Learning identification control for model-based optoelectronic packaging

Shubham K. Bhat, Timothy P. Kurzweg, Allon Guez

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)945-951
Number of pages7
JournalIEEE Journal on Selected Topics in Quantum Electronics
Volume12
Issue number5
DOIs
StatePublished - Sep 1 2006

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packaging
Optoelectronic devices
learning
Identification (control systems)
Packaging
automation
Automation
control theory
test stands
Control theory
controllers
Learning algorithms
sampling
alignment
inclusions
Sampling
propagation
Feedback
sensors
Controllers

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

Cite this

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Learning identification control for model-based optoelectronic packaging. / Bhat, Shubham K.; Kurzweg, Timothy P.; Guez, Allon.

In: IEEE Journal on Selected Topics in Quantum Electronics, Vol. 12, No. 5, 01.09.2006, p. 945-951.

Research output: Contribution to journalArticle

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