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CS COLLOQUIUM

October 26, 1995
3:30 - 4:30 pm
Engineering Center Classroom 2-26

Refreshments will be served before the talk

New Approaches to Engineering Design: Controlled Chaos and Computer
Automation

Liz Bradley
Dept of Computer Science
CU-Boulder

This seminar is an overview of a research project that is exploring two
nontraditional approaches to engineering design.  Each of these two threads
is composed of several synergistic subprojects; these subprojects combine
analytical mathematics, numerical simulation, artificial intelligence
techniques, control theory, and physical experiments.

The first approach involves the active use of chaos to improve the analysis
and design of various electrical, mechanical and chemical engineering
systems.  For example, the dynamics of the differential equation that is
normally used to model the driven pendulum bear only a very general
resemblance to the dynamics of real devices --- and nonlinear regression on
time domain data is not a good enough tool to elucidate the differences.
Nonlinear dynamics techniques like
bifurcation analysis provide a much more powerful comparison.  An example
of how chaos can be exploited in design is the broadening of the capture
range of the common phase-locked loop circuit, which was recently
demonstrated in a physical circuit.  Another potential application, which
we are just beginning to explore, is to cause gases to burn more
effectively by inducing chaotic mixing in a combustion chamber.

The second approach to improving engineering design is through computer
automation.  The ultimate goal of this endeavor is a suite of programs that
explore different high-level analysis and design paradigms.  The first step
along this path, currently under development, is a program called PRET,
which autonomously constructs mathematical models from information about a
system, presented in a variety of forms and formats: measurements made
directly on the physical device; a user's observations described to the
program, in varying degrees of precision, symbolically or graphically;
partial models and hypotheses suggested by a user; and general mathematical
theory that is encoded in the program's knowledge base.

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