Robust design optimization for control systems with uncertainties

Author

Luis Prado

Abstract

"A direct method to improve the reliability of a control system with uncertainties may present tremendous implementation and numerical difficulties. The need for alternative methods to generate reliability and robust design in control systems leads the introduction of probability engineering in this area. Most of the studies in robust design use uniform distributions to characterize uncertainties. The proposed idea is to generate a maximum value of an objective function. Techniques used in this study assume a normal probabilistic distribution. The objective is to increase the quality or to reduce the cost of a linear control system by designing it with different values. To complement this study, a reliability-based design for linear and nonlinear systems that uses probability engineering concepts has been developed"--Abstract, page iii.

Advisor(s)

Balakrishnan, S. N.
Du, Xiaoping

Committee Member(s)

Ramakrishnan, Sreeram
Landers, Robert G.

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Fall 2006

Pagination

viii, 80 pages

Rights

© 2006 Luis Prado, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Subject Headings

Control theory
Engineering design -- Mathematical models
Monte Carlo method
Reliability (Engineering)

Thesis Number

T 9077

Print OCLC #

123566265

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

Recommended Citation

Prado, Luis, "Robust design optimization for control systems with uncertainties" (2006). Masters Theses. 5873.
https://scholarsmine.mst.edu/masters_theses/5873