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Model-Based FDI for Agile Spacecraft with Multiple Actuators Working Simultaneously E

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Model-Based FDI for Agile Spacecraft with Multiple Actuators Working Simultaneously E Model-based FDI for Agile Spacecraft with Multiple Actuators Working Simultaneously E. Lopez i de la Encarnacion Technische Universiteit Delft Model-based FDI for Agile Spacecraft with Multiple Actuators Working Simultaneously by E. Lopez i de la Encarnacion in partial fulfillement of the requirements to obtain the degree of Master of Science in Aerospace Engineering at the Delft University of Technology, to be defended publicly on 12th June 2019 at 9.00am. Student number: 4617266 Project duration: July 16, 2018 – June 12, 2019 Thesis committee: Dr.ir. R. Fónod, TU Delft, supervisor Dr. A. Cervone, TU Delft, committee chair Dr.ir. E. van Kampen, TU Delft, external examinator An electronic version of this thesis is available at http://repository.tudelft.nl/. Cover image credits: European Space Agency Preface This report presents the MSc thesis project Model-based FDI for Agile Spacecraft with Multiple Actuators Working Simultaneously, the bases of which is a novel fault detection and isolation strategy applied to agile spacecrafts that use multiple actuators together and tested using Monte Carlo campaigns. It has been written to partially fulfill the requirements to obtain the degree of Master of Science in Aerospace Engineering at the Delft University of Technology. The research project and the writing of this thesis has been done from July 2018 to May 2019. The development of this research project has been done at Airbus Defence and Space GmbH, in Friedrichshafen, Germany, within the Attitude and Orbit Control System and Guidance, Navigation, and Control (AOCS/GNC) department. The definition of the thesis goals and scope was done in accordance with my company supervisor, Patrick Bergner, and my thesis supervisor, Róbert Fónod. The thesis presented some difficulties, the fault detection and isolation field is very broad and there are so many strategies that can be used to achieve the defined goals. However, a good literature research and the help and advice of both my supervisors, who were always available and willing to respond to my inquiries, allowed me to accomplish this thesis with satisfaction. In addition, this project allowed me to submit, together with both supervisors, a conference paper to the Automatic Control in Aerospace 2019 (ACA2019) conference, which has been accepted for publication. Therefore, I would to sincerely thank both my supervisors for their support, guidance, and supervision during all these months. I also want to thank all the Airbus colleagues, employ- ees, interns, and thesis students, who help me going through and gave their advice when I needed it. To my family and friends: I would like to thank you for supporting me and keep me motivated when I was discouraged. And specially thank to my parents who have always been there for me and encouraged me to pursue my dreams. I hope you find it interesting and enjoy reading it. E. Lopez i de la Encarnacion Sabadell, May 2019 iii Abstract Current and future space missions require agile and reliable spacecraft capable of trailing and keeping the required attitude. Most of the agile spacecraft missions are near-Earth based but some are placed far away from Earth and its influence. One example of such missions is the Athena mission, which requires the spacecraft to perform fast and large-angle attitude slew manoeuvres. Such manoeuvres often imply simultaneous use of multiple actuators such as thrusters and reaction wheels (RWs). A fault in any of these actuators might lead to partial or full damage of sensitive spacecraft instruments. In this research project, a novel model- based Fault Detection and Isolation (FDI) strategy is proposed, which is able to detect and isolate various actuator faults, such as stuck-open/closed thruster, thruster leakage, loss of effectiveness of all thrusters, and change of RW friction torque due to change of Coulomb and/or viscosity factor. Moreover, the proposed FDI strategy is also able to detect and isolate faults affecting the RWs tachometer. The design of the FDI algorithm is based on a multi- plicative extended Kalman filter, a generalised likelihood ratio thresholding of the residual signals, and a logic algorithm which unequivocally link the faults to the symptoms. The performance and robustness of the proposed FDI strategy are evaluated using Monte Carlo simulations and carefully defined FDI performance indices. In addition, the influence of faults’ magnitudes, times of fault occurrence, and uncertainties’ magnitudes on the FDI sys- tem performance are evaluated. Preliminary results suggest promising performance in terms of detection/isolation times, miss-detection/isolation rates, and false alarm rates. Also, un- certainties on the spacecraft inertia seem to have a negative impact on the FDI performance. In order to fully understand the research project presented here, graduate-level knowledge on rigid body dynamics and kinematics, control theory, and filters applied to estimation might be required. If any of these areas are not known by the reader, it is recommended to read some of the associated literature referenced in the bibliography. v Contents List of Figures ix List of Tables xi Nomenclature xvi Notation xvi 1 Introduction 1 1.1 Background . 1 1.2 Motivation . 3 1.3 The Scope of this Research . 4 1.4 Research Objectives, Framework, and Questions . 4 1.4.1 Research Objectives . 4 1.4.2 Research Framework . 5 1.4.3 Research Questions . 5 2 Theoretical Background 7 2.1 Athena Mission Description . 7 2.1.1 Space Environment . 7 2.1.2 Spacecraft Characteristics . 7 2.1.3 AOCS Equipment. 8 2.2 Fault Detection and Isolation. 9 2.2.1 FDI Architectures . 10 2.2.2 Model-Based FDI . 12 2.3 Spacecraft Attitude Representation . 15 3 Study Case Description and Methodology 17 3.1 Definition of the Study Case . 17 3.1.1 Environment . 17 3.1.2 AOCS Equipment: Sensors and Actuators . 18 3.1.3 Spacecraft’s Dynamics and Kinematics . 20 3.1.4 Faults . 21 3.1.5 Uncertainties . 22 3.2 Methodology for Evaluation of the FDI System . 22 3.2.1 Test Campaigns . 22 3.2.2 Evaluation Criteria . 23 3.2.3 Post-Processing . 24 4 Proposed FDI Strategy 25 4.1 FDI Strategy . 25 4.1.1 Kalman Filter . 25 4.1.2 Extended Kalman Filter . 26 4.1.3 Multiplicative Extended Kalman Filter . 27 4.1.4 State Estimation . 29 4.1.5 Residual Generation . 32 4.1.6 Fault Detection Algorithm . 32 4.1.7 Fault Isolation Algorithm . 33 vii viii Contents 5 Simulation Results 35 5.1 Simulator . 35 5.1.1 Workflow . 35 5.1.2 Structure and Functionality. 36 5.1.3 Missing Features in the Simulator . 37 5.2 Study Case Parameters Definition. 39 5.3 Sample Runs Analysis . 43 5.3.1 Fault-Free. 43 5.3.2 Leakage Fault . 44 5.3.3 Loss of Effectiveness Fault . 45 5.3.4 Stuck Close Fault. 46 5.3.5 Stuck Open Fault . 47 5.3.6 Reaction Wheel Friction Fault . 48 5.3.7 Reaction Wheel Tachometer Fault. 49 5.4 Monte Carlo Analysis. 49 5.4.1 Test Campaign Without Uncertainties . 50 5.4.2 Test Campaign With Uncertainties. 59 5.5 Discussion on Simulation Results . 64 6 Conclusions and Recommendations 65 6.1 Research Sub-Questions . 65 6.1.1 Sub-Question: Study Case Model . 65 6.1.2 Sub-Question: Methodology . 66 6.1.3 Sub-Question: AOCS FDI System. 66 6.1.4 Sub-Question: FDI System Performance . 67 6.2 Research Question . 67 6.3 Recommendations and Future Work . 68 A Appendix: Derivations 71 A.1 Process Noise Matrix Q . 71 A.2 Power Spectral Density and Variance . 74 B Appendix: Validation and Verification 75 B.1 Thruster Reaction Control System. 75 B.1.1 Individual Test . 75 B.1.2 Multiple Test . 76 B.1.3 Monte Carlo Test . 76 B.2 Kalman Filter . 78 C Appendix: Additional Simulation Figures 81 C.1 Sample Runs of Interest . 81 C.1.1 Stuck Open Fault With Highest Time To Detection . 81 C.1.2 Stuck Close Fault With Highest Time To Detection . 82 C.2 Additional Simulation Results Figures . 83 C.3 Uncertainties Correlations . 84 Bibliography 85 List of Figures 1.1 Research framework ................................... 6 2.1 L2 Earth-Sun Halo Orbit. ................................ 8 2.2 ESA design: Athena spacecraft in deployed configuration. ............. 8 2.3 Hybrid expert based architecture. ........................... 10 2.4 Simplified model-based FDI architecture. ...................... 11 2.5 General model-based FDI architecture. ........................ 13 3.1 ESA design: Athena spacecraft in deployed configuration with fixed-body frame. 20 5.1 Top-level architecture of the GAFE Simulator. Source: GAFE Users’ Manual. 36 5.2 Comparison between real scenario PWM signal and simulation scenario PWM signal of single thruster during a single cycle. .................... 39 5.3 Comparation between real scenario PWM signal and simulation scenario PWM signal of single thruster during a single cycle. .................... 39 5.4 Maximum, minimum, and limiting generated torque per axis. .......... 40 5.5 RCS torque envelope. ...................................
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