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At least 775 records · Page 43

NASA'S Water Resources Element Within the Applied Sciences Program

The NASA Earth Systems Division has the primary responsibility for the Applied Science Program and the objective to accelerate the use of NASA science results in applications to help solve problems important to society and the economy. The primary goal of the NASA Applied Science Program is to improve future and current operational systems by infusing them with scientific knowledge of the Earth system gained through space-based observation, assimilation of new observations, and development and deployment of enabling technologies, systems, and capabilities. This paper discusses major problems facing water resources managers, including having timely and accurate data to drive their decision support tools. It then describes how NASA's science and space based satellites may be used to overcome this problem. Opportunities for the water resources community to participate in NASA's Water Resources Applications Program are described.

Toll, David↗

Twenty Years of Systems Engineering on the Cassini-Huygens Mission

Over the past twenty years, the Cassini-Huygens Mission has successfully utilized systems engineering to develop and execute a challenging prime mission and two mission extensions. Systems engineering was not only essential in designing the mission, but as knowledge of the system was gained during cruise and science operations, it was critical in evolving operational strategies and processes. This paper discusses systems engineering successes, challenges, and lessons learned on the Cassini-Huygens Mission gathered from a thorough study of mission plans and developed scenarios, and interviews with key project leaders across its twenty-year history.

Manor-Chapman, Emily↗

Optimization of low gravity materials processing experiments using expert systems

The use of an expert system for the control of materials processing experiments in a facility such as the Space Station provides a number of attractive features for insuring that certain critical process parameters can be used to optimize the productivity of the materials processing experiments. The proposed approach to implementation of an expert system utilizes a knowledge base of desired process characteristics which will provide the desired results. The knowledge base for each experiment will be created in conjunction with the scientific investigator in charge of the experiment. Improvements to the knowledge base will be expanded to include self learning sessions in ground based experiments in order to teach the expert system how to respond to perturbations in the process and update the knowledge base on what process change should be implemented in order to reach the desired end product. Design considerations using an on-line real time expert system such as PICON is studied. The types of experiments evaluated include several types of solidification experiments which will be performed on the Space Station.

Workman, Gary L.↗

Machine learning research 1989-90

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base.

Porter, Bruce W.↗

Supplemental knowledge acquisition through external product interface for CLIPS

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

Saito, Tim↗

Detecting opportunities for parallel observations on the Hubble Space Telescope

The presence of multiple scientific instruments aboard the Hubble Space Telescope provides opportunities for parallel science, i.e., the simultaneous use of different instruments for different observations. Determining whether candidate observations are suitable for parallel execution depends on numerous criteria (some involving quantitative tradeoffs) that may change frequently. A knowledge based approach is presented for constructing a scoring function to rank candidate pairs of observations for parallel science. In the Parallel Observation Matching System (POMS), spacecraft knowledge and schedulers' preferences are represented using a uniform set of mappings, or knowledge functions. Assessment of parallel science opportunities is achieved via composition of the knowledge functions in a prescribed manner. The knowledge acquisition, and explanation facilities of the system are presented. The methodology is applicable to many other multiple criteria assessment problems.

Lucks, Michael↗

Galileo: Exploration of Jupiter's system

The scientific objectives of the Galileo mission to the Jovian system is presented. Topics discussed include the history of the project, our current knowledge of the system, the objectives of interrelated experiments, mission design, spacecraft, and instruments. The management, scientists, and major contractors for the project are also given.

Johnson, T. V.↗

An XML Representation for Crew Procedures

NASA ensures safe operation of complex systems through the use of formally-documented procedures, which encode the operational knowledge of the system as derived from system experts. Crew members use procedure documentation on the ground for training purposes and on-board space shuttle and space station to guide their activities. Investigators at JSC are developing a new representation for procedures that is content-based (as opposed to display-based). Instead of specifying how a procedure should look on the printed page, the content-based representation will identify the components of a procedure and (more importantly) how the components are related (e.g., how the activities within a procedure are sequenced; what resources need to be available for each activity). This approach will allow different sets of rules to be created for displaying procedures on a computer screen, on a hand-held personal digital assistant (PDA), verbally, or on a printed page, and will also allow intelligent reasoning processes to automatically interpret and use procedure definitions. During his NASA fellowship, Dr. Simpson examined how various industries represent procedures (also called business processes or workflows), in areas such as manufacturing, accounting, shipping, or customer service. A useful method for designing and evaluating workflow representation languages is by determining their ability to encode various workflow patterns, which depict abstract relationships between the components of a procedure removed from the context of a specific procedure or industry. Investigators have used this type of analysis to evaluate how well-suited existing workflow representation languages are for various industries based on the workflow patterns that commonly arise across industry-specific procedures. Based on this type of analysis, it is already clear that existing workflow representations capture discrete flow of control (i.e., when one activity should start and stop based on when other activities start and stop), but do not capture the flow of data, materials, resources or priorities. Existing workflow representation languages are also limited to representing sequences of discrete activities, and cannot encode procedures involving continuous flow of information or materials between activities.

Simpson, Richard C.↗

An architecture for object-oriented intelligent control of power systems in space

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

Holmquist, Sven G.↗

Linked Autonomous Interplanetary Satellite Orbit Navigation

A navigation technology known as LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation) has been known to produce very impressive navigation results for scenarios involving two or more cooperative satellites near the Moon, such that at least one satellite must be in an orbit significantly perturbed by the Earth, such as a lunar halo orbit. The two (or more) satellites track each other using satellite-to-satellite range and/or range-rate measurements. These relative measurements yield absolute orbit navigation when one of the satellites is in a lunar halo orbit, or the like. The geometry between a lunar halo orbiter and a GEO satellite continuously changes, which dramatically improves the information content of a satellite-to-satellite tracking signal. The geometrical variations include significant out-of-plane shifts, as well as inplane shifts. Further, the GEO satellite is almost continuously in view of a lunar halo orbiter. High-fidelity simulations demonstrate that LiAISON technology improves the navigation of GEO orbiters by an order of magnitude, relative to standard ground tracking. If a GEO satellite is navigated using LiAISON- only tracking measurements, its position is typically known to better than 10 meters. If LiAISON measurements are combined with simple radiometric ground observations, then the satellite s position is typically known to better than 3 meters, which is substantially better than the current state of GEO navigation. There are two features of LiAISON that are novel and advantageous compared with conventional satellite navigation. First, ordinary satellite-to-satellite tracking data only provides relative navigation of each satellite. The novelty is the placement of one navigation satellite in an orbit that is significantly perturbed by both the Earth and the Moon. A navigation satellite can track other satellites elsewhere in the Earth-Moon system and acquire knowledge about both satellites absolute positions and velocities, as well as relative positions and velocities in space. The second novelty is that ordinarily one requires many satellites in order to achieve full navigation of any given customer s position and velocity over time. With LiAISON navigation, only a single navigation satellite is needed, provided that the satellite is significantly affected by the gravity of the Earth and the Moon. That single satellite can track another satellite elsewhere in the Earth- Moon system and obtain absolute knowledge of both satellites states.

Parker, Jeffrey S.↗

Advanced Technology Infusion into Spacesuit Systems

Advancement in technology drives our future. The successful implementation of a technology drives its possibilities. The National Aeronautics and Space Administration (NASA) has invested in numerous technologies that have proved to be successful. The desire is to learn from those successes. For a technology to evolve, become a reality, and infuse into NASA’s missions, a compilation of success-oriented factors must exist for the technology to reach fruition. Understanding these factors could help decrease the complexity of technology infusion and bridge the gap between technology developers and system integrators. The knowledge gained could facilitate the design, development, test, and infusion of a technology to be more effective and efficient. Successful technology infusion is complex and can be even more daunting when advanced technologies are infused into complicated systems. NASA, industry, and academia desire to understand the infusion process, along with measuring the success of infusing an advanced technology into a complex system. This paper focuses on complicated systems that necessitate successful infusion of technologies. These systems include NASA’s spacesuits used for extravehicular activity, including the Apollo Extravehicular Mobility Unit (EMU), the Shuttle/International Space Station EMU, and the Exploration EMU (xEMU) architectures. Several life support technologies will be addressed in the xEMU. Those technologies will be discussed, along with a methodology for assessing infusion pathways. The infusion pathways of these life support technologies into spacesuit architectures can form the benchmark for technology infusion into other architectures for lunar and Martian surfaces. The spacesuit system architectures as case studies can provide the foundation of technical knowledge to help NASA and industry’s project managers and system managers integrate advanced technologies more effectively and efficiently.

Cinda Chullen↗

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

Choudhary, Alok Nidhi↗

Simulation-based assessment on stochastic load scheduling for building cooling systems

Here, to fill knowledge gaps related to stochastic load scheduling, we performed a comprehensive evaluation of the stochastic load scheduling for building cooling systems. Specifically, we studied the common uncertain variables in the load scheduling process for building cooling systems and categorized those variables based on their dynamic patterns. We then developed a generic stochastic load scheduling framework and applied it to building cooling systems that served a simulated community. This community consists of 100 heterogeneous houses and serves as a virtual testbed for evaluating the performance of stochastic load scheduling. In this evaluation, we considered representatives of uncertain variables with different dynamic patterns and included 100 realizations of the considered uncertainty in the evaluation to better catch the probability distribution of the control performance. The evaluation results suggest that deterministic load scheduling can reduce the operating energy cost by 18% but its performance can be affected by uncertainty. Stochastic load scheduling can further decrease the operating energy cost under uncertainty compared to deterministic load scheduling. We also found that the effectiveness of stochastic load scheduling in handling uncertainty is not directly associated with the number of uncertainty scenarios that are considered in its formulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Adaptive Fuzzy Control of a Direct Drive Motor: Experimental Aspects

This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is experimentally verified. The real-time performance is compared with simulation results.

Medina, E.↗

Adaptive Fuzzy Control of a Direct Drive Motor

This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is verified by simulation results.

Medina, E.↗

Spike-Free Adaptive Sliding Mode Control: Application to Permanent Magnet Synchronous Motors

A new methodology for adaptive sliding mode control (ASMC) has been widely used to improve the control performance in various systems. This method exhibits several advantages, including low sliding mode control (SMC) chattering, no knowledge of the system disturbance bound, and no overestimation of the control gain. Despite its advantages, this method can be hampered by the spike phenomenon, slow control gain convergence, and difficulty in achieving optimal performance under varying disturbances. Consequently, this article proposes a spike-free ASMC method with a disturbance observer (DOB) to address these problems. Previous ASMC methods have been analyzed via simulations to verify the aforementioned problems. Here, this analysis highlights the need for disturbance compensation and improvements in the SMC gain adaptation law. Therefore, a DOB is designed to mitigate the spike phenomenon by compensating for disturbances. Subsequently, an SMC gain adaptation law based on disturbance error estimation is designed to eliminate the spike phenomenon completely. The proposed adaptation law makes the SMC gain to converge to a slightly higher value than the disturbance estimation error. Consequently, the proposed method not only eliminates the spike phenomenon, but also ensures optimal performance under varying disturbances. The performance of the proposed method is experimen tally validated through a comparative study.

42 ENGINEERING↗

Decomposing Systems Into Subsystems For Design

Interactions among systems displayed in concise format. DeMAID (Design Manager's Aide for Intelligent Decomposition) is knowledge based software system for automating sequencing of subprocesses in design process and identifying possible multilevel structure for synthesis problem. Reorders and groups modules of equipment being designed on basis of links among modules, helping design manager make design decisions early in design cycle. Written in FORTRAN 77.

Rogers, James L., Jr.↗

Optimum-AIV: A planning and scheduling system for spacecraft AIV

A project undertaken for the European Space Agency (ESA) is presented. The project is developing a knowledge based software system for planning and scheduling of activities for spacecraft assembly, integration, and verification (AIV). The system extends into the monitoring of plan execution and the plan repair phase. The objectives are to develop an operational kernel of a planning, scheduling, and plan repair tool, called OPTIMUM-AIV, and to provide facilities which will allow individual projects to customize the kernel to suit its specific needs. The kernel shall consist of a set of software functionalities for assistance in initial specification of the AIV plan, in verification and generation of valid plans and schedules for the AIV activities, and in interactive monitoring and execution problem recovery for the detailed AIV plans. Embedded in OPTIMUM-AIV are external interfaces which allow integration with alternative scheduling systems and project databases. The current status of the OPTIMUM-AIV project, as of Jan. 1991, is that a further analysis of the AIV domain has taken place through interviews with satellite AIV experts, a software requirement document (SRD) for the full operational tool was approved, and an architectural design document (ADD) for the kernel excluding external interfaces is ready for review.

Arentoft, M. M.↗