SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The Defense Meteorological Satellite Program is a total satellite system composed of spacecraft with meteorological sensors, an Earth-based command and control network, user stations, launch vehicle and support; with a communication network linking the various segments together. The various system segments are described.
Network-management software assists in planning, monitoring, and controlling resources of Datalink network. Packet-message network featuring time-division multiple access, frequency and spatial diversity, and dynamic tree-structured routing scheme. Developed for communication between central control station on ground and instrumented aircraft flying over test range. Aircraft derives navigational data from satellites of Global Positioning System, and primary function of Datalink network feeding GPS position data from participating aircraft into control center in real time.
We propose an X Window Graphical User Interface (GUI) which is tailored to the operations of NASA GSFC's Network Control Center (NCC), the NASA Ground Terminal (NGT), the White Sands Ground Terminal (WSGT), and the Second Tracking and Data Relay Satellite System (TDRSS) Ground Terminal (STGT). The proposed GUI can also be easily extended to other Ground Network (GN) Tracking Stations due to its standardized nature.
Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a well-defined set of system-level performance criteria, are called collectives. The fundamental problem in analyzing/designing such systems is in determining how the combined actions of self-interested agents leads to 'coordinated' behavior on a iarge scale. Examples of artificial systems which exhibit such behavior include packet routing across a data network, control of an array of communication satellites, coordination of multiple deployables, and dynamic job scheduling across a distributed computer grid. Examples of natural systems include ecosystems, economies, and the organelles within a living cell. No current scientific discipline provides a thorough understanding of the relation between the structure of collectives and how well they meet their overall performance criteria. Although still very young, research on collectives has resulted in successes both in understanding and designing such systems. It is eqected that as it matures and draws upon other disciplines related to collectives, this field will greatly expand the range of computationally addressable tasks. Moreover, in addition to drawing on them, such a fully developed field of collective intelligence may provide insight into already established scientific fields, such as mechanism design, economics, game theory, and population biology. This chapter provides a survey to the emerging science of collectives.
Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.
A windpowered generator system is described which uses a windmill to convert mechanical energy to electrical energy for a three phase (network) voltage of constant amplitude and frequency. The generator system controls the windmill by the number of revolutions so that the power drawn from the wind for a given wind velocity is maximum. A generator revolution which is proportional to wind velocity is achieved. The stator of the generator is linked directly to the network and a feed converter at the rotor takes care of constant voltage and frequency at the stator.
A three-dimensional (3D) culture system for growing long-lived B lymphocytes has been invented. The capabilities afforded by the system can be expected to expand the range of options for immunological research and related activities, including testing of immunogenicity of vaccine candidates in vitro, generation of human monoclonal antibodies, and immunotherapy. Mature lymphocytes, which are the effectors of adaptive immune responses in vertebrates, are extremely susceptible to apoptotic death, and depend on continuous reception of survival-inducing stimulation (in the forms of cytokines, cell-to-cell contacts, and antigen receptor signaling) from the microenvironment. For this reason, efforts to develop systems for long-term culture of functional, non-transformed and non-activated mature lymphocytes have been unsuccessful until now. The bone-marrow microenvironment supports the growth and differentiation of many hematopoietic lineages, in addition to B-lymphocytes. Primary bone-marrow cell cultures designed to promote the development of specific cell types in vitro are highly desirable experimental systems, amenable to manipulation under controlled conditions. However, the dynamic and complex network of stromal cells and insoluble matrix proteins is disrupted in prior plate- and flask-based culture systems, wherein the microenvironments have a predominantly two-dimensional (2D) character. In 2D bone-marrow cultures, normal B-lymphoid cells become progressively skewed toward precursor B-cell populations that do not retain a normal immunophenotype, and such mature B-lymphocytes as those harvested from the spleen or lymph nodes do not survive beyond several days ex vivo in the absence of mitogenic stimulation. The present 3D culture system is a bioreactor that contains highly porous artificial scaffolding that supports the long-term culture of bone marrow, spleen, and lymph-node samples. In this system, unlike in 2D culture systems, B-cell subpopulations developing within 3D cultures that have been modified to foster lymphopoiesis retain an immunophenotype that closely recapitulates cells in fresh bone marrow harvests. The 3D culture system has been found to be capable of supporting long-lived (8 weeks) populations of B and T lymphocytes from peripheral lymphoid organs, in the absence of activation signals, to an extent not achievable by conventional culture techniques. Interestingly, it has been found that 3D-culture B cells display a phenotype that has characteristics of both B1a and B2 cells. These promising preliminary observations suggest that the 3D culture system could be used with success in the study of peripheral-B-lymphocyte biology and in the development of biotechnological techniques and processes.
Based on a survey of current local area network technology with special attention paid to high bandwidth and very low transport delay requirements, NASA's Langley Research Center designed a new simulation subsystem using the computer automated measurement and control (CAMAC) network. This required significant modifications to the standard CAMAC system and development of a network switch, a clocking system, new conversion equipment, new consoles, supporting software, etc. This system is referred to as the advanced real-time simulation (ARTS) system. It is presently being built at LaRC. This paper provides a functional and physical description of the hardware and a functional description of the software. The requirements which drove the design are presented as well as present performance figures and status.
Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural network should be able to predict the vehicle's future states at next time step. A complete 4-D trajectory are then generated step by step using the trained neural network. Experiments in this work show that the neural network can approximate the sUAV's model and predict the trajectory accurately.
For practical industrial applications, the development of trainable robots is an important and immediate objective. Therefore, the developing of flexible intelligence directly applicable to training is emphasized. It is generally agreed upon by the AI community that the fusion of expert systems, neural networks, and conventionally programmed modules (e.g., a trajectory generator) is promising in the quest for autonomous robotic intelligence. Autonomous robot development is hindered by integration and architectural problems. Some obstacles towards the construction of more general robot control systems are as follows: (1) Growth problem; (2) Software generation; (3) Interaction with environment; (4) Reliability; and (5) Resource limitation. Neural networks can be successfully applied to some of these problems. However, current implementations of neural networks are hampered by the resource limitation problem and must be trained extensively to produce computationally accurate output. A generalization of conventional neural nets is proposed, and an architecture is offered in an attempt to address the above problems.
The paper presents the analysis results (in terms of settling time, bandwidth, and servo error in wind disturbances) of four control systems designed for the Large Millimeter Telescope (LMT). The first system, called PI’, consists of the proportional and integral (PI) controllers in the rate and position loops, and is widely used in the antenna and radiotelescope industry. The analysis shows that the PP control system performance is remarkably good when compared to similar control systems applied to typical antennas. This performance is achieved because the LMT structure is exceptionally rigid, however, it does not meet the stringent LMT pointing requirements. The second system, called PL, consists of the PI controller in the rate loop, and the Linear-Quadratic-Gaussian (LQG) controller in the position loop. This type of controller is implemented in the NASA Deep Space Network antennas, where pointing accuracy is twice that of PP control system. The third system, called LP, consists of the LQG controller in the rate loop, and the propositional-integral-derivative (PID) controller in the position loop. This type of loop has not been yet implemented at known antennas or radiotelescopes, but the analysis shows that its pointing accuracy is the ten times better than PP control system. The fourth system, called LL, consists of the LQG controller in both the rate loop, and the position loop. It is the best of the four, with accuracy 250 better than the PP system, thus is worth further investigations, to identify implementation challenges for the telescopes of high pointing requirements.
The implementation and verification of the delay-compensation algorithm are addressed. The delay compensator has been experimentally verified at an IEEE 802.4 network testbed for velocity control of a DC servomotor. The performance of the delay-compensation algorithm was also examined by combined discrete-event and continuous-time simulation of the flight control system of an advanced aircraft that uses the SAE (Society of Automotive Engineers) linear token passing bus for data communications.
Over the past three years, our group has concentrated on the application of neural network methods to the training of controllers for real-world systems. This presentation describes our approach, surveys what we have found to be important, mentions some contributions to the field, and shows some representative results. Topics discussed include: (1) executing model studies as rehearsal for experimental studies; (2) the importance of correct derivatives; (3) effective training with second-order (DEKF) methods; (4) the efficacy of time-lagged recurrent networks; (5) liberation from the tyranny of the control cycle using asynchronous truncated backpropagation through time; and (6) multistream training for robustness. Results from model studies of automotive idle speed control serve as examples for several of these topics.
The functions, characteristics, and benefits of autonomous control are outlined. An autonomous control functional architecture for future space vehicles that incorporates the concepts and characteristics described is presented. The controller is hierarchical, with an execution level (the lowest level), coordination level (middle level), and management and organization level (highest level). The general characteristics of the overall architecture, including those of the three levels, are explained, and an example to illustrate their functions is given. Mathematical models for autonomous systems, including 'logical' discrete event system models, are discussed. An approach to the quantitative, systematic modeling, analysis, and design of autonomous controllers is also discussed. It is a hybrid approach since it uses conventional analysis techniques based on difference and differential equations and new techniques for the analysis of the systems described with a symbolic formalism such as finite automata. Some recent results from the areas of planning and expert systems, machine learning, artificial neural networks, and the area restructurable controls are briefly outlined.
A Volterra series approach was applied to the identification of nonlinear systems which are described by a neural network model. A procedure is outlined by which a mathematical model can be developed from experimental data obtained from the network structure. Applications of the results to the control of robotic systems are discussed.
This paper describes the development and testing of a scalable thermal control architecture for instruments, subsystems, or systems that must operate in severe space environments with wide variations in sink temperature. The architecture is comprised by linking one or more hot-side variable conductance heat pipes (VCHPs) in series with one or more cold-side loop heat pipes (LHPs). The VCHPs provide wide area heat acquisition, limited distance thermal transport, modest against gravity pumping, concentrated LHP startup heating, and high switching ratio variable conductance operation. The LHPs provide localized heat acquisition, long distance thermal transport, significant against gravity pumping, and high switching ratio variable conductance operation. Combining two variable conductance devices in series ensures very high switching ratio isolation from severe environments like the Earth's moon, where each lunar day spans 15 Earth days (270 K sink, with a surface-shielded/space viewing radiator) and each lunar night spans 15 Earth days (80-100 K radiative sink, depending on location). The single VCHP-single LHP system described herein was developed to maintain thermal control of International Lunar Network (ILN) anchor node lander electronics, but it is also applicable to other variable heat rejection space missions in severe environments. The LHPVCHP system utilizes a stainless steel wire mesh wick ammonia VCHP, a Teflon wick propylene LHP, a pair of one-third square meter high radiators (one capillary-pumped horizontal radiator and a second gravity-fed vertical radiator), a half-meter of transport distance, and a wick-bearing co-located flow regulator (CLFR) to allow operation with a hot (deactivated) radiator. The VCHP was designed with a small reservoir formed by extending the length of its stainless steel heat pipe tubing. The system was able to provide end-to-end switching ratios of 300-500 during thermal vacuum testing at ATK, including 3-5 W/K ON conductance and 0.01 W/K OFF conductance. The test results described herein also include an in-depth analysis of VCHP condenser performance to explain VCHP switching operation in detail. Future multi-VCHP/multi-LHP thermal management system concepts that provide scalability to higher powers/longer transport lengths are also discussed in the paper.
The Space Station Freedom workstation system is a distributed network of computer based workstations that provides the man-machine interfaces for controlling space station systems. This includes control of external manipulator, robotic and free flyer devices by crewmembers in the space station's pressurized shirt-sleeve environment. These remotely controlled devices help minimize the requirement for costly crew extravehicular activity (EVA) time for such tasks as station assembly and payload support. Direct window views may be used for controlling some of the systems, but many activities will be remote or require levels of detail not possible by direct observation. Since controlling remote devices becomes more difficult when direct views are inadequate or unavailable, many performance enhancing techniques have been considered for representing information about remote activities to the operator. Described here are the telepresence techniques under consideration to support operations and training. This includes video enhancements (e.g., graphic and text overlays and stereo viewing), machine vision systems, remote activity animation, and force reflection representation.
The National Aeronautics and Space Administration's (NASA) Unmanned Aircraft Systems (UAS) Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude UAS operations. Currently there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. The UTM technical challenge will develop comprehensive and validated airspace operations and integration requirements to safely enable large-scale persistent access to visual line of sight and autonomous beyond visual line of sight small UAS in low-altitude airspace. Within the UTM project, a number of communications technologies to support UTM command and control (C2) are under investigation. In particular, commercial networked cellular systems are being tested and assessed for their ability to meet the reliability, scalability, cybersecurity and redundancy required. NASA Glenn Research Center is studying some of the aspects of employing such networks for UTM C2 communications. This includes the development of a test platform for sensing and characterizing the airborne C2 communications environment at various altitudes and in various terrains and topologies, measuring such aspects as received signal strength and interference. System performance aspects such as latency in the link, handover performance, packet error loss rate, drop outs, coverage gaps and other aspects impacting UTM operation will also be assessed. In this paper we explore some of the C2 approaches being proposed and demonstrated in the UTM project, the reliability, availability and other general C2 performance requirements, and approaches to evaluating and analyzing UTM C2 links based on commercial cellular networks.