Modern Spacecraft Guidance, Navigation, and Control: From System Modeling to AI and Innovative Applications provides a comprehensive foundation of theory and applications of spacecraft GNC, from fundamentals to advanced concepts, including modern AI-based architectures with focus on hardware and software practical applications. Divided into four parts, this book begins with an introduction to spacecraft GNC, before discussing the basic tools for GNC applications. These include an overview of the main reference systems and planetary models, a description of the space environment, an introduction to orbital and attitude dynamics, and a survey on spacecraft sensors and actuators, with details of their modeling principles. Part 2 covers guidance, navigation, and control, including both on-board and ground-based methods. It also discusses classical and novel control techniques, failure detection isolation and recovery (FDIR) methodologies, GNC verification, validation, and on-board implementation. The final part 3 discusses AI and modern applications featuring different applicative scenarios, with particular attention on artificial intelligence and the possible benefits when applied to spacecraft GNC. In this part, GNC for small satellites and CubeSats is also discussed.
Modern Spacecraft Guidance, Navigation, and Control: From System Modeling to AI and Innovative Applications is a valuable resource for aerospace engineers, GNC/AOCS engineers, avionic developers, and AIV/AIT technicians.
1. Chapter one Introduction - p. 3 2. Chapter Two Reference systems and planetary models - p. 45 3. Chapter Three The space environment - p. 77 4. Perturbation sources - p. 78 5. External perturbations - p. 79 6. External perturbations modeling guidelines - p. 97 7. Internal perturbations - p. 100 8. Internal perturbations modeling guidelines - p. 123 9. What is relevant for GNC? - p. 124 10. Chapter Four Orbital dynamics - p. 131 11. Two-body problem - p. 132 12. Three-body problem - p. 161 13. Irregular solar system bodies - p. 170 14. Relative orbital dynamics - p. 174 15. Chapter Five Attitude dynamics - p. 207 16. Attitude kinematics - p. 208 17. Attitude dynamics - p. 227 18. Three-body problem attitude dynamics - p. 248 19. Relative attitude dynamics - p. 249 20. Multibody spacecraft dynamics - p. 250 21. Chapter Six Sensors - p. 253 22. Sensor modeling for GNC - p. 254 23. Sensor faults - p. 275 24. Orbit sensors - p. 276 25. Attitude sensors - p. 286 26. Inertial sensors - p. 306 27. Electro-optical sensors - p. 322 28. Altimeters - p. 330 29. Chapter Seven Actuators - p. 337 30. Chapter Eight Guidance - p. 381 31. What is guidance? - p. 381 32. On-board versus ground-based guidance - p. 382 33. Guidance applications - p. 385 34. Design process - p. 385 35. Design of a guidance function - p. 431 36. Guidance implementation best practices - p. 438 37. Chapter Nine Navigation - p. 441 38. What is navigation? - p. 441 39. On-board versus ground-based navigation - p. 443 40. Sequential filters - p. 445 41. Batch estimation - p. 461 42. Absolute orbit navigation - p. 470 43. Absolute attitude navigation - p. 488 44. Relative navigation - p. 504 45. Image processing techniques - p. 507 46. Navigation budgets - p. 528 47. Navigation implementation best practices - p. 533 48. Chapter Ten Control - p. 543 49. What is control? - p. 543 50. Control design - p. 545 51. Basic terminology - p. 545 52. Properties of feedback control - p. 546 53. Control objective and performance - p. 547 54. Controllability - p. 551 55. Control design in frequency domain - p. 552 56. Control design in the state space - p. 569 57. Limitations to control performance - p. 581 58. An introduction to control design for nonlinear systems - p. 584 59. Review of control methods - p. 592 60. Control budgets - p. 618 61. Control implementation best practices - p. 626 62. Chapter Eleven FDIR development approaches in space systems - p. 631 63. Chapter Twelve GNC verification and validation - p. 647 64. Chapter Thirteen On-board implementation - p. 685 65. Chapter Fourteen Applicative GNC cases and examples - p. 715 66. AOCS design - p. 717 67. Orbital control system - p. 730 68. Attitude control system - p. 742 69. Relative GNC - p. 775 70. On-board sensor processing - p. 791 71. Irregular solar system bodies fly around - p. 803 72. GNC for planetary landing - p. 806 73. Chapter Fifteen Modern Spacecraft GNC - p. 819 74. AI in space—Introduction - p. 821 75. Introduction - p. 821 76. Learning paradigms: supervised, unsupervised, and reinforcement learning - p. 822 77. Unsupervised learning: k-means clustering - p. 825 78. Supervised learning: regression and classification - p. 826 79. Types of artificial neural networks - p. 843 80. Applications scenarios and AI challenges - p. 865 81. Artificial intelligence and navigation - p. 867 82. Validation of AI-based systems - p. 883 83. Reinforcement learning - p. 890 84. AI use cases - p. 906 85. AI on-board processors - p. 923 86. Innovative techniques for highly autonomous FDIR in GNC applications - p. 925 87. Small satellites/CubeSats - p. 938 88. Chapter Sixteen Mathematical and geometrical rules - p. 983 89. Chapter Seventeen Dynamical systems theory - p. 1007 90. Chapter Eighteen Autocoding best practices - p. 1017 91. List of main architectural and implementation rules - p. 1017 92. Index - p. 1027
Modern Spacecraft Guidance, Navigation, and Control: From System Modeling to AI and Innovative Applications provides a comprehensive foundation of theory and applications of spacecraft GNC, from fundamentals to advanced concepts, including modern AI-based architectures with focus on hardware and software practical applications. Divided into four parts, this book begins with an introduction to spacecraft GNC, before discussing the basic tools for GNC applications. These include an overview of the main reference systems and planetary models, a description of the space environment, an introduction to orbital and attitude dynamics, and a survey on spacecraft sensors and actuators, with details of their modeling principles. Part 2 covers guidance, navigation, and control, including both on-board and ground-based methods. It also discusses classical and novel control techniques, failure detection isolation and recovery (FDIR) methodologies, GNC verification, validation, and on-board implementation. The final part 3 discusses AI and modern applications featuring different applicative scenarios, with particular attention on artificial intelligence and the possible benefits when applied to spacecraft GNC. In this part, GNC for small satellites and CubeSats is also discussed.
Modern Spacecraft Guidance, Navigation, and Control: From System Modeling to AI and Innovative Applications is a valuable resource for aerospace engineers, GNC/AOCS engineers, avionic developers, and AIV/AIT technicians.
1. Chapter one Introduction - p. 3 2. Chapter Two Reference systems and planetary models - p. 45 3. Chapter Three The space environment - p. 77 4. Perturbation sources - p. 78 5. External perturbations - p. 79 6. External perturbations modeling guidelines - p. 97 7. Internal perturbations - p. 100 8. Internal perturbations modeling guidelines - p. 123 9. What is relevant for GNC? - p. 124 10. Chapter Four Orbital dynamics - p. 131 11. Two-body problem - p. 132 12. Three-body problem - p. 161 13. Irregular solar system bodies - p. 170 14. Relative orbital dynamics - p. 174 15. Chapter Five Attitude dynamics - p. 207 16. Attitude kinematics - p. 208 17. Attitude dynamics - p. 227 18. Three-body problem attitude dynamics - p. 248 19. Relative attitude dynamics - p. 249 20. Multibody spacecraft dynamics - p. 250 21. Chapter Six Sensors - p. 253 22. Sensor modeling for GNC - p. 254 23. Sensor faults - p. 275 24. Orbit sensors - p. 276 25. Attitude sensors - p. 286 26. Inertial sensors - p. 306 27. Electro-optical sensors - p. 322 28. Altimeters - p. 330 29. Chapter Seven Actuators - p. 337 30. Chapter Eight Guidance - p. 381 31. What is guidance? - p. 381 32. On-board versus ground-based guidance - p. 382 33. Guidance applications - p. 385 34. Design process - p. 385 35. Design of a guidance function - p. 431 36. Guidance implementation best practices - p. 438 37. Chapter Nine Navigation - p. 441 38. What is navigation? - p. 441 39. On-board versus ground-based navigation - p. 443 40. Sequential filters - p. 445 41. Batch estimation - p. 461 42. Absolute orbit navigation - p. 470 43. Absolute attitude navigation - p. 488 44. Relative navigation - p. 504 45. Image processing techniques - p. 507 46. Navigation budgets - p. 528 47. Navigation implementation best practices - p. 533 48. Chapter Ten Control - p. 543 49. What is control? - p. 543 50. Control design - p. 545 51. Basic terminology - p. 545 52. Properties of feedback control - p. 546 53. Control objective and performance - p. 547 54. Controllability - p. 551 55. Control design in frequency domain - p. 552 56. Control design in the state space - p. 569 57. Limitations to control performance - p. 581 58. An introduction to control design for nonlinear systems - p. 584 59. Review of control methods - p. 592 60. Control budgets - p. 618 61. Control implementation best practices - p. 626 62. Chapter Eleven FDIR development approaches in space systems - p. 631 63. Chapter Twelve GNC verification and validation - p. 647 64. Chapter Thirteen On-board implementation - p. 685 65. Chapter Fourteen Applicative GNC cases and examples - p. 715 66. AOCS design - p. 717 67. Orbital control system - p. 730 68. Attitude control system - p. 742 69. Relative GNC - p. 775 70. On-board sensor processing - p. 791 71. Irregular solar system bodies fly around - p. 803 72. GNC for planetary landing - p. 806 73. Chapter Fifteen Modern Spacecraft GNC - p. 819 74. AI in space—Introduction - p. 821 75. Introduction - p. 821 76. Learning paradigms: supervised, unsupervised, and reinforcement learning - p. 822 77. Unsupervised learning: k-means clustering - p. 825 78. Supervised learning: regression and classification - p. 826 79. Types of artificial neural networks - p. 843 80. Applications scenarios and AI challenges - p. 865 81. Artificial intelligence and navigation - p. 867 82. Validation of AI-based systems - p. 883 83. Reinforcement learning - p. 890 84. AI use cases - p. 906 85. AI on-board processors - p. 923 86. Innovative techniques for highly autonomous FDIR in GNC applications - p. 925 87. Small satellites/CubeSats - p. 938 88. Chapter Sixteen Mathematical and geometrical rules - p. 983 89. Chapter Seventeen Dynamical systems theory - p. 1007 90. Chapter Eighteen Autocoding best practices - p. 1017 91. List of main architectural and implementation rules - p. 1017 92. Index - p. 1027
