Masters Theses

Abstract

"This work first presents the development of a nearly-optimal control scheme and then evaluates the effectiveness of this nearly-optimal control scheme by comparing it to a non optimal controller in Paper I. It is shown that the proposed nearly-optimal scheme is a significant improvement over the non optimal one in both simulation and hardware tests. The test was carried out on a differentially driven robotic vehicle in both obstacle free and obstacle ridden environments. On the other hand, the controller introduced for the obstacle avoidance in Paper II will also function in the absence of obstacles so that no switching between controllers is required. The tests also show that the nearly optimal control scheme is still well within the capabilities of an embedded processor"--Abstract, page iv.

Advisor(s)

Sarangapani, Jagannathan, 1965-

Committee Member(s)

Acar, Levent
Zawodniok, Maciej Jan, 1975-

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Computer Engineering

Sponsor(s)

National Science Foundation (U.S.)

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2010

Journal article titles appearing in thesis/dissertation

  • Optimal control of mobile robot formations in discrete-time using neural networks
  • Obstacle avoidance with mobile robot formations using optimal control

Pagination

xi, 93 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2010 Bryan Michael Brenner, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Library of Congress Subject Headings

Mobile robots -- Design
Robots -- Control systems -- Design

Thesis Number

T 9721

Print OCLC #

730954219

Electronic OCLC #

911038377

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b8244129~S5

Comments

Financial support provided by the NSF grant ECCS#0621924 in the form of Graduate Research Assistantship

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