definition, Analysis and Evaluation of Spacecraft Failures 28
5.1 Definition of Failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.1.1 OBC Failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.1.2 Power System Failures . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.1.3 Thermal Control System Failures . . . . . . . . . . . . . . . . . . . . . 31
5.1.4 ADCS Failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1.5 TT&C Failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.1.6 Payload Failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.2 Analysis of the Defined Failures . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.2.1 Definition of the Characteristics of Power System Failures . . . . . . . 37
5.2.2 Determining the Degree of Impact of Power System Failures . . . . . . 42
5.2.3 Results of the Failure Rating . . . . . . . . . . . . . . . . . . . . . . . . 51
6 Event Analysis 53
6.1 Defining the Features of the Events . . . . . . . . . . . . . . . . . . . . . . . . 53
6.1.1 Predictability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6.1.2 Repetition in one Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
6.1.3 Level of Intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
6.1.4 Strangeness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.2 Combination of Event Features . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.3 Determining the Importances of Events . . . . . . . . . . . . . . . . . . . . . . 56
7 Decision Support System 60
7.1 Defining the Facts and Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
7.1.1 Facts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
7.1.2 Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.2 Implementation in Prolog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
7.2.1 Facts in Prolog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
7.2.2 Rules in Prolog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
7.2.3 Queries in Prolog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
8 Results and Future Work 70
8.1 Results of the Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
8.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
Contents iii
9 Conclusion 73
Appendix 74
A On-Board Computer Failure Analysis . . . . . . . . . . . . . . . . . . . . . . . 74
B Power System Failure Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
C Thermal Control System Failure Analysis . . . . . . . . . . . . . . . . . . . . . 78
D Attitude Determination and Control System Failure Analysis . . . . . . . . . . 80
E Telemetry, Tracking & Command Failure Analysis . . . . . . . . . . . . . . . . 86
F Payload Failure Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
G Event Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
H Èxypnos System Code for Power System Failures . . . . . . . . . . . . . . . . 91
List of Figures i
List of Tables ii
References iv
Abstract
Low-level decisions in space missions, like maximizing the contact duration or bringing the
spacecraft in safe mode in case of anomalies, are autonomously made by the spacecraft,
whereas high-level and critical decisions are still taken by humans. Due to communication
delays in interplanetary or even interstellar missions, this leads to the limitation of spacecraft
operations in case of unexpected situations. Unexpected situations can be either the detection
of unforeseeable short lived events or even on-board failures. In this given conditions the
spacecraft have to take quick decisions to not miss the event or loss the spacecraft. Higher
demands are imposed to spacecraft autonomy, if an event is detected and an on-board failure
occurs at the same time. The presented work deals exactly with the last stated problem,
which requires autonomy in high-level planning. A decision should be taken between either
investigating the event or repairing the failure. Thereby the unique scientific measurements,
that can result from the detected event, as well as the impact of the failure are considered. In
order to reach this objective an approach of rule-based decision support system, also referred
to as a expert system, is designed for nano satellites. For this purpose, events and on-board
failures are defined, analyzed and converted from objective ratings into numerical values by
applying the Analytical Hierarchy Process. Since the logical programming language Prolog is
an appropriate language for experts systems, a part of the developed system is implemented in
Prolog, to verify its use in space related expert systems.
Acknowledgment
First of all I want to thank my master thesis advisors Prof. Dr.-Ing. Hakan Kayal and Prof. Dr.
Dietmar Seipel of the department of computer Science at the University Würzburg. Prof. Kayal
supported me during my thesis with his expert knowledge concerning aerospace technology and
Prof. Seipel, as a Prolog expert, introduced me in Prolog. I would also like to thank Florian
Kempf (research assistant at the University Würzburg) for inspiring me with new ideas, that
helped me to make great progresses in my thesis.
Finally, I must express my very profound gratitude to my parents, to my partner and to my
friends for providing me with unfailing support and continuous encouragement throughout
my years of study and through the process of researching and writing this thesis. This
accomplishment would not have been possible without them. Thank you.
Saliha Serdar
Acronyms
ADCS Attitude Determination and Control System
ADIA++ Autonomous Diagnostic System for nano satllites
AEGIS Autonomous Exploration for Gathering Increased Science
AHP Analytical Hierarchy Process
ANP Analytical Network Process
ASAP Autonomous Sensor And Planning
ASE Autonomous Sciencecraft Experiment
ASTIA Autonomous Science Target Identification and Acquisition
CASPER Continuous Activity Scheduling, Planning, Execution and Re-planning
ChemCam Chemistry and Camera
CI Consistency Index
DSS Decision Support System
EDAC Error Detection and Correction
EO-1 Earth Observing-1
ESA European Space Agency
ESD Electrostatic Discharge
FDIR Fault Detection Isolation and Recovery
FIDO Field Integrated Design and Operations
GESTALT Gird-based Estimation of Surface Traversability Applied to Local Terrain
GRB Gamma Ray Bursts
Acronyms vii
HG High Gain
HMNAO Her Majesty’s Nautical Almanac Office
HW Hardware
JPL Jet Propulsion Laboratory
KS Knowledge System
KSTIS Knowledge based Science Target Identification System
LG Low Gain
LIBS Laser Induced Breakdown Spectrometer
LS Language System
𝜇ASC micro Advanced Stellar Compass
MBU Multiple Bit Upset
MEL Mars Exploration Laboratory
MER Mars Exploration Rover
MISUS Multi-Rover Integrated Science Understanding System
NASA National Aeronautics and Space Administration
OASIS On-Board Autonomous Science Investigation System for Opportunistic Rover
Science
OBC On-Board Computer
OBSW On-Board Software
PCDU Power Control and Distribution Unit
PPS Problem-Processing System
PROBA Project for On-Board Autonomy
PROLOG Programming in Logic
PS Presentation System
RCS Reaction Control System
RI Random Index