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Teaching Neural Network Control System Design Using a Low-Cost Rapid Control Prototyping Platform

[+] Author Affiliations
Francisco Franquiz, Alecia Hurst, Yan Tang

Embry-Riddle Aeronautical University, Daytona Beach, FL

Paper No. IMECE2013-65568, pp. V005T05A004; 7 pages
doi:10.1115/IMECE2013-65568
From:
  • ASME 2013 International Mechanical Engineering Congress and Exposition
  • Volume 5: Education and Globalization
  • San Diego, California, USA, November 15–21, 2013
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5627-7
  • Copyright © 2013 by ASME

abstract

This paper presents the use of a low-cost rapid control prototyping platform, HILINK, in teaching a graduate course on neural network control system design for mechanical engineering students. The HILINK platform offers a seamless interface between physical plants and Simulink for implementation of hardware-in-the-loop real-time control systems. With HILINK, student can quickly build a neural network controller for applications using Neural Network Toolbox in Simulink. As a result, students can use one single environment for both computer simulation and hardware implementation to understand theories and tackle practical issues in a limited time frame. The paper presents the experimental setup and implementation process of the NARMA-L2 controller for DC motor speed control, and demonstrates the convenience and effectiveness of using HILINK in developing a neural network controller.

Copyright © 2013 by ASME

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