Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems

碩士 === 國立成功大學 === 電機工程學系碩博士班 === 94 === A novel state-space self-tuning control methodology for a nonlinear stochastic hybrid system with stochastic/deterministic noise is proposed in this thesis. Via the optimal linearization approach, an adjustable NARMA-based noise model with estimated states can...

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Main Authors:	Chi-Chieh Kuang, 鄺智傑
Other Authors:	Jason S. H. Tsai
Format:	Others
Language:	en_US
Published:	2006
Online Access:	http://ndltd.ncl.edu.tw/handle/19425709035292447025

id	ndltd-TW-094NCKU5442032
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spelling	ndltd-TW-094NCKU54420322016-05-30T04:21:56Z http://ndltd.ncl.edu.tw/handle/19425709035292447025 Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems 適用於非線性隨機混合系統的嶄新ARMAX模型狀態空間自調式控制 Chi-Chieh Kuang 鄺智傑碩士國立成功大學電機工程學系碩博士班 94 A novel state-space self-tuning control methodology for a nonlinear stochastic hybrid system with stochastic/deterministic noise is proposed in this thesis. Via the optimal linearization approach, an adjustable NARMA-based noise model with estimated states can be constructed for the state-space self-tuning control in nonlinear continuous-time stochastic systems. In addition, a state-space self-tuning control scheme for the adaptive digital control of continuous-time multivariable nonlinear stochastic systems, which have unknown system parameters, measurement noise, deterministic noise, and inaccessible system states, is proposed. The proposed method enables the development of digitally implemental advanced control algorithms for nonlinear stochastic hybrid systems. Jason S. H. Tsai 蔡聖鴻 2006 學位論文 ; thesis 61 en_US
collection	NDLTD
language	en_US
format	Others
sources	NDLTD
description	碩士 === 國立成功大學 === 電機工程學系碩博士班 === 94 === A novel state-space self-tuning control methodology for a nonlinear stochastic hybrid system with stochastic/deterministic noise is proposed in this thesis. Via the optimal linearization approach, an adjustable NARMA-based noise model with estimated states can be constructed for the state-space self-tuning control in nonlinear continuous-time stochastic systems. In addition, a state-space self-tuning control scheme for the adaptive digital control of continuous-time multivariable nonlinear stochastic systems, which have unknown system parameters, measurement noise, deterministic noise, and inaccessible system states, is proposed. The proposed method enables the development of digitally implemental advanced control algorithms for nonlinear stochastic hybrid systems.
author2	Jason S. H. Tsai
author_facet	Jason S. H. Tsai Chi-Chieh Kuang 鄺智傑
author	Chi-Chieh Kuang 鄺智傑
spellingShingle	Chi-Chieh Kuang 鄺智傑 Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems
author_sort	Chi-Chieh Kuang
title	Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems
title_short	Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems
title_full	Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems
title_fullStr	Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems
title_full_unstemmed	Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems
title_sort	novel armax model for state-space self-tuning control of nonlinear stochastic hybrid systems
publishDate	2006
url	http://ndltd.ncl.edu.tw/handle/19425709035292447025
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Novel ARMAX Model for State-Space Self-Tuning Control of Nonlinear Stochastic Hybrid Systems

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