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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

An intelligent training system for payload-assist module deploys

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The Payload-Assist Module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system has, so far, proven to be a potentially valuable addition to the training tools available for training Flight Dynamics Officers in shuttle ground control. The authors are convinced that the basic structure of PD/ICAT can be extended to form a general architecture for intelligent training systems for training flight controllers and crew members in the performance of complex, mission-critical tasks.

Loftin, R. Bowen↗
NASA NTRS1992

Implementation of an intelligent control system

A laboratory testbed facility which was constructed at NASA LeRC for the development of an Intelligent Control System (ICS) for reusable rocket engines is described. The framework of the ICS consists of a hierarchy of various control and diagnostic functions. The traditional high speed, closed-loop controller resides at the lowest level of the ICS hierarchy. Above this level resides the diagnostic functions which identify engine faults. The ICS top level consists of the coordination function which manages the interaction between an expert system and a traditional control system. The purpose of the testbed is to demonstrate the feasibility of the OCS concept by implementing the ICS as the primary controller in a simulation of the Space Shuttle Main Engine (SSME). The functions of the ICS which are implemented in the testbed are as follows: an SSME dynamic simulation with selected fault mode models, a reconfigurable controller, a neural network for sensor validation, a model-based failure detection algorithm, a rule based failure detection algorithm, a diagnostic expert system, an intelligent coordinator, and a user interface which provides a graphical representation of the event occurring within the testbed. The diverse nature of the ICS has led to the development of a distributed architecture consisting of specialized hardware and software for the implementation of the various functions. This testbed is made up of five different computer systems. These individual computers are discussed along with the schemes used to implement the various ICS components. The communication between computers and the timing and synchronization between components are also addressed.

Simon, D. L.↗
NASA NTRS1989

The development of expertise on an intelligent tutoring system

An initial examination was conducted of an Intelligent Tutoring System (ITS) developed for use in industry. The ITS, developed by NASA, simulated a satellite deployment task. More specifically, the PD (Payload Assist Module Deployment)/ICAT (Intelligent Computer Aided Training) System simulated a nominal Payload Assist Module (PAM) deployment. The development of expertise on this task was examined using three Flight Dynamics Officer (FDO) candidates who had no previous experience with this task. The results indicated that performance improved rapidly until Trial 5, followed by more gradual improvements through Trial 12. The performance dimensions measured included performance speed, actions completed, errors, help required, and display fields checked. Suggestions for further refining the software and for deciding when to expose trainees to more difficult task scenarios are discussed. Further, the results provide an initial demonstration of the effectiveness of the PD/ICAT system in training the nominal PAM deployment task and indicate the potential benefits of using ITS's for training other FDO tasks.

Johnson, Debra Steele↗
NASA NTRS1997

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

Tunstel, Edward↗
NASA NTRS1989

Intelligent computational systems for space applications

The evolution of intelligent computation systems is discussed starting with the Spaceborne VHSIC Multiprocessor System (SVMS). The SVMS is a six-processor system designed to provide at least a 100-fold increase in both numeric and symbolic processing over the i386 uniprocessor. The significant system performance parameters necessary to achieve the performance increase are discussed.

Lum, Henry, Jr.↗
NASA NTRS1990

Intelligent Robotic Systems Study (IRSS), phase 2

Under the Intelligent Robotics System Study (IRSS) contract, a generalized robotic control architecture was developed for use with the ProtoFlight Manipulator Arm (PFMA). The controller built for the PFMA provides localized position based force control, teleoperation and advanced path recording and playback capabilities. Various hand controllers can be used with the system in conjunction with a synthetic time delay capability to provide a realistic test bed for typical satellite servicing tasks. The configuration of the IRSS system is illustrated and discussed. The PFMA has six computer controllable degrees of freedom (DOF) plus a seventh manually indexable DOF, making the manipulator a pseudo 7 DOF mechanism. Because the PFMA was not developed to operate in a gravity field, but rather in space, it is counter balanced at the shoulder, elbow and wrist and a spring counterbalance has been added near the wrist to provide additional support. Built with long slender intra-joint linkages, the PFMA has a workspace nearly 2 meters deep and possesses sufficient dexterity to perform numerous satellite servicing tasks. The manipulator is arranged in a shoulder-yaw, pitch, elbow-pitch, and wrist-pitch, yaw, roll configuration, with an indexable shoulder roll joint. Digital control of the PFMA is implemented using a variety of single board computers developed by Heurikon Corporation and other manufacturers. The IRSS controller is designed to be a multi-rate, multi-tasking system. Independent joint servos run at a 134 Hz rate and position based impedance control functions at 67 Hz. Autonomous path generation and hand controller inputs are processed at a 33 Hz.

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NASA NTRS1991

Intelligent Robotic Systems Study (IRSS), phase 4

Under the Intelligent Robotics Systems Study (IRSS), a generalized robotic control architecture was developed for use with the ProtoFlight Manipulator Arm (PFMA). Based upon the NASREM system design concept, the controller built for the PFMA provides localized position based force control, teleoperation, and advanced path recording and playback capabilities. The PFMA has six computer controllable degrees of freedom (DOF) plus a 7th manually indexable DOF, making the manipulator a pseudo 7 DOF mechanism. Joints on the PFMA are driven via 7 pulse width modulated amplifiers. Digital control of the PFMA is implemented using a variety of single board computers. There were two major activities under the IRSS phase 4 study: (1) enhancement of the PFMA control system software functionality; and (2) evaluation of operating modes via a teleoperation performance study. These activities are described and results are given.

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NASA NTRS1992

An advanced intelligent control system framework

A reusable rocket-engine intelligent control system (RREICS) framework was developed to a define a control framework for rocket-engine systems that reduces the required engine maintenance, extends the useful operating life, and maximizes the probability of mission success. The RREICS framework defines a controller that handles a rocket engine cluster as a single system rather than as a collection of individual engines. This enables the controller to alter individual engine operations in response to engine performance or integrity degradations while maintaining the propulsion subsystem external parameters at the levels required for mission success. A simplified model of a three engine cluster and the associated propulsion subsystem controller is also described.

Nemeth, ED↗
NASA NTRS1991

An intelligent control system for rocket engines - Need, vision, and issues

Several components of intelligence are defined. Within the context of these definitions an intelligent control system for rocket engines is described. The description includes a framework for development of an intelligent control system, including diagnostics, coordination, and direct control. Some current results and issues are presented.

Lorenzo, Carl F.↗
NASA NTRS2017

What Machines Need to Learn to Support Human Problem-Solving

In the development of intelligent systems that interact with humans, there is often confusion between how the system functions with respect to the humans it interacts with and how it interfaces with those humans. The former is a much deeper challenge than the latter it requires a system-level understanding of evolving human roles as well as an understanding of what humans need to know (and when) in order to perform their tasks. This talk will focus on some of the challenges in getting this right as well as on the type of research and development that results in successful human-autonomy teaming. Brief Bio: Dr. Alonso Vera is Chief of the Human Systems Integration Division at NASA Ames Research Center. His expertise is in human-computer interaction, information systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Dr. Vera received a Bachelor of Science with First Class Honors from McGill University in 1985 and a Ph.D. from Cornell University in 1991. He went on to a Post-Doctoral Fellowship in the School of Computer Science at Carnegie Mellon University from 1990-93.

intelligent systems↗
NASA NTRS1988

An expert system based intelligent control scheme for space bioreactors

An expert system based intelligent control scheme is being developed for the effective control and full automation of bioreactor systems in space. The scheme developed will have the capability to capture information from various resources including heuristic information from process researchers and operators. The knowledge base of the expert system should contain enough expertise to perform on-line system identification and thus be able to adapt the controllers accordingly with minimal human supervision.

San, Ka-Yiu↗
NASA NTRS1991

Lessons learned in the development of the STOL intelligent tutoring system

Lessons learned during the development of the NASA Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS), being developed at NASA Goddard Space Flight Center are presented. The purpose of the intelligent tutor is to train STOL users by adapting tutoring based on inferred student strengths and weaknesses. This system has been under development for over one year and numerous lessons learned have emerged. These observations are presented in three sections, as follows. The first section addresses the methodology employed in the development of the STOL ITS and briefly presents the ITS architecture. The second presents lessons learned, in the areas of: intelligent tutor development; documentation and reporting; cost and schedule control; and tools and shells effectiveness. The third section presents recommendations which may be considered by other ITS developers, addressing: access, use and selection of subject matter experts; steps involved in ITS development; use of ITS interface design prototypes as part of knowledge engineering; and tools and shells effectiveness.

Seamster, Thomas↗
NASA NTRS2004

Compact Microscope Imaging System With Intelligent Controls Improved

The Compact Microscope Imaging System (CMIS) with intelligent controls is a diagnostic microscope analysis tool with intelligent controls for use in space, industrial, medical, and security applications. This compact miniature microscope, which can perform tasks usually reserved for conventional microscopes, has unique advantages in the fields of microscopy, biomedical research, inline process inspection, and space science. Its unique approach integrates a machine vision technique with an instrumentation and control technique that provides intelligence via the use of adaptive neural networks. The CMIS system was developed at the NASA Glenn Research Center specifically for interface detection used for colloid hard spheres experiments; biological cell detection for patch clamping, cell movement, and tracking; and detection of anode and cathode defects for laboratory samples using microscope technology.

McDowell, Mark↗
NASA NTRS1991

Development of an intelligent diagnostic system for reusable rocket engine control

A description of an intelligent diagnostic system for the Space Shuttle Main Engines (SSME) is presented. This system is suitable for incorporation in an intelligent controller which implements accommodating closed-loop control to extend engine life and maximize available performance. The diagnostic system architecture is a modular, hierarchical, blackboard system which is particularly well suited for real-time implementation of a system which must be repeatedly updated and extended. The diagnostic problem is formulated as a hierarchical classification problem in which the failure hypotheses are represented in terms of predefined data patterns. The diagnostic expert system incorporates techniques for priority-based diagnostics, the combination of analytical and heuristic knowledge for diagnosis, integration of different AI systems, and the implementation of hierarchical distributed systems. A prototype reusable rocket engine diagnostic system (ReREDS) has been implemented. The prototype user interface and diagnostic performance using SSME test data are described.

Anex, R. P.↗
NASA NTRS1992

Sound transmission reduction with intelligent panel systems

Experimental and theoretical investigations are performed of the use of intelligent panel systems to control the sound transmission and radiation. An intelligent structure is defined as a structural system with integrated actuators and sensors under the guidance of an adaptive, learning type controller. The system configuration is based on the Active Structural Acoustic Control (ASAC) concept where control inputs are applied directly to the structure to minimize an error quantity related to the radiated sound field. In this case multiple piezoelectric elements are employed as sensors. The importance of optimal shape and location is demonstrated to be of the same order of influence as increasing the number of channels of control.

Fuller, Chris R.↗
NASA NTRS1990

Monitoring the health of control system components

One characteristic of intelligent behavior is recognition of impaired capability. So an intelligent system should be able to monitor its own performance and determine when one of its components has failed - causing it to lose some degree of capability. This is especially important in autonomous operation which is one of the primary motivations for intelligent systems. This paper briefly reviews the principal approaches that have been suggested for monitoring control systems for failures of its sensors and actuators. The important characteristics of these methods are noted and two are selected for further consideration. These two methods, the failure detection filter and generalized parity relations, are described. Results of experiments are then given of detection and isolation of sensor failures using data taken on the Mini-Mast facility at the NASA Langley Research Center. The effects of certain design options are illustrated. The paper concludes with some observations about the general problem of monitoring the health of control systems.

Vander Velde, W. E.↗
NASA NTRS1990

An endorsement-based approach to student modeling for planner-controlled intelligent tutoring systems

An approach is described to student modeling for intelligent tutoring systems based on an explicit representation of the tutor's beliefs about the student and the arguments for and against those beliefs (called endorsements). A lexicographic comparison of arguments, sorted according to evidence reliability, provides a principled means of determining those beliefs that are considered true, false, or uncertain. Each of these beliefs is ultimately justified by underlying assessment data. The endorsement-based approach to student modeling is particularly appropriate for tutors controlled by instructional planners. These tutors place greater demands on a student model than opportunistic tutors. Numerical calculi approaches are less well-suited because it is difficult to correctly assign numbers for evidence reliability and rule plausibility. It may also be difficult to interpret final results and provide suitable combining functions. When numeric measures of uncertainty are used, arbitrary numeric thresholds are often required for planning decisions. Such an approach is inappropriate when robust context-sensitive planning decisions must be made. A TMS-based implementation of the endorsement-based approach to student modeling is presented, this approach is compared to alternatives, and a project history is provided describing the evolution of this approach.

Murray, William R.↗
NASA NTRS1991

Intelligent Robotic Systems Study (IRSS), phase 3

This phase of the Intelligent Robotic Systems Study (IRSS) examines some basic dynamics and control issues for a space manipulator attached to its worksite through a compliant base. One example of this scenario is depicted, which is a simplified, planar representation of the Flight Telerobotic Servicer (FTS) Development Test Flight 2 (DTF-2) experiment. The system consists of 4 major components: (1) dual FTS arms to perform dextrous tasks; (2) the main body to house power and electronics; (3) an Attachment Stabilization and Positioning Subsystem (ASPS) to provide coarse positioning and stabilization of the arms, and (4) the Worksite Attachment Mechanism (WAM) which anchors the system to its worksite, such as a Space Station truss node or Shuttle bay platform. The analysis is limited to the DTF-2 scenario. The goal is to understand the basic interaction dynamics between the arm, the positioner and/or stabilizer, and the worksite. The dynamics and controls simulation model are described. Analysis and simulation results are presented.

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