Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

IEEE IRI 2006 Keynote Speech(I); System of Systems - From Definition to Architecture to Simulation to Space Applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Jamshidi, M. ; Dr., Lutcher Brown Endowed Chair, Department of Electrical and Computer Engineering and Autonomous Control Engineering - ACE Center, The University of Texas, San Antonio TX, USA

One of the main challenges of any related paradigms in systems engineering is being able to handle complex systems under unforeseen uncertainties. A system may be called complex if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is so uncertain that classical techniques cannot easily handle the problem. A system of systems (SoS) is a "super system," or an integration of complex systems coordinated together in such a way as to achieve a wider set of goals with possible higher significance such as global warming, Mars missions, air traffic control, global earth observation system, etc. Computational Intelligence or Soft Computing, a consortium of fuzzy logic (approximate reasoning), neuro-computing (learning), genetic algorithms and genetic programming (optimization), has proven to be a powerful set of tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this presentation, paradigms using soft computing approaches are utilized to design autonomous controller with controller reuse for a number of space applications. The notion of adaptation in autonomous controller reuse can be handled via intelligent tools to add on additional capabilities in real-time scenarios. Learning from past experience is but one such scenario for the reuse of autonomous controllers. These applications include satellite array formations, robotic agents and the Virtual Laboratory (V-LAB??) for multi-physics modeling and simulation.

Published in:

Information Reuse and Integration, 2006 IEEE International Conference on

Date of Conference:

16-18 Sept. 2006