Intelligent Systems and Control
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Description
Research in modern systems science covers a variety of topics, with an emphasis
on the intensive use of mathematics and computers in distributed complex
dynamical systems which evolve in an environment containing considerable
uncertainty and complexity.
Consider, for example, the control of a mobile robotic system
interacting with a changing environment. The intent is for
the elements of the system (arms, camera, mobile base) to cooperate in the
performance of some complex task. The nature of the cooperative interaction is
task dependent and may require real-time adjustments to accommodate sensed
environmental constraints. The control loop is subject to external disturbances
(e.g. changes in the environment), and the robot structural properties change
with changing loads. Measurements of the relevant states are made by
conventional position or force sensors as well as image sensors (video cameras).
These measurements are subject to both noise - random perturbations in the
sensor outputs and artifacts (e.g. partial obscuration of the image field). The
need for good planning and control for nominal performance, as well as proper
emergency capability, also complicates the design problem. The system must
operate properly in a wide range of operating modes
Similar issues arise in biomedical control problems, and aerospace guidance and control
problems. All of these designs require fusion of a complicated suite of sensors,
computers, and problem dynamics into one integrated system. Again, the wide
range of events to which the system is subject create an environment in which
the controller must adapt itself to its perception of the operational
conditions.
As a group, faculty in systems science are involved in
virtually all aspects of this problem. Individual faculty are focusing on topics
that include aerospace guidance and control, as well as advanced digital signal
and image processing, image-based tracking and guidance systems, control of
teleoperated vehicles, analysis and control of mobile multi-armed robot
manipulators. Researchers also integrating non-traditional approaches including
neural networks, fuzzy adaptive control, and rule-based descriptions from LISP
and PROLOG. Typically, advanced mathematical and computational techniques play a
fundamental role in this work. Much of our research is at the interface between
mathematics, control theory, and computer science.
In summary, the group is interested primarily in the study of intelligent information
systems. Focus is placed on that class of system which can, and must learn, about its
environment in an on-line fashion. Such systems exhibit behavior that a human
observer would describe as competent, perhaps purposeful, and at time, even
intelligent.
Information engineering has extensive computing facilities including a Vision Lab
(http://vision.ucsd.edu), an extensive network of
workstations and access to the Computational and Graphical facilities in the San
Diego Supercomputer Center.
Affiliated Faculty
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