Doctoral Dissertations

Keywords and Phrases

Chatter; Hypothesis Testing; Modeling; Robotics; Validation; Vibration

Abstract

"Robots are used in a wide variety of manufacturing applications, but machining applications in which robots can excel are limited by their lower accuracy and stiffness relative to traditional CNC machines. This work is composed of two parts: one to evaluate a robot’s accuracy and one to compensate for the vibrations of the robot due to its lower stiffness.

In order to evaluate whether a robot has the necessary accuracy to perform a given machining task, Paper 1 discusses a novel Model Invalidation method. This methodology provides a statistical framework as well as a measurement strategy for determining if a robot is unable to meet a given accuracy requirement. This paper shows through simulation that the Model Invalidation method more accurately evaluates the error in a robot model as compared to other commonly used methods for accuracy identification. Additionally, the Model Invalidation method is shown in implementation on an experimental robot system and results are discussed.

While chatter has always been a widely studied topic in the field of machining, due to their low stiffness, chatter in robots is typically due to deflection of the robot arm itself rather than the deflection of the tool or part. In order to reduce the robot deflections, Paper 2 discusses a structure for designing a vibration suppression controller using an H∞ framework. Using this framework, control algorithms are designed for an experimental robot machining system to suppress vibrations in both one and two directions, and the results of these controls are discussed" -- Abstract, p. iv

Advisor(s)

Bristow, Douglas A.

Committee Member(s)

Landers, Robert G.
Leu, M. C. (Ming-Chuan)
Adekpedjou, Akim
Song, Yun Seong

Department(s)

Mechanical and Aerospace Engineering

Degree Name

Ph. D. in Mechanical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2024

Pagination

x, 51 pages

Note about bibliography

Includes_bibliographical_references_(pages 27 & 47-48)

Rights

©2024 Patrick Bazzoli , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12372

Electronic OCLC #

1460021564

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