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Distributed Spacecraft Control Architectures
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.
Carpenter, James Russell↗
Software for Autonomous Spacecraft Maneuvers
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.
Bristow, John↗
An IP-Based Software System for Real-time, Closed Loop, Multi-Spacecraft Mission Simulations
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.
Cary, Everett↗
The Precision Formation Flying Integrated Analysis Tool (PFFIAT)
Several space missions presently in the concept phase (e.g. Stellar Imager, Submillimeter Probe of Evolutionary Cosmic Structure, Terrestrial Planet Finder) plan to use multiple spacecraft flying in precise formation to synthesize unprecedently large aperture optical systems. These architectures present challenges to the attitude and position determination and control system; optical performance is directly coupled to spacecraft pointing with typical control requirements being on the scale of milliarcseconds and nanometers. To investigate control strategies, rejection of environmental disturbances, and sensor and actuator requirements, a capability is needed to model both the dynamical and optical behavior of such a distributed telescope system. This paper describes work ongoing at NASA Goddard Space Flight Center toward the integration of a set of optical analysis tools (Optical System Characterization and Analysis Research software, or OSCAR) with the Formation Flying Test Bed (FFTB). The resulting system is called the Precision Formation Flying Integrated Analysis Tool (PFFIAT), and it provides the capability to simulate closed-loop control of optical systems composed of elements mounted on multiple spacecraft. The attitude and translation spacecraft dynamics are simulated in the FFTB, including effects of the space environment (e.g. solar radiation pressure, differential orbital motion). The resulting optical configuration is then processed by OSCAR to determine an optical image. From this image, wavefront sensing (e.g. phase retrieval) techniques are being developed to derive attitude and position errors. These error signals will be fed back to the spacecraft control systems, completing the control loop. A simple case study is presented to demonstrate the present capabilities of the tool.
Stoneking, Eric↗
The Precision Formation Flying Integrated Analysis Tool (PFFIAT)
Several space missions presently in the concept phase (e.g. Stellar Imager, Sub- millimeter Probe of Evolutionary Cosmic Structure, Terrestrial Planet Finder) plan to use multiple spacecraft flying in precise formation to synthesize unprecedently large aperture optical systems. These architectures present challenges to the attitude and position determination and control system; optical performance is directly coupled to spacecraft pointing with typical control requirements being on the scale of milliarcseconds and nanometers. To investigate control strategies, rejection of environmental disturbances, and sensor and actuator requirements, a capability is needed to model both the dynamical and optical behavior of such a distributed telescope system. This paper describes work ongoing at NASA Goddard Space Flight Center toward the integration of a set of optical analysis tools (Optical System Characterization and Analysis Research software, or OSCAR) with the Formation J?lying Test Bed (FFTB). The resulting system is called the Precision Formation Flying Integrated Analysis Tool (PFFIAT), and it provides the capability to simulate closed-loop control of optical systems composed of elements mounted on multiple spacecraft. The attitude and translation spacecraft dynamics are simulated in the FFTB, including effects of the space environment (e.g. solar radiation pressure, differential orbital motion). The resulting optical configuration is then processed by OSCAR to determine an optical image. From this image, wavefront sensing (e.g. phase retrieval) techniques are being developed to derive attitude and position errors. These error signals will be fed back to the spacecraft control systems, completing the control loop. A simple case study is presented to demonstrate the present capabilities of the tool.
Stoneking, Eric↗
Autonomy Architectures for a Constellation of Spacecraft
Until the past few years, missions typically involved fairly large expensive spacecraft. Such missions have primarily favored using older proven technologies over more recently developed ones, and humans controlled spacecraft by manually generating detailed command sequences with low-level tools and then transmitting the sequences for subsequent execution on a spacecraft controller. This approach toward controlling a spacecraft has worked spectacularly on previous missions, but it has limitations deriving from communications restrictions - scheduling time to communicate with a particular spacecraft involves competing with other projects due to the limited number of deep space network antennae. This implies that a spacecraft can spend a long time just waiting whenever a command sequence fails. This is one reason why the New Millennium program has an objective to migrate parts of mission control tasks onboard a spacecraft to reduce wait time by making spacecraft more robust. The migrated software is called a "remote agent" and has 4 components: a mission manager to generate the high level goals, a planner/scheduler to turn goals into activities while reasoning about future expected situations, an executive/diagnostics engine to initiate and maintain activities while interpreting sensed events by reasoning about past and present situations, and a conventional real-time subsystem to interface with the spacecraft to implement an activity's primitive actions. In addition to needing remote planning and execution for isolated spacecraft, a trend toward multiple-spacecraft missions points to the need for remote distributed planning and execution. The past few years have seen missions with growing numbers of probes. Pathfinder has its rover (Sojourner), Cassini has its lander (Huygens), and the New Millenium Deep Space 3 (DS3) proposal involves a constellation of 3 spacecraft for interferometric mapping. This trend is expected to continue to progressively larger fleets. For example, one mission proposed to succeed DS3 would have 18 spacecraft flying in formation in order to detect earth-sized planets orbiting other stars. A proposed magnetospheric constellation would involve 5 to 500 spacecraft in Earth orbit to measure global phenomena within the magnetosphere. This work describes and compares three autonomy architectures for a system that continuously plans to control a fleet of spacecraft using collective mission goals instead of goals or command sequences for each spacecraft. A fleet of self-commanding spacecraft would autonomously coordinate itself to satisfy high level science and engineering goals in a changing partially-understood environment making feasible the operation of tens or even a hundred spacecraft (such as for interferometry or plasma physics missions). The easiest way to adapt autonomous spacecraft research to controlling constellations involves treating the constellation as a single spacecraft. Here one spacecraft directly controls the others as if they were connected. The controlling "master" spacecraft performs all autonomy reasoning, and the slaves only have real-time subsystems to execute the master's commands and transmit local telemetry/observations. The executive/diagnostics module starts actions and the master's real-time subsystem controls the action either locally or remotely through a slave. While the master/slave approach benefits from conceptual simplicity, it relies on an assumption that the master spacecraft's executive can continuously monitor the slaves' real-time subsystems, and this relies on high-bandwidth highly-reliable communications. Since unintended results occur fairly rarely, one way to relax the bandwidth requirements involves only monitoring unexpected events in spacecraft. Unfortunately, this disables the ability to monitor for unexpected events between spacecraft and leads to a host of coordination problems among the slaves. Also, failures in the communications system can result in losing slaves. The other two architectures improve robustness while reducing communications by progressively distributing more of the other three remote agent components across the constellation. In a teamwork architecture, all spacecraft have executives and real-time subsystems - only the leader has the planner/scheduler and mission manager. Finally, distributing all remote agent components leads to a peer-to-peer approach toward constellation control.
Barrett, Anthony↗
An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer
The Terrestrial Planet Finder formation flying Interferometer (TPF-I) will be a five-spacecraft, precision formation operating near a Sun-Earth Lagrange point. As part of technology development for TPF-I, a formation and attitude control system (FACS) is being developed that achieves the precision and functionality associated with the TPF-I formation. This FACS will be demonstrated in a distributed, real-time simulation environment. In this paper we present an overview of the FACS and discuss in detail its constituent formation estimation, guidance and control architectures and algorithms. Since the FACS is currently being integrated into a high-fidelity simulation environment, component simulations demonstrating algorithm performance are presented.
Terrestrial Planet Finder (TPF)↗
2000 Survey of Distributed Spacecraft Technologies and Architectures for NASA's Earth Science Enterprise in the 2010-2025 Timeframe
The study investigates NASA's Earth Science Enterprise needs for Distributed Spacecraft Technologies in the 2010-2025 timeframe. In particular, the study focused on the Earth Science Vision Initiative and extrapolation of the measurement architecture from the 2002-2010 time period. Earth Science Enterprise documents were reviewed. Interviews were conducted with a number of Earth scientists and technologists. fundamental principles of formation flying were also explored. The results led to the development of four notional distribution spacecraft architectures. These four notional architectures (global constellations, virtual platforms, precision formation flying, and sensorwebs) are presented. They broadly and generically cover the distributed spacecraft architectures needed by Earth Science in the post-2010 era. These notional architectures are used to identify technology needs and drivers. Technology needs are subsequently grouped into five categories: Systems and architecture development tools; Miniaturization, production, manufacture, test and calibration; Data networks and information management; Orbit control, planning and operations; and Launch and deployment. The current state of the art and expected developments are explored. High-value technology areas are identified for possible future funding emphasis.
Ticker, Ronald L.↗
Precision Formation Delta-V Requirements for Distributed Platforms in Earth Orbit
Distributed spacecraft flying in formation can overcome the resolution limitations of monolithic, Earth-sensing systems. However, formation spacecraft must now expend fuel to counteract disturbances and the gravity gradients between spacecraft. We consider three different formation architectures and determine the (Delta)(nu) required to maintain relative positions at accuracies from 0.1 to 10 m (1(sigma)). The three architectures considered are: (i) Leader/Follower, in which individual spacecraft controllers track with respect to a passive, leader spacecraft, (ii) Center of Formation, in which individual spacecraft controllers track with respect to the geometric center of the formation, and (iii) Iterated Virtual Structure, in which a formation template is fit each timestep and individual spacecraft controllers track with respect to the fitted template.
formation flying↗
A Hardware-in-the-Loop Testbed for Spacecraft Formation Flying Applications
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.
Leitner, Jesse↗
Local Estimators for Spacecraft Formation Flying
A formation estimation architecture for formation flying builds upon the local information exchange among multiple local estimators. 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 needed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms should rely on a local information-exchange network, relaxing the assumptions on existing algorithms. In this research, it was shown that only local observability is required to design a formation estimator and control law. The approach relies on breaking up the overall information-exchange network into sequence of local subnetworks, and invoking an agreement-type filter to reach consensus among local estimators within each local network. State estimates were obtained by a set of local measurements that were passed through a set of communicating Kalman filters to reach an overall state estimation for the formation. An optimization approach was also presented by means of which diffused estimates over the network can be incorporated in the local estimates obtained by each estimator via local measurements. This approach compares favorably with that obtained by a centralized Kalman filter, which requires complete knowledge of the raw measurement available to each estimator.
Fathpour, Nanaz↗
Formation Flying for Distributed InSAR
We consider two spacecraft flying in formation to create interferometric synthetic aperture radar (InSAR). Several candidate orbits for such in InSar formation have been previously determined based on radar performance and Keplerian orbital dynamics. However, with out active control, disturbance-induced drift can degrade radar performance and (in the worst case) cause a collision. This study evaluates the feasibility of operating the InSAR spacecraft as a formation, that is, with inner-spacecraft sensing and control. We describe the candidate InSAR orbits, design formation guidance and control architectures and algorithms, and report the (Delta)(nu) and control acceleration requirements for the candidate orbits for several tracking performance levels. As part of determining formation requirements, a formation guidance algorithm called Command Virtual Structure is introduced that can reduce the (Delta)(nu) requirements compared to standard Leader/Follower formation approaches.
control↗
Decentralized Formation Flying Control in a Multiple-Team Hierarchy
This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple-team framework. The objective is to divide large clusters into teams of manageable size, so that the communication and computational demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high-level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using MANTA (Messaging Architecture for Networking and Threaded Applications). In this architecture, tasks may be remotely added, removed or replaced post-launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in MATLAB, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple-team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.
Mueller, Joseph .↗
An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer
The Terrestrial Planet Finder formation flying Interferometer (TPF-I) will be a five-spacecraft, precision formation operating near the second Sun-Earth Lagrange point. As part of technology development for TPF-I, a formation and attitude control system (FACS) is being developed that achieves the precision and functionality needed for the TPF-I formation and that will be demonstrated in a distributed, real-time simulation environment. In this paper we present an overview of FACS and discuss in detail its formation estimation, guidance and control architectures and algorithms. Since FACS is currently being integrated into a high-fidelity simulation environment, component simulations demonstrating algorithm performance are presented.
Scharf, Daniel P.↗
Formation Control for the Maxim Mission.
Over the next twenty years, a wave of change is occurring in the spacebased scientific remote sensing community. While the fundamental limits in the spatial and angular resolution achievable in spacecraft have been reached, based on today's technology, an expansive new technology base has appeared over the past decade in the area of Distributed Space Systems (DSS). A key subset of the DSS technology area is that which covers precision formation flying of space vehicles. Through precision formation flying, the baselines, previously defined by the largest monolithic structure which could fit in the largest launch vehicle fairing, are now virtually unlimited. Several missions including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), and the Stellar Imager will drive the formation flying challenges to achieve unprecedented baselines for high resolution, extended-scene, interferometry in the ultraviolet and X-ray regimes. This paper focuses on establishing the feasibility for the formation control of the MAXIM mission. The Stellar Imager mission requirements are on the same order of those for MAXIM. This paper specifically addresses: (1) high-level science requirements for these missions and how they evolve into engineering requirements; (2) the formation control architecture devised for such missions; (3) the design of the formation control laws to maintain very high precision relative positions; and (4) the levels of fuel usage required in the duration of these missions. Specific preliminary results are presented for two spacecraft within the MAXIM mission.
Luquette, Richard J.↗
Agent Based Software for the Autonomous Control of Formation Flying Spacecraft
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).
How, Jonathan P.↗
Autonomous Performance Monitoring System: Monitoring and Self-Tuning (MAST)
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.
Peterson, Chariya↗