NURBS adaptive neural-fuzzy inference system and its application in real time control for SDM rapid prototyping system

Author

Qingwen Huang

Abstract

“This thesis describes the concept and performance of NURBS (Non-Uniform Rational B-Spline) ANFIS (Adaptive Neural-Fuzzy Inference System) models and controllers for nonlinear systems. ANFIS is constructed based on Sugeno fuzzy model. High order Sugeno fuzzy model with proposed NURBS as a membership function is first introduced. Simulation shows that it gives improved performance compared to zero order Sugeno fuzzy model. A mathematical proof of the NURBS ANFIS as a university approximator is also given in this thesis

Based on the NURBS ANFIS, several intelligent control architectures are proposed to provide the appropriate inputs to the SDM (Shape Deposition Manufacturing) Rapid Prototyping System, so that desired product quality is obtain. The properties of the proposed architectures are studies through both software simulation and experiments”--Abstract, page iii.

Advisor(s)

Lu, Wen F.
Liou, Frank W.

Committee Member(s)

Fu, Yongjian

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Summer 2000

Pagination

x, 94 pages

Note about bibliography

Includes bibliographical references (pages 90-93).

Rights

© 2000 Qingwen Huang, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 7807

Print OCLC #

45687055

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.

Recommended Citation

Huang, Qingwen, "NURBS adaptive neural-fuzzy inference system and its application in real time control for SDM rapid prototyping system" (2000). Masters Theses. 1956.
https://scholarsmine.mst.edu/masters_theses/1956