Distributed control topologies for deep space formation flying spacecraft
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A formation of satellites flying in deep space can be specified in terms of the relative satellite positions and absolute satellite orientations. The redundancy in the relative position specification generates a family of control topologies with equivalent stability and reference tracking performance, one of which can be implemented without requiring communication between the spacecraft. A relative position design formulation is inherently unobservable, and a methodology for circumventing this problem is presented. Additional redundancy in the control actuation space can be exploited for feed-forward control of the formation centroid's location in space, or for minimization of total fuel consumption.
Distributed satellite systems is an enabling technology for many future NASA/DoD earth and space science missions, such as MMS, MAXIM, Leonardo, and LISA [1, 2, 3]. While formation flying offers significant science benefits, to reduce the operating costs for these missions it will be essential that these multiple vehicles effectively act as a single spacecraft by performing coordinated observations. Autonomous guidance, navigation, and control as part of a coordinated fleet-autonomy is a key technology that will help accomplish this complex goal. This is no small task, as most current space missions require significant input from the ground for even relatively simple decisions such as thruster burns. Work for the NMP DS1 mission focused on the development of the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. NMRA integrates traditional real-time monitoring and control with components for constraint-based planning, robust multi-threaded execution, and model-based diagnosis and reconfiguration. The complexity of using an autonomous approach for space flight software was evident when most of its capabilities were stripped off prior to launch (although more capability was uplinked subsequently, and the resulting demonstration was very successful).
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The formation reconfiguration of multiple free-flying spacecraft is posed as an optimization problem involving minimum fuel expenditure.
Concepts for missions of distributed spacecraft flying in formation abound. From high resolution interferometry to spatially distributed in-situ measurements, these mission concepts levy a myriad of guidance, navigation, and control (GNC) requirements on the spacecraft/formation as a single system. A critical step toward assessing and meeting these challenges lies in realistically simulating distributed spacecraft systems. The Formation Flying TestBed (FFTB) at NASA Goddard Space Flight Center's (GSFC) Guidance, Navigation, and Control Center is a hardware-in-the-loop simulation and development facility focused on GNC issues relevant to formation flying systems. The FFTB provides a realistic simulation of the vehicle dynamics and control for formation flying missions in order to: (1) conduct feasibility analyses of mission requirements, (2) conduct and answer mission and spacecraft design trades, and (3) serve as a host for GNC software and hardware development and testing. The initial capabilities of the FFTB are based upon an integration of high fidelity hardware and software simulation, emulation, and test platforms developed or employed at GSFC in recent years, including a high-fidelity Global Positioning System (GPS) simulator which has been a fundamental component of the GNC Center's GPS Test Facility. The FFTB will be continuously evolving over the next several years from a tool with capabilities in GPS navigation hardware/software-in-the-loop analysis and closed loop GPS-based orbit control algorithm assessment. Eventually, it will include full capability to support all aspects of multi-sensor, absolute and relative state determination and control, in all (attitude and orbit) degrees of freedom, as well as information management for satellite clusters and constellations. A detailed description of the FFTB architecture is presented in the paper.
A fundamental issue for estimation and control of distributed systems such as formation flying spacecraft is the information exchange architecture. In centralized schemes, each subordinate need only share its measurement data with a central hub, and the subordinates depend on the center to direct their actions. In decentralized schemes, all nodes participate in the data exchange, so that each has the same in by formation as the center, and may thereby self-direct the same action that the center would have commanded, assuming all share a common goal. This talk compares and contrasts the centralized and decentralized schemes in the context of autonomously maintaining a distributed satellite formation.
This viewgraph presentation provides information on the architecture of a computerized testbest for simulating Distributed Space Systems (DSS) for controlling spacecraft flying in formation. The presentation also discusses and diagrams the Distributed Synthesis Environment (DSE) for simulating and planning DSS missions.
In this paper we investigate the interaction between an orbiting tethered system and a single spacecraft acting as leader of the tethered formation.
Topics discussed include: The Stellar Imager (SI) "Vision Mission"; First Formation Flying Demonstration Mission Including on Flight Nulling; Formation Flying X-ray Telescope in L2 Orbit; SPECS: The Kilometer-baseline Far-IR Interferometer in NASA's Space Science Roadmap Presentation; A Tight Formation for Along-track SAR Interferometry; Realization of the Solar Power Satellite using the Formation Flying Solar Reflector; SIMBOL-X : Formation Flying for High-Energy Astrophysics; High Precision Optical Metrology for DARWIN; Close Formation Flight of Micro-Satellites for SAR Interferometry; Station-Keeping Requirements for Astronomical Imaging with Constellations of Free-Flying Collectors; Closed-Loop Control of Formation Flying Satellites; Formation Control for the MAXIM Mission; Precision Formation Keeping at L2 Using the Autonomous Formation Flying Sensor; Robust Control of Multiple Spacecraft Formation Flying; Virtual Rigid Body (VRB) Satellite Formation Control: Stable Mode-Switching and Cross-Coupling; Electromagnetic Formation Flight (EMFF) System Design, Mission Capabilities, and Testbed Development; Navigation Algorithms for Formation Flying Missions; Use of Formation Flying Small Satellites Incorporating OISL's in a Tandem Cluster Mission; Semimajor Axis Estimation Strategies; Relative Attitude Determination of Earth Orbiting Formations Using GPS Receivers; Analysis of Formation Flying in Eccentric Orbits Using Linearized Equations of Relative Motion; Conservative Analytical Collision Probabilities for Orbital Formation Flying; Equations of Motion and Stability of Two Spacecraft in Formation at the Earth/Moon Triangular Libration Points; Formations Near the Libration Points: Design Strategies Using Natural and Non-Natural Ares; An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer; GVE-Based Dynamics and Control for Formation Flying Spacecraft; GNC System Design for a New Concept of X-Ray Distributed Telescope; GNC System for the Deployment and Fine Control of the DARWIN Free-Flying Interferometer; Formation Algorithm and Simulation Testbed; and PLATFORM: A Formation Flying, RvD and Robotic Validation Test-bench.
The AutoCon computer programs facilitate and accelerate the planning and execution of orbital control maneuvers of spacecraft while analyzing and resolving mission constraints. AutoCon-F is executed aboard spacecraft, enabling the spacecraft to plan and execute maneuvers autonomously; AutoCon-G is designed for use on the ground. The AutoCon programs utilize advanced techniques of artificial intelligence, including those of fuzzy logic and natural-language scripting, to resolve multiple conflicting constraints and automatically plan maneuvers. These programs can be used to satisfy requirements for missions that involve orbits around the Earth, the Moon, or any planet, and are especially useful for missions in which there are requirements for frequent maneuvers and for resolution of complex conflicting constraints. During operations, the software targets new trajectories, places and sizes maneuvers, and controls spacecraft burns. AutoCon-G provides a userfriendly graphical interface, and can be used effectively by an analyst with minimal training. AutoCon-F reduces latency and supports multiple-spacecraft and formation-flying missions. The AutoCon architecture supports distributive processing, which can be critical for formation- control missions. AutoCon is completely object-oriented and can easily be enhanced by adding new objects and events. AutoCon-F was flight demonstrated onboard GSFC's EO-1 spacecraft flying in formation with Landsat-7.
To provide high-level focus to distributed space system flight dynamics and control research, several benchmark problems are suggested. These problems are not specific to any current or proposed mission, but instead are intended to capture high-level features that would be generic to many similar missions.
Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a formation estimation algorithm that is modular and robust to variations in the topology and link properties of the underlying formation network.
Maintaining the long-term performance of software onboard a spacecraft can be a major factor in the cost of operations. In particular, the task of controlling and maintaining a future mission of distributed spacecraft will undoubtedly pose a great challenge, since the complexity of multiple spacecraft flying in formation grows rapidly as the number of spacecraft in the formation increases. Eventually, new approaches will be required in developing viable control systems that can handle the complexity of the data and that are flexible, reliable and efficient. In this paper we propose a methodology that aims to maintain the accuracy of flight software, while reducing the computational complexity of software tuning tasks. The proposed Monitoring and Self-Tuning (MAST) method consists of two parts: a flight software monitoring algorithm and a tuning algorithm. The dependency on the software being monitored is mostly contained in the monitoring process, while the tuning process is a generic algorithm independent of the detailed knowledge on the software. This architecture will enable MAST to be applicable to different onboard software controlling various dynamics of the spacecraft, such as attitude self-calibration, and formation control. An advantage of MAST over conventional techniques such as filter or batch least square is that the tuning algorithm uses machine learning approach to handle uncertainty in the problem domain, resulting in reducing over all computational complexity. The underlying concept of this technique is a reinforcement learning scheme based on cumulative probability generated by the historical performance of the system. The success of MAST will depend heavily on the reinforcement scheme used in the tuning algorithm, which guarantees the tuning solutions exist.
Numerous space interferometry missions are planned for the next decade to verify different enabling technologies towards very-long-baseline interferometry to achieve high-resolution imaging and high-precision measurements. These objectives will require coordinated formations of spacecraft separately carrying optical elements comprising the interferometer. High-precision sensing and control of the spacecraft and the interferometer-component payloads are necessary to deliver sub-wavelength accuracy to achieve the scientific objectives. For these missions, the primary scientific product of interferometer measurements may be the only source of data available at the precision required to maintain the spacecraft and interferometer-component formation. A concept is studied for detecting the interferometer's optical configuration errors based on information extracted from the interferometer sensor output. It enables precision control of the optical components, and, in cases of space interferometers requiring formation flight of spacecraft that comprise the elements of a distributed instrument, it enables the control of the formation flying vehicles because independent navigation or ranging sensors cannot deliver the high-precision metrology over the entire required geometry. Since the concept can act on the quality of the interferometer output directly, it can detect errors outside the capability of traditional metrology instruments, and provide the means needed to augment the traditional instrumentation to enable enhanced performance. Specific analyses performed in this study include the application of signal-processing and image-processing techniques to solve the problems of interferometer aperture baseline control, interferometer pointing, and orientation of multiple interferometer aperture pairs.
Numerous space interferometry missions are planned for the next decade to verify different enabling technologies towards very-long-baseline interferometry to achieve high-resolution imaging and high-precision measurements. These objectives will require coordinated formations of spacecraft separately carrying optical elements comprising the interferometer. High-precision sensing and control of the spacecraft and the interferometer-component payloads are necessary to deliver sub-wavelength accuracy to achieve the scientific objectives. For these missions, the primary scientific product of interferometer measurements may be the only source of data available at the precision required to maintain the spacecraft and interferometer-component formation. A concept is studied for detecting the interferometer's optical configuration errors based on information extracted from the interferometer sensor output. It enables precision control of the optical components, and, in cases of space interferometers requiring formation flight of spacecraft that comprise the elements of a distributed instrument, it enables the control of the formation-flying vehicles because independent navigation or ranging sensors cannot deliver the high-precision metrology over the entire required geometry. Since the concept can act on the quality of the interferometer output directly, it can detect errors outside the capability of traditional metrology instruments, and provide the means needed to augment the traditional instrumentation to enable enhanced performance. Specific analyses performed in this study include the application of signal-processing and image-processing techniques to solve the problems of interferometer aperture baseline control, interferometer pointing, and orientation of multiple interferometer aperture pairs.
Topics covered include: 1) SNE Industrial Fieldbus Interface; 2) Composite Thermal Switch; 3) XMOS XC-2 Development Board for Mechanical Control and Data Collection; 4) Receiver Gain Modulation Circuit; 5) NEXUS Scalable and Distributed Next-Generation Avionics Bus for Space Missions; 6) Digital Interface Board to Control Phase and Amplitude of Four Channels; 7) CoNNeCT Baseband Processor Module; 8) Cryogenic 160-GHz MMIC Heterodyne Receiver Module; 9) Ka-Band, Multi-Gigabit-Per-Second Transceiver; 10) All-Solid-State 2.45-to-2.78-THz Source; 11) Onboard Interferometric SAR Processor for the Ka-Band Radar Interferometer (KaRIn); 12) Space Environments Testbed; 13) High-Performance 3D Articulated Robot Display; 14) Athena; 15) In Situ Surface Characterization; 16) Ndarts; 17) Cryo-Etched Black Silicon for Use as Optical Black; 18) Advanced CO2 Removal and Reduction System; 19) Correcting Thermal Deformations in an Active Composite Reflector; 20) Umbilical Deployment Device; 21) Space Mirror Alignment System; 22) Thermionic Power Cell To Harness Heat Energies for Geothermal Applications; 23) Graph Theory Roots of Spatial Operators for Kinematics and Dynamics; 24) Spacesuit Soft Upper Torso Sizing Systems; 25) Radiation Protection Using Single-Wall Carbon Nanotube Derivatives; 26) PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure; 27) Lidar Luminance Quantizer; 28) Distributed Capacitive Sensor for Sample Mass Measurement; 29) Base Flow Model Validation; 30) Minimum Landing Error Powered-Descent Guidance for Planetary Missions; 31) Framework for Integrating Science Data Processing Algorithms Into Process Control Systems; 32) Time Synchronization and Distribution Mechanisms for Space Networks; 33) Local Estimators for Spacecraft Formation Flying; 34) Software-Defined Radio for Space-to-Space Communications; 35) Reflective Occultation Mask for Evaluation of Occulter Designs for Planet Finding; and 36) Molecular Adsorber Coating
The Formation Flying Test Bed (FFTB) at NASA Goddard Space Flight Center (GSFC) is being developed as a modular, hybrid dynamic simulation facility employed for end-to-end guidance, navigation, and control (GN&C) analysis and design for formation flying clusters and constellations of satellites. The FFTB will support critical hardware and software technology development to enable current and future missions for NASA, other government agencies, and external customers for a wide range of missions, particularly those involving distributed spacecraft operations. The initial capabilities of the FFTB are based upon an integration of high fidelity hardware and software simulation, emulation, and test platforms developed at GSFC in recent years; including a high-fidelity GPS simulator which has been a fundamental component of the Guidance, Navigation, and Control Center's GPS Test Facility. The FFTB will be continuously evolving over the next several years from a too[ with initial capabilities in GPS navigation hardware/software- in-the- loop analysis and closed loop GPS-based orbit control algorithm assessment to one with cross-link communications and relative navigation analysis and simulation capability. Eventually the FFT13 will provide full capability to support all aspects of multi-sensor, absolute and relative position determination and control, in all (attitude and orbit) degrees of freedom, as well as information management for satellite clusters and constellations. In this paper we focus on the architecture for the FFT13 as a general GN&C analysis environment for the spacecraft formation flying community inside and outside of NASA GSFC and we briefly reference some current and future activities which will drive the requirements and development.