The ISA expert system: a prototype system for failure diagnosis on the space station

ABSTRACT

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) is responsible for the safe operation and mission success of manned space flights. The MITRE Corporation, working with MOD, is developing requirements for the Operations Management System (OMS) to automate many aspects of flight control for the Space Station onboard systems. To help develop these requirements, the Integrated Status Assessment (ISA) expert system prototype was built to perform Station-wide failure diagnosis. This paper describes the OMS, how the ISA prototype was built, and how the prototype is being used to help define the OMS. Currently the Space Shuttle is managed on the ground using a hierarchy of control personnel. A flight director responsible for the overall Shuttle mission, a number of front room flight controllers are each responsible for a different system, and many back room controllers support various front room controllers. This system has been used since the early days of space flight and is very manpower intensive. A similar hierarchy is seen in an automated system for the Space Station. The back room controllers can be augmented with smart components and sensors on the Station and the front room controllers can have their jobs aided with expert systems. At the highest level is the OMS which works at the flight director level getting summary information from the various systems in the Station. The OMS will include onboard automation, ground based automation, onboard manual operations, and ground based operations. One of the functions of the OMS is to perform a Station-wide status assessment and failure diagnosis of the Station. This Station-wide view is very important because all of the systems interact with each other and a failure in one system will have impacts on the other systems. It became evident early in discussion with to the MOD flight controllers that prototypes would be very helpful in the process of gathering requirements for the OMS. The prototypes were used to gather additional requirements, to expose people to new ideas and technologies, and study the feasibility of these technologies for systems management. Because the task of assessing the status of space vehicles is a complex job that requires “expert” knowledge to find heuristic solutions to problems, an expert system approach was chosen to prototype the ISA system. The initial domain of the expert system was the KU band portion of the communications and tracking system (one of the onboard “core” Space Station Systems). The ISA prototype expert system consists of a knowledge base, an inference engine, and a user interface. The ISA system was designed as a hybrid expert system using different methodologies: object-oriented programming, rule-based programming using both shallow and deep reasoning, and qualitative modeling. The ISA prototype has been very successful in its goals. ISA has demonstrated new technology and ideas to the NASA operations community, helped define requirements for the OMS, and shown the feasibility of using hierarchical expert systems to monitor complex systems. The ISA prototype, along with other OMS prototypes, are being integrated in a test bed environment with other space station prototypes to form the Space Station Information System (SSIS) End-to-end Test Capability (ETC) which will have components all over the world. The results of the ETC will influence the Space Station design and be a test environment for software and hardware for years to come.

REFERENCES

• 1: D G Bobrow, Qualitative reasoning about physical systems, Massachusetts Institute of Technology, Cambridge, MA, 1985
• 2: Brad J Cox, Object oriented programming: an evolutionary approach, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1986
• 3: Hammen, David G., (1987) Space Station Resource Management, MITRE Working Paper, Houston, TX' The MITRE Corporation.
• 4: Harris, R. A., Marsh, C. A., Reynolds, S. J., Muratore, J., (1987) "Hierarchical Expert Systems for Space Station Systems Management", Poster Session Abstracts, The IEEE Computer Society.
• 5: Marsh, C. A., (March 12, 1987) "ISAES - An Expert System for Evaluating the Condition of the Space Station", Proceedings of JAIPCC '87 Mini-Symposium, Instrument Society of America, Clear Lake - Galveston Section and The Institute of Electrical and Electronics Engineers, Inc., Galveston Bay Section.
• 6: National Aeronautics and Space Administration Advanced Technology Advisory Committee, (1985) Advancing Automation and Robotics Technology for the Space Station and for the U.S. Economy, NASA TM-87566, Houston, TX: NASA Johnson Space Center.
• 7: National Aeronautics and Space Administration, (1986) Space Station Systems Operations Concepts for Systems Management", JSC-20792, Houston, TX: NASA Johnson Space Center.
• 8: Operations Management System Working Group, (1986) Operations Management System Definition Document, Houston, TX: NASA Johnson Space Center.
• 9: R. G. Ross, Entity modeling: techniques and application, Database Research Group, Boston, MA, 1987
• 10: Spitzer, J. F., et al. (January, 1987) Overview of AI Applications for Space Station Systems Managementt, AIAA 25th Aerospace Sciences Meeting, Reno, Nevada.
• 11: Training Division, Systems Training Branch, Mission Operations Directorate- Orientation Manual, JSC 20349, Houston, TX: NASA Johnson Space Center.
• 12: Donald A. Waterman, A guide to expert systems, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1985

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.3 Deduction and Theorem Proving
          Subjects: Deduction (e.g., natural, rule-based)

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.0 General
          Subjects: Data communications

  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human factors
  H.2 DATABASE MANAGEMENT
      H.2.4 Systems
          Subjects: Distributed databases

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Knowledge acquisition

  J. Computer Applications
  J.2 PHYSICAL SCIENCES AND ENGINEERING
      Subjects: Aerospace
  J.6 COMPUTER-AIDED ENGINEERING
      Subjects: Computer-aided manufacturing (CAM)

  K. Computing Milieux
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS
      K.6.1 Project and People Management
          Subjects: Systems development

General Terms:
Design, Human Factors, Languages, Management