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Continuous Low-Thrust Trajectory Optimization: Techniques and Applications

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Continuous Low-Thrust Trajectory Optimization: Techniques and Applications Continuous Low-Thrust Trajectory Optimization: Techniques and Applications Mischa Kim Dipl.Ing. – Technische Universit¨at Wien – 2001 M.S. – Virginia Polytechnic Institute and State University – 2003 Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Aerospace Engineering Dr. Christopher D. Hall, Committee Chair Dr. Scott L. Hendricks, Committee Member Dr. Hanspeter Schaub, Committee Member Dr. Daniel J. Stilwell, Committee Member Dr. Craig A. Woolsey, Committee Member April 18, 2005 Blacksburg, Virginia Keywords: Trajectory Optimization, Low-Thrust Propulsion, Symmetry Copyright c 2005 by Mischa Kim Continuous Low-Thrust Trajectory Optimization: Techniques and Applications Mischa Kim (Abstract) Trajectory optimization is a powerful technique to analyze mission feasibility during mission design. High-thrust trajectory optimization problems are typically formulated as discrete optimization problems and are numerically well-behaved. Low-thrust sys- tems, on the other hand, operate for significant periods of the mission time. As a result, the solution approach requires continuous optimization; the associated optimal control problems are in general numerically ill-conditioned. In addition, case studies comparing the performance of low-thrust technologies for space travel have not received adequate attention in the literature and are in most instances incomplete. The objective of this dissertation is therefore to design an efficient optimal control algorithm and to apply it to the minimum-time transfer problem of low-thrust spacecraft. We devise a cas- caded computational scheme based on numerical and analytical methods. Whereas other conventional optimization packages rely on numerical solution approaches, we employ analytical and semi-analytical techniques such as symmetry and homotopy methods to assist in the solution-finding process. The first objective is to obtain a single optimized trajectory that satisfies some given boundary conditions. The initialization phase for this first trajectory includes a global, stochastic search based on Adaptive Simulated Anneal- ing; the fine tuning of optimization parameters – the local search – is accomplished by Quasi-Newton and Newton methods. Once an optimized trajectory has been obtained, we use system symmetry and homotopy techniques to generate additional optimal con- trol solutions efficiently. We obtain optimal trajectories for several interrelated problem families that are described as Multi-Point Boundary Value Problems. We present and prove two theorems describing system symmetries for solar sail spacecraft and discuss symmetry properties and symmetry breaking for electric spacecraft systems models. We demonstrate how these symmetry properties can be used to significantly simplify the solution-finding process. f¨ur mine eltra und min bruadr edi iii Acknowledgments I would like to acknowledge my advisor, and mentor Dr. Chris D. Hall, for giving me the opportunity to study at Virginia Tech. His guidance and motivation have been an integral part in helping me to pursue my career goals. I also wish to express my gratitude to the members of my committee, Dr. Scott L. Hendricks, Dr. Hanspeter Schaub, Dr. Daniel J. Stilwell, and Dr. Craig A. Woolsey for their patience and support. I extend my appreciation and sincere thanks to all the professors that I had the pleasure to learn from during my time at Virginia Tech. I would like to thank the aerospace and ocean engineering staff of Mrs. Gail Coe, Mr. Luke Scharf, Mrs. Wanda Foushee, and Mrs. Betty Williams, who were always able to lend a helping hand whenever needed. Furthermore, I must acknowledge the funding agencies who made my graduate career possible: NASA Goddard Space Flight Center, Society of Satellite Professionals Interna- tional, Osterreichisches¨ Bundesministerium f¨ur Bildung, Wissenschaft und Kunst, Aus- trian Space Agency, and Virginia Space Grant Consortium. Finally, and most importantly, I would like to thank those closest to me. I am greatly indebted to my parents and my brother Edgar for all the moral and loving support and for their unshakable confidence in my abilities. A very special thank-you goes to my girlfriend, Kim Locraft, for her dedication within the past year. She has given me relentless encouragement and has stood by my side through both the good times and bad times. Lastly, I thank all my friends for sharing with me some of the most precious moments of my life. iv Contents Abstract ii Dedication iii Acknowledgements iv List of Figures viii List of Tables xi List of Symbols, Constants and Acronyms xii 1 Introduction 1 1.1 Trajectory Optimization for Low-Thrust Space Travel . ........ 1 1.2 Dissertation Objectives and Problem Statement . ..... 2 1.3 DissertationOverview ............................ 3 2 Literature Review 5 2.1 Trajectory Optimization via Direct Methods . ...... 5 2.2 Trajectory Optimization via Indirect Methods . ....... 8 2.3 StochasticTrajectoryOptimization . 10 2.4 New Trends and Developments in the Field of Trajectory Optimization . 11 2.5 Summary ................................... 13 3 Trajectory Optimization 14 3.1 Low-ThrustTrajectoryOptimization . 14 3.1.1 Trajectory optimization objectives . 15 v 3.1.2 Low-thrust versus high-thrust trajectory optimization ....... 16 3.1.3 Missionscenarios ........................... 17 3.2 OptimizationTheory ............................. 17 3.2.1 Theoptimalcontrolproblem. 18 3.2.2 Directandindirectmethods . 19 3.2.3 Optimizationtechniques . 21 3.2.4 AdditionalmethodstosolveMPBVP . 31 3.3 Developing an Optimization Algorithm . 35 3.4 Summary ................................... 35 4 System Models and Motion Equations 37 4.1 SystemModels ................................ 37 4.2 ElectricPropulsionSpacecraft . 38 4.2.1 Nuclear-electric propulsion systems . 40 4.2.2 Solar-electric propulsion systems . 40 4.2.3 Motion equations for electric propulsion system . 41 4.3 SolarSailSpacecraft ............................. 42 4.3.1 Solarradiationpressuremodel. 42 4.3.2 Motion equations for solar sail system . 43 4.4 Summary ................................... 44 5 Optimal Control Analysis 45 5.1 Two-dimensionalAnalysis . 45 5.1.1 Nuclear-electric propulsion systems . 46 5.1.2 Solar-electric propulsion systems . 48 5.1.3 Solar sail spacecraft . 49 5.1.4 Symmetryanalysis .......................... 50 5.1.5 Results and propulsion system performance comparison . 54 5.2 Three-dimensionalAnalysis . 62 5.2.1 Nuclear-electric propulsion systems . 65 5.2.2 Solar sail spacecraft . 70 5.2.3 Coordinate transformation of solution trajectories . ....... 73 5.2.4 Definingahomotopyproblem . 74 5.2.5 Results and propulsion system performance comparison . 75 5.3 Summary ................................... 77 vi 6 Work in Progress and Future Challenges 80 6.1 Integrating Satellite Attitude Dynamics . ....... 80 6.2 Control system design considerations . 81 6.3 Systemmodelsandmotionequations . 82 6.4 Optimal control analysis for solar sail spacecraft . ...... 85 6.4.1 Spacecraft design parameters . 86 6.4.2 Optimalityconditions . 87 6.4.3 Singular control arc analysis . 88 6.5 Optimal control analysis for nuclear-electric spacecraft .......... 90 6.6 Simulationresults............................... 91 6.7 Summaryandconclusions .......................... 92 7 Summary and Conclusions 95 Bibliography 98 A Optimal Control of Time-Continuous Systems 108 B Nondimensional Motion Equations 112 C Orbital Elements and Cartesian Coordinates 115 Vita 119 vii List of Figures 3.1 Flowchart of the Adaptive Simulated Annealing algorithm . ....... 24 3.2 Interval reduction with Golden Section search algorithm ......... 27 3.3 Numeric and algebraic continuation . 35 3.4 Cascaded numerical algorithm for solving the optimal control problem . 36 4.1 Dynamical systems representations in two dimensions . ..... 39 4.2 Dynamical systems representations in three dimensions . ...... 39 5.1 System symmetry shown with three transfer trajectories for β = 0.33784 53 5.2 Transfer trajectory and solar sail orientation angle history for an Earth- to-Mars transfer with β = 0.16892...................... 55 5.3 Transfer trajectory and solar sail orientation angle history for an Earth- to-Mars transfer with β = 0.33784...................... 56 5.4 Transfer trajectory and thrust angle history for an Earth-to-Mars transfer with τ0 = 0.16892 and κ = 0.50604 ..................... 56 5.5 Transfer trajectory and thrust angle history for an Mars-to-Earth transfer with τ0 = 0.16892 and κ = 0.50604 ..................... 57 5.6 Transfer time as a function of target orbit radius for solar sail spacecraft (solid-dotted lines) and nuclear-electric propulsion spacecraft (solid lines). Theinitialorbitradiusis1AU . 57 5.7 Minimum-time Earth-Mars-Earth double orbit transfer trajectory and so- lar sail orientation angle history for β = 0.33784.............. 59 viii 5.8 Minimum-time Earth-Mars-Earth double orbit transfer trajectory and thrust angle history for τ = 0.16892 and κ = 1.01208 ............... 59 5.9 Minimum-time Mars-to-Earth rendezvous trajectories at first crossover point for β = 0.135136 ............................ 60 5.10 Minimum transfer time for Mars-to-Earth rendezvous for β = 0.16892 . 61 5.11 Minimum-time Mars-to-Earth rendezvous trajectories for second crossover point and for β = 0.33784 .......................... 62 5.12 Trajectory geometry comparison for sleep-type and catch-type solution trajectories
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