Evolutionary-Programming-Based Tracker for Hybrid Chaotic Interval Systems

碩士 === 國立成功大學 === 電機工程學系碩博士班 === 91 === The nominal optimal tracker for the chaotic nonlinear interval system is first proposed in this thesis. First, we use an optimal linearization methodology to obtain the exact linear models of a class of discrete-time nonlinear time-invariant systems at operati...

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Bibliographic Details
Main Authors: Ken-Ming Chen, 陳耿銘
Other Authors: Sheng-Hong Tsai
Format: Others
Language:en_US
Published: 2003
Online Access:http://ndltd.ncl.edu.tw/handle/64749397219651009490
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Summary:碩士 === 國立成功大學 === 電機工程學系碩博士班 === 91 === The nominal optimal tracker for the chaotic nonlinear interval system is first proposed in this thesis. First, we use an optimal linearization methodology to obtain the exact linear models of a class of discrete-time nonlinear time-invariant systems at operating states of interest, so that the conventional tracker can work for the nonlinear systems. A prediction-based digital tracker using the state-matching digital redesign method from a predesigned, state-feedback, continuous-time tracker for a hybrid chaotic system is presented. Then, we discuss the system has interval parameters. The interval system treated has interval and bounded parameters. The proposed evolutionary programming (EP) technique yields the strongest species to survive, reproduces themselves, and creates more outstanding offspring. The worst-case realization of the sampled-data nonlinear uncertain systems represented by the interval form with respect to the implemented "best" tracker is also found in this thesis for demonstrating the effectiveness of the proposed tracker.