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INTELLIGENT SYSTEMS I

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Widely used on systems such as metros, ABS on cars. TUD recently proposed for AOCS ... Classic AI problem: may not be deterministic ... – PowerPoint PPT presentation

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Title: INTELLIGENT SYSTEMS I


1
INTELLIGENT SYSTEMS - I
Workshop on European Space Information
Technology in the 21st Century 27-28th September
2000
  • Roger Thompson and Roger Ward
  • Science Systems (Space) Ltd.
  • Methuen Park
  • Chippenham, Wiltshire, UK SN14 0GB
  • 44 (0)1249 466466
  • www.scisys.co.uk

2
Introduction
  • Definition of Intelligent Systems
  • On-board Intelligence
  • Ground-based Intelligence
  • Importance of Space-Ground Integration
  • Appropriate Applications
  • Appropriate Technologies
  • Validation of Intelligent Systems
  • History Some Examples
  • The Way Forward

3
The Vision...
  • Scientists controlling their own telescopes
  • Spacecraft seeking targets of opportunity as they
    arise
  • Interoperable space and ground segment automation
  • Satellites that call home when they have a
    problem, or call the end user when they find an
    anomaly
  • Formations of spacecraft on "patrol" passing
    guidance and actions from one to another
  • Multiple satellites operating as conventional
    networks, "sharing the processing load
  • Long duration missions augmented with latest
    technology
  • Reduced Operations Costs - Lights Out in the
    Control Room

4
The Reality...
  • The impossible is becoming increasingly possible
  • Software is becoming increasingly Intelligent
    with the application of advanced software
    technology
  • On-board software is the only subsystem which can
    be augmented post launch
  • Software can be used to maximise scientific
    return, and make in-orbit assets more accessible
    to investigators
  • But
  • Software must be actively considered in Mission
    Design
  • European industry is Good at Software - but the
    Initiative is being taken elsewhere...

5
What is an Intelligent System?
  • Key Features
  • Reasoning or Decision Making without Human
    Intervention
  • Delegation of Operational Authority from Human
    Operators to the System
  • Abstraction of Operational Requests (High-Level
    Goals)
  • Autonomous Response to Observable Events
  • Ability to Handle Failures/Anomalies
  • Intelligent or Autonomous? A matter of degree
  • Location - can be anywhere in the System
  • On-board (OBS) - Autonomy
  • Ground Control - Automation
  • Technology
  • Invariably Software
  • Can be Traditional (C, ADA)
  • AI Technologies may allow more efficient
    Development

6
On-board Intelligence (Autonomy)
  • Make Impossible Possible
  • Rapid Reaction to Events - Propagation Delays and
    Non-Contact Periods
  • Simplify Operations
  • Goal Directed Commanding, Target Selection
  • Autonomous Scheduling/Re-scheduling of Operations
    based on Events
  • On-board Quality Control / Data Reduction
  • Qualitative or Fuzzy FDIR cope with sensor
    degradation
  • Benefits
  • Enhanced Performance or Science Return
  • Reduction of Data Traffic on Space-Ground Link
  • Open Accessibility of Payload Operations -
    Telescience
  • Enhanced Safety/Reliability
  • Issues
  • Complexity of Ground Operations
  • Failure of Autonomy - Safety, Diagnosis/Correction
    , Fall-back Ops Mode

7
Ground-based Intelligence (Automation)
  • Automation of Operations
  • Optimisation and Generation of Mission Timelines
  • Management of Operational Constraints (Time and
    Resource)
  • Automated Operations Schedules
  • Automated Operations Procedures
  • Anomaly Detection and Automated Recovery
  • Fault Diagnosis
  • Benefits
  • Fewer Operators or Lights Out Operations
  • Increased Reliability of Routine Operations
  • Potential for Improved Service Provision
  • Reduction of through-life Operations Costs
  • Issues
  • Validation
  • Failure of Automation - Safety, Ability of
    Engineers to React, Potential Service Loss
  • Appropriate Displays and Operations History

8
Importance of Space-Ground Integration
  • Cohesive System - not two independent halves as
    at present
  • Migration of Functions from Ground to Space
  • Common (or Equivalent) Infrastructure on-board
  • Basic TM/TC processing On-board
  • HCI for Operations more useful on Ground!
  • Visibility of On-board Decisions enhanced if SCC
    OBS share common Representation
  • Need to Standardise Higher Levels of Commanding
    and Reporting
  • Command, Event, Parameter, Scheduled Items
  • Common Model of Procedure/Function and Reporting
    against this
  • Definition of APIs rather than Data Formats
  • Support for Interoperable Software Components
  • Remote Agents DS-1
  • Technologies
  • CORBA
  • TCP/IP or SCPS

9
Potential Integrated Model of Operations
Parameters Commands Events
Ground Segment
10
Need to Identify Appropriate Applications
  • Autonomous Operations
  • Goal-oriented Tasking
  • Reaction to Events (e.g. imaging of celestial
    events)
  • On-board Scheduling (e.g. EO constraints - cloud
    cover, mode, power)
  • Management of Resources Power, Fuel, Downlink
  • Task Cueing within Constellation or between
    Instruments
  • Fault Management FDIR, Fault Diagnosis
  • Data Reduction
  • On-board Processing (e.g. SAR Feature Extraction)
  • On-board Quality Control (e.g. discard obscured
    images)
  • Housekeeping Data
  • Autonomous Flight Control
  • Agile AOCS / Image Motion Compensation
  • Formation Control
  • Constellation / Formation Data Management
  • Pass Management
  • Unreliable Ground Contacts - Pass Rescheduling,
    Alternative Comms Routes
  • In Theatre Data Delivery

11
Need to identify appropriate technologies
  • Technologies for Ground Systems will be discussed
    shortly
  • Possible Technologies for end-to-end integration
  • CORBA
  • SCPS or Internet protocols for distributed access
  • Intelligence may be distributed on the ground
  • Interaction and control of on-board autonomy
  • Standardisation of Ground and Space Components
    through OMG or CCSDS?

12
Need to identify appropriate technologies
  • Possible Technologies for On-Board Software
  • Classical coding (Ada or C)
  • Heuristic
  • Fuzzy Logic
  • Neural Networks
  • Potential Functions
  • Only Classical coding (with auto code) being
    exploited currently in Europe, US more
    adventurous?
  • Need to adequately address these technologies

13
Heuristic Techniques
  • Knowledge Based, Constraint Based or Rule Based
  • Allows experience and knowledge to be
    incorporated
  • Solve highly constrained, high data volume
    problems
  • Applicable to Diagnostics, Decision making
    problems and Spacecraft Scheduling

14
Fuzzy Controllers
  • Allows the control of complex systems
  • Fuzzy logic provides an efficient approximate
    description of a system.
  • Can program using algorithms then tune it based
    on input data and expert knowledge.
  • Widely used on systems such as metros, ABS on
    cars
  • TUD recently proposed for AOCS

15
Neural Networks
x0
  • Non deterministic suitable for situations with
    many inputs possibly uncertain inputs
  • Needs to be trained
  • Testing is a major problem
  • Commonly used for diagnostics
  • Could be used to detect Solar flares, space
    debris etc.

f(x)B
f(x)A
x1
y
f(x)A
f(x)B
f(x)C
f(x)A
f(x)B
x2
1
1
16
Potential Functions
  • Based on Lyapunovs Second Method
  • Allows control of complex Non-Linear Systems
  • Will solve large multi-variable systems through
    control of single potential function
  • Useful for Formation Flying, RVD...

17
What would make them appropriate?
  • They must be better than classical approaches
  • Traditionally they should be
  • Deterministic
  • Efficient
  • Secure
  • Supported for radiation hard processors etc
  • Testable
  • Take a Systems View

18
How do we Test these things?
  • Classic AI problem
  • may not be deterministic
  • even if solution is deterministic may be too many
    paths.
  • how rigorously was the human operator tested
  • test specific scenarios, rather than all possible
    conditions
  • test using a subset of the data used for
    training.
  • Do systems level criticality analysis
  • level of testing should depend on level of
    criticality
  • Build confidence slowly. If mission is not
    possible any other way maybe just accept it.

19
Examples of Autonomy
  • XMM
  • Real time spacecraft under ground control
  • Survived at other times
  • AOCS
  • Autonomous Momentum Dumping, FDIR
  • FIRST
  • 48 hours nominal operation without ground contact
  • Operations based on a Timeline
  • Beagle 2
  • Ground contact approximately 15mins every 4 days
    not real time
  • Nominal Operation based on timelines
  • Battery monitoring, Safe Mode

20
Ground/Space Integration on STRV - RATE
  • Space Segment
  • Attitude Determination Remote Agent (ADRA)
  • Migrate existing Attitude Determination Algorithm
    from Ground to Space Segment
  • Uses CORBA Integrated with SCPS
  • Ground Segment
  • STRV MCC
  • Bridge to CORBA based UNiT
  • ADRA becomes a component of the Ground Segment

21
Benefits
  • Intelligent systems are increasingly used as part
    of Ground Segment
  • Only classical software technologies used
    on-board
  • Ground-Space Integration is not addressed

22
Conclusions
  • Need mission developers to recognise
    opportunities for intelligent software technology
    and to support its provision.
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