Masters Theses

Abstract

"A differentially steered nonholonomic mobile robot platform has been fabricated to implement and validate nonlinear control laws. The platform can also be used to validate hierarchical cooperative control techniques. As a first step towards building a fleet of autonomous robots, novel control methods are developed and implemented on the robot platform for trajectory tracking as well as point stabilization. As an extension to the development of nonlinear controllers, a novel reinforcement learning based neural network is developed to control a manipulation task for a micro-electro-mechanical system (MEMS). The nonlinear controllers developed for both the robot and the MEMS have online neural networks to compensate for the unknown nonlinear system dynamics"--Abstract, page iv.

Advisor(s)

Sarangapani, Jagannathan, 1965-
Balakrishnan, S. N.

Committee Member(s)

Agarwal, Sanjeev, 1971-

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Comments

The support received from the National Science Foundation grants ECS XXXXX and ECS 0296191 and Intelligent Systems Center for this research is greatly appreciated.

Research Center/Lab(s)

Intelligent Systems Center

Publisher

University of Missouri--Rolla

Publication Date

Fall 2005

Journal article titles appearing in thesis/dissertation

  • Control of a nonholonomic mobile robot
  • Neural network controller for manipulation of microscale objects

Pagination

viii, 42 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2005 Vijayakumar Janardhan, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Neural networks (Computer science)Robots -- Control systemsNonholonomic dynamical systemsMicroelectromechanical systems

Thesis Number

T 8896

Print OCLC #

71044152

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