Announcement for Downloading full text filePlease respect the Copyright Act.
All digital full text dissertation and theses from this website are authorized the copyright owners. These copyrighted full-text dissertation and theses can be only used for academic, research and non-commercial purposes. Users of this website can search, read, and print for personal usage. In respect of the Copyright Act of the Republic of China, please do not reproduce, distribute, change, or edit the content of these dissertations and theses without any permission. Please do not create any work based upon a pre-existing work by reproduction, Adaptation, Distribution or other means.
URN etd-0904107-111957 Statistics This thesis had been viewed 2448 times. Download 1016 times. Author Po-Jen Cheng Author's Email Address No Public. Department Electrical Engineering Year 2006 Semester 2 Degree Master Type of Document Master's Thesis Language English Page Count 22 Title Observer-Based Adaptive Controller Design for a Class of Nonaffine Nonlinear Systems via Fuzzy-Neural Method Keyword fuzzy-neural adaptive observer nonlinear nonaffine nonaffine nonlinear observer adaptive fuzzy-neural Abstract In this paper, an observer-based adaptive fuzzy-neural control (AFNC) scheme is developed for the (SISO) nonaffine nonlinear systems with unknown structure of nonlinearities. Because of using a suitable observer, the proposed adaptive fuzzyneural algorithm does not require the state variables to be measurable. By parameterizing the nonaffine part of the system, the original system is simplified, and the weight update law of the fuzzy-neural controller is derived. Afterwards, we design a supervisory control to estimate the approximation error of the system. Based on Lyapunov theory, the stability of the closed-loop system can be guaranteed, and all signals involved are bounded. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper. Advisor Committee Wen-Shyong Yu - advisor
Files Date of Defense 2007-07-30 Date of Submission 2007-09-04