“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.
Lu, Wen F.
Liou, Frank W.
Mechanical and Aerospace Engineering
M.S. in Mechanical Engineering
University of Missouri--Rolla
x, 94 pages
© 2000 Qingwen Huang, All rights reserved.
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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://merlin.lib.umsystem.edu/record=b4498024~S5
Huang, Qingwen, "NURBS adaptive neural-fuzzy inference system and its application in real time control for SDM rapid prototyping system" (2000). Masters Theses. 1956.
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