Author

A. Mohammadi

Publication Date

2018

Document Type

Dissertation/Thesis

First Advisor

Ryu, Ji-Chul

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Mechanical Engineering

LCSH

Robotics; Artificial intelligence; Mechanical engineering

Abstract

Controller design of a nonlinear system is in general very difficult. One way to avoid such complexity is using a simplified model so that certain nonlinear control techniques can be easily applied. Using a linearized model could make the controller design even simpler. However, some control error is inevitable with a simplified model. Therefore, in this thesis, a neural network-based approach is proposed in order to compensate for the errors caused by using a simplified dynamic model. The base controller which is designed by using the simplified dynamic model will be compensated by a PID controller with adjustable gains. A neural network is used to update the PID gains during control process. Finally, the outputs of the NN-based PID compensator and the base controller are added together to control the actual nonlinear system. This way, the NN-based PID compensator tries to compensate for the effects of the ignored nonlinear terms of the dynamic model. The performance of the proposed control method is verified on the ball-on-plate system that is built for this study. Approximate feedback linearization is applied as the base controller on a simplified decoupled dynamic model. A NN-based PID compensator is added to each decoupled ball-on-beam system. Experimental results that show better stabilization and trajectory tracking performance are provided and discussed in the thesis.

Comments

Advisors: Ji-Chul Ryu.||Committee members: Sachit Butail; Brianno D. Coller.||Includes illustrations.||Includes bibliographical references.

Extent

89 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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