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At least 253 records · Page 14

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NASA NTRS1990

Results of the Systems Autonomy Demonstration Project

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external control system (TCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as nominal control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous, particularly for detection of unforeseen faults and sensor failures.

Glass, B. J.↗

NASA NTRS1990

Applications of AI for automated monitoring - The SHARP system

This paper describes a software system which utilizes artificial intelligence technology to automate several real-time mission operations functions. The paper gives an overview of Voyager spacecraft telecommunications operations at the Jet Propulsion Laboratory to highlight requirements for operations automation in the area of real-time monitoring and analysis. A knowledge-based system, called the 'Spacecraft Health Automated Reasoning Prototype' (SHARP), was developed to explore methods for automated ground data system health and status analysis. The prototype system was applied to Voyager spacecraft telecommunications operations, and installed in the Voyager real-time telecommunications operations area during the spacecraft's encounter with the planet Neptune. The paper reviews the design of the fault detection and diagnosis portions of SHARP, and discusses the performance of SHARP during the encounter. Two follow-on systems based on SHARP which are now in development are also discussed.

Atkinson, David J.↗

NASA NTRS1990

Autonomous power expert system

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.

Ringer, Mark J.↗

NASA NTRS1990

Development of an automated electrical power subsystem testbed for large spacecraft

The NASA Marshall Space Flight Center (MSFC) has developed two autonomous electrical power system breadboards. The first breadboard, the autonomously managed power system (AMPS), is a two power channel system featuring energy generation and storage and 24-kW of switchable loads, all under computer control. The second breadboard, the space station module/power management and distribution (SSM/PMAD) testbed, is a two-bus 120-Vdc model of the Space Station power subsystem featuring smart switchgear and multiple knowledge-based control systems. NASA/MSFC is combining these two breadboards to form a complete autonomous source-to-load power system called the large autonomous spacecraft electrical power system (LASEPS). LASEPS is a high-power, intelligent, physical electrical power system testbed which can be used to derive and test new power system control techniques, new power switching components, and new energy storage elements in a more accurate and realistic fashion. LASEPS has the potential to be interfaced with other spacecraft subsystem breadboards in order to simulate an entire space vehicle. The two individual systems, the combined systems (hardware and software), and the current and future uses of LASEPS are described.

Hall, David K.↗

NASA NTRS1990

Techniques for capturing expert knowledge - An expert systems/hypertext approach

The knowledge-acquisition strategy developed for the Explosive Hazards Classification (EHC) Expert System is described in which expert systems and hypertext are combined, and broad applications are proposed. The EHC expert system is based on rapid prototyping in which primary knowledge acquisition from experts is not emphasized; the explosive hazards technical bulletin, technical guidance, and minimal interviewing are used to develop the knowledge-based system. Hypertext is used to capture the technical information with respect to four issues including procedural, materials, test, and classification issues. The hypertext display allows the integration of multiple knowlege representations such as clarifications or opinions, and thereby allows the performance of a broad range of tasks on a single machine. Among other recommendations, it is suggested that the integration of hypertext and expert systems makes the resulting synergistic system highly efficient.

Lafferty, Larry↗

NASA NTRS1990

Summary of quasi-procedural method

The topics are presented in viewgraph form and include the following: basic system structure and user interface; quasi-procedural method; knowledge-based system; and application to aircraft design.

Source record↗

NASA NTRS1990

Space Station module Power Management And Distribution (PMAD) system

This project consists of several tasks which are unified toward experimentally demonstrating the operation of a highly autonomous, user-supportive power management and distribution system for Space Station Freedom (SSF) habitation/laboratory modules. This goal will be extended to a demonstration of autonomous, cooperative power system operation for the whole SSF power system through a joint effort with NASA's Lewis Research Center, using their Autonomous Power System. Short term goals for the space station module power management and distribution include having an operational breadboard reflecting current plans for SSF, improving performance of the system communications, and improving the organization and mutability of the artificial intelligence (AI) systems. In the middle term, intermediate levels of autonomy will be added, user interfaces will be modified, and enhanced modeling capabilities will be integrated in the system. Long term goals involve conversion of all software into Ada, vigorous verification and validation efforts and, finally, seeing an impact of this research on the operation of SSF. Conversion of the system to a DC Star configuration is now in progress, and should be completed by the end of October, 1989. This configuration reflects the latest SSF module architecture. Hardware is now being procured which will improve system communications significantly. The Knowledge-Based Management System (KBMS) is initially developed and the rules from FRAMES have been implemented in the KBMS. Rules in the other two AI systems are also being grouped modularly, making them more tractable, and easier to eventually move into the KBMS. Adding an intermediate level of autonomy will require development of a planning utility, which will also be built using the KBMS. These changes will require having the user interface for the whole system available from one interface. An Enhanced Model will be developed, which will allow exercise of the system through the interface without requiring all of the power hardware to be operational. The functionality of the AI systems will continue to be advanced, including incipient failure detection. Ada conversion will begin with the lowest level processor (LLP) code. Then selected pieces of the higher level functionality will be recorded in Ada and, where possible, moved to the LLP level. Validation and verification will be done on the Ada code, and will complete sometimes after completion of the Ada conversion.

Walls, Bryan↗

NASA NTRS1990

TEXSYS

The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.

Bull, John↗

NASA NTRS1990

Intelligent systems engineering methodology

An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

Fouse, Scott↗

NASA NTRS1990

Autonomous control

KSC has been developing the Knowledge-Based Autonomous Test Engineer (KATE), which is a tool for performing automated monitoring, diagnosis, and control of electromechanical devices. KATE employs artificial intelligence computing techniques to perform these functions. The KATE system consists of a generic shell and a knowledge base. The KATE shell is the portion of the system which performs the monitoring, diagnosis, and control functions. It is generic in the sense that it is application independent. This means that the monitoring activity, for instance, will be performed with the same algorithms regardless of the particular physical device being used. The knowledge base is the portion of the system which contains specific functional and behavorial information about the physical device KATE is working with. Work is nearing completion on a project at KSC to interface a Texas Instruments Explorer running a LISP version of KATE with a Generic Checkout System (GCS) test-bed to control a physical simulation of a shuttle tanking system (humorously called the Red Wagon because of its color and mobility). The Autonomous Control System (ACS) project supplements and extends the KATE/GCS project by adding three other major activities. The activities include: porting KATE from the Texas Instruments Explorer machine to an Intel 80386-based UNIX workstation in the LISP language; rewriting KATE as necessary to run on the same 80386 workstation but in the Ada language; and investigating software and techniques to translate ANSI Standard Common LISP to Mil Standard Ada. Primary goals of this task are as follows: (1) establish the advantages of using expert systems to provide intelligent autonomous software for Space Station Freedom applications; (2) determine the feasibility of using Ada as the run-time environment for model-based expert systems; (3) provide insight into the advantages and disadvantagesof using LISP or Ada in the run-time environment for expert systems; and (4) compare the performance of the 80386 processor to a symbolic processor as a delivery vehicle for expert systems.

Brown, Barbara↗

NASA NTRS1990

System control module diagnostic Expert Assistant

The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

Flores, Luis M.↗

NASA NTRS1990

An expert system to manage the operation of the Space Shuttle's fuel cell cryogenic reactant tanks

This paper describes a rule-based expert system to manage the operation of the Space Shuttle's cryogenic fuel system. Rules are based on standard fuel tank operating procedures described in the EECOM Console Handbook. The problem of configuring the operation of the Space Shuttle's fuel tanks is well-bounded and well defined. Moreover, the solution of this problem can be encoded in a knowledge-based system. Therefore, a rule-based expert system is the appropriate paradigm. Furthermore, the expert system could be used in coordination with power system simulation software to design operating procedures for specific missions.

Murphey, Amy Y.↗

NASA NTRS1990

ISLE: Intelligent Selection of Loop Electronics. A CLIPS/C++/INGRES integrated application

The Intelligent Selection of Loop Electronics (ISLE) system is an integrated knowledge-based system that is used to configure, evaluate, and rank possible network carrier equipment known as Digital Loop Carrier (DLC), which will be used to meet the demands of forecasted telephone services. Determining the best carrier systems and carrier architectures, while minimizing the cost, meeting corporate policies and addressing area service demands, has become a formidable task. Network planners and engineers use the ISLE system to assist them in this task of selecting and configuring the appropriate loop electronics equipment for future telephone services. The ISLE application is an integrated system consisting of a knowledge base, implemented in CLIPS (a planner application), C++, and an object database created from existing INGRES database information. The embedibility, performance, and portability of CLIPS provided us with a tool with which to capture, clarify, and refine corporate knowledge and distribute this knowledge within a larger functional system to network planners and engineers throughout U S WEST.

Fischer, Lynn↗

NASA NTRS1990

HyperCLIPS: A HyperCard interface to CLIPS

HyperCLIPS combines the intuitive, interactive user interface of the Apple Macintosh(TM) with the powerful symbolic computation of an expert system interpreter. HyperCard(TM) is an excellent environment for quickly developing the front end of an application with buttons, dialogs, and pictures, while the CLIPS interpreter provides a powerful inference engine for complex problem solving and analysis. By integrating HyperCard and CLIPS the advantages and uses of both packages are made available for a wide range of uses: rapid prototyping of knowledge-based expert systems, interactive simulations of physical systems, and intelligent control of hypertext processes, to name a few. Interfacing HyperCard and CLIPS is natural. HyperCard was designed to be extended through the use of external commands (XCMDs), and CLIPS was designed to be embedded through the use of the I/O router facilities and callable interface routines. With the exception of some technical difficulties which will be discussed later, HyperCLIPS implements this interface in a straight forward manner, using the facilities provided. An XCMD called 'ClipsX' was added to HyperCard to give access to the CLIPS routines: clear, load, reset, and run. And an I/O router was added to CLIPS to handle the communication of data between CLIPS and HyperCard.

Pickering, Brad↗

NASA NTRS1990

UFC advisor: An AI-based system for the automatic test environment

The Air Logistics Command within the Air Force is responsible for maintaining a wide variety of aircraft fleets and weapon systems. To maintain these fleets and systems requires specialized test equipment that provides data concerning the behavior of a particular device. The test equipment is used to 'poke and prod' the device to determine its functionality. The data represent voltages, pressures, torques, temperatures, etc. and are called testpoints. These testpoints can be defined numerically as being in or out of limits/tolerance. Some test equipment is termed 'automatic' because it is computer-controlled. Due to the fact that effective maintenance in the test arena requires a significant amount of expertise, it is an ideal area for the application of knowledge-based system technology. Such a system would take testpoint data, identify values out-of-limits, and determine potential underlying problems based on what is out-of-limits and how far. This paper discusses the application of this technology to a device called the Unified Fuel Control (UFC) which is maintained in this manner.

Lincoln, David T.↗

NASA NTRS1989

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗

NASA NTRS1985

Development of an Expert System for Representing Procedural Knowledge

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Georgeff, Michael P.↗

NASA NTRS1990

Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

McManus, John W.↗