27 research outputs found
Imaging with two-axis micromirrors
We demonstrate a means of creating a digital image by using a two axis tilt
micromirror to scan a scene. For each different orientation we extract a single
grayscale value from the mirror and combine them to form a single composite
image. This allows one to choose the distribution of the samples, and so in
principle a variable resolution image could be created. We demonstrate this
ability to control resolution by constructing a voltage table that compensates
for the non-linear response of the mirrors to the applied voltage.Comment: 8 pages, 5 figures, preprin
Optical Propagation Methods for System-Level Modeling of Optical MEM Systems
In this thesis, we determine and implement an optical propagation technique suitable for system-level simulation of optical micro-systems. The Rayleigh-Sommerfeld formulation is selected as the optical propagation modeling technique because it satisfies the requirements of a system-level CAD tool and supports accurate modeling at propagation distances on the order of the wavelength of light. We present an efficient solution to the Rayleigh-Sommerfeld formulation using the angular spectrum technique which uses the fast Fourier transform to decompose the complex optical wavefront into plane waves propagating from the aperture to the observation plane. This technique reduces the computational order of solving the Rayleigh-Sommerfeld formulation from a brute force direct integration technique of O(N4) to a computational order of O(N2logN).For use in a design environment, we present an error analysis of our technique. Errors are caused by the discrete sampling of the optical wavefront over a finite range to approximate the infinite continuous Fourier transform. Methods for reducing both aliasing and truncation errors are presented, along with techniques to estimate the remaining errors of the angular spectrum technique. We perform a rigorous error estimate on several common optical wavefronts and provide techniques to perform an error analysis on a general wavefront. The utility of this method is shown by implementing the work into a mixed-signal, multi-domain CAD tool, in which we perform system-level simulations and analyses of several optical MEM systems
Model-based optoelectronic packaging automation
IEEE Journal of Selected Topics in Quantum Electronics, 10(3): pp. 445-454. http:dx.doi.org/10.1109/JSTQE.2004.828476In this paper, we present an automation technique
that yields high-performance, low-cost optoelectronic alignment
and packaging through the use of intelligent control theory
and system-level modeling. The control loop design is based
on model-based control, previously popularized in process and
other control industries. The approach is to build an a priori
knowledge model, specific to the assembled package’s optical
power propagation characteristics, and use this to set the initial
“feed-forward” conditions of the automation system. In addition
to this feed-forward model, the controller is designed with feedback
components, along with the inclusion of a built in optical
power sensor. The optical modeling is performed with the rigorous
scalar Rayleigh–Sommerfeld formulation, efficiently solved online
using an angular spectrum technique. One of the benefits of using
a knowledge-based control technique is that the efficiency of the
automation process can be increased, as the number of alignment
steps can be greatly reduced. An additional benefit of this technique
is that it can reduce the possibility that attachment between
optical components will occur at local power maximums, instead
of the global maximum of the power distribution. Therefore,
the technique improves system performance, while reducing the
overall cost of the automation process
Learning identification control for model-based optoelectronic packaging
IEEE Journal Of Selected Topics In Quantum Electronics, 12(5): 945-951.In this paper, we present a learning control algorithm
for the packaging automation of optoelectronic systems. This automation
provides high performance, low-cost alignment and packaging
through the use of a model-based control theory and systemlevel
modeling. The approach is to build an a priori model, specific
to the assembled package’s optical power propagation characteristics.
From this model, an inverse model is created and used in
the “feedforward” loop. In addition to this feedforward model, the
controller is designed with feedback components, along with the
inclusion of a built-in optical power sensor. We introduce a learning
technique, which is activated at a lower sampling frequency
for specific and appropriate tasks, to improve the model used in
the model-based control. Initial results are presented from an experimental
test bed that is used to verify the control and learning
algorithms
Advanced packaging automation for opto-electronic systems
Virology, 351(2), 271-279. http://dx.doi.org/10.1016/j.virol.2006.01.051In this paper, we present a learning control
algorithm used in our research of advanced opto-electronic
automation, which yields high performance, low cost optoelectronic
alignment and packaging through the use of
intelligent control theory and system-level modeling. The
learning loop technique is activated at a lower sampling
frequency for specific and appropriate tasks, to improve the
knowledge based control model. Our automation technique
is based on constructing an a priori knowledge based model,
specific to the assembled package’s optical power
propagation characteristics. From this model, a piece-wise
linear inverse model is created and used in the “feedforward”
loop. This model can be updated for increased
accuracy through the learning loop
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