An Observer-Based Tracker for Hybrid Interval Chaotic Systems with Saturating Actuators: The Choas-Evolutionary-Programming Apporach

• Main Authors: Kuang-Ting Liu, 劉光庭
• Other Authors: Sheng-Hong Tsai
• Format: Others
• Language: en_US
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/44298203443640561695

碩士 === 國立成功大學 === 電機工程學系碩博士班 === 92 === A novel evolutionary-programming (EP) algorithm including chaotic variable named chaos-evolutionary-programming algorithm (CEPA) has been proposed in this thesis. Due to the nature of chaotic variable, i.e. pseudo-randomness, ergodicity and irregularity, the evolutional process of CEPA makes the individuals of subgenerations distributed ergodically in the defined space and circumvents the premature of the individuals of subgenerations. Then a dual-rate observer-based tracker for a hybrid interval chaotic system with saturating actuators by using the CEPA is developed. The CEPA can search many local minimum or maximum in parallel and thereby increasing the probability of finding the global one. An illustrative example is presented to demonstrate the effectiveness of the proposed algorithm.