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Implementation Of An Undergraduate Intelligent Control Laboratory

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Conference

2001 Annual Conference

Location

Albuquerque, New Mexico

Publication Date

June 24, 2001

Start Date

June 24, 2001

End Date

June 27, 2001

ISSN

2153-5965

Page Count

7

Page Numbers

6.552.1 - 6.552.7

DOI

10.18260/1-2--9350

Permanent URL

https://peer.asee.org/9350

Download Count

497

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Paper Authors

author page

Ali Zilouchian

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Session 1526

1 Implementation of an Undergraduate Intelligent Control Laboratory

Ali Zilouchian

Department of Electrical Engineering Florida Atlantic University Boca Raton, Florida 33431

Abstract Recently, the author has been awarded a grant by National Science Foundation (NSF) in order to develop an interdisciplinary intelligent control laboratory. The objective of the laboratory is to substantially improve the instructional capability of undergraduate instruction in intelligent systems analysis and design. The project addresses simple, robust, and effective implementation of soft computing techniques for several industrial applications including Servo Systems, Heat Trainers, and Visual Component Inspection Stations. The development is carried out through the adaptation of innovative industrial design techniques, incorporation of real-time sensory interfacing and other applicable industrial advances, which have been already utilized in several manufacturing industries such as Motorola Inc. The implementation of an undergraduate intelligent system laboratory can serve as a model for other institution in the nation.

I. Introduction

During the last four decades, many model based control techniques have been proposed by the researchers. However, most of these methods have often been subordinated to the development of mathematical theories that dealt with over-idealized issues bearing little relation to practice. In reality, many processes are model free systems where their mathematical representations are not necessarily available.

On the other hand, during the last decade, the critical links between complexity, ambiguity, robustness, and performance of various processes have become increasingly evident. This may explain the dominant role of emerging “intelligent systems” in recent years [1]. However, the definition of intelligent systems is a function of expectations and the status of present knowledge: Perhaps the “intelligent systems” of today are the “classical systems” of tomorrow. ____________________________________________________ 1. This project is partially supported by NSF under grant # 99-50310

“Proceeding of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright 2001, American Society for Engineering Education”

Zilouchian, A. (2001, June), Implementation Of An Undergraduate Intelligent Control Laboratory Paper presented at 2001 Annual Conference, Albuquerque, New Mexico. 10.18260/1-2--9350

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