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URN etd-0713104-230026 Statistics This thesis had been viewed 2502 times. Download 969 times. Author Mao-An Wang Author's Email Address firstname.lastname@example.org Department Electrical Engineering Year 2003 Semester 2 Degree Master Type of Document Master's Thesis Language English Page Count 55 Title ADAPTIVE FUZZY CONTROL OF UNCERTAIN
NONLINEAR SYSTEMS REPRESENTED
BY INPUT-OUTPUT MODELS
Keyword nonlinear systems high-gain observer adaptive control adaptive control high-gain observer nonlinear systems Abstract In this thesis, an adaptive fuzzy control scheme is developed for a single-input -single-output unknown nonlinear system which can be represented by an input-output model with unmodeled dynamics. We propose the adaptive fuzzy control schemes, and the fuzzy approximator is used to approximate the unknown nonlinear functions in the nonlinear system with unmodeled dynamics and uncertain nonlinearity. This scheme does not need the assumption that all the states of the nonlinear system are available for feedback and unknown parameters to satisfy the linear dependence condition. With the proposed control scheme, all the variables in the closed-loop system are bounded in the presence of unmodeled dynamics and bounded disturbances. The design process is simple. First we assume that the output and its derivatives are available for feedback and design the adaptive fuzzy controller as a state feedback controller. Then we saturate the controller outside a domain of interest and use a high-gain observer to estimate the derivative of output. We prove that the proposed output feedback adaptive fuzzy control can recover the performance achieved under the state feedback controller. At last, some simulation results are given to demonstrate the applicability of the proposed method. Advisor Committee Chiang-Cheng Chiang - advisor
none - co-chair
none - co-chair
Files Date of Defense 2004-07-13 Date of Submission 2004-07-13