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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/30841

Title: 具乘積雜訊之線性參數變化隨機Takagi-Sugeno模糊系統的模糊控制器與模糊觀測器設計
Fuzzy Controller and Observer Design for Linear Parameter Varying Stochastic Takagi-Sugeno Fuzzy Systems with Multiplicative Noises
Authors: 張文哲
Contributors: NTOU:Department of Marine Engineering
國立臺灣海洋大學:輪機工程學系
Date: 2011-08
Issue Date: 2012-04-13T01:49:12Z
Publisher: 行政院國家科學委員會
Abstract: 摘要:具乘積雜訊之線性參數變化隨機 Takagi-Sugeno 模糊系統的 模糊控制器與模糊觀測器設計 近年來,學者們針對隨機系統的研究與討論投入了大量的努力與心血,其中Langevin 方程式被廣泛的應用於描述隨機系統,該方程式透過狀態與雜訊相乘的項次來描述隨機系 統中之隨機行為,因此,其非線性隨機系統具有雙線性系統之特性。對此系統,Itô 準則被 發展來探討並進行穩定性分析之過程。 Takagi-Sugeno (T-S) 模糊模型提供了一個有效且有用的方法來近似非線性系統。以 T-S 模糊模型為基礎,我們可透過平行分佈補償(PDC)的觀念設計穩定的模糊控制器,利用 T-S 模糊控制方法,我們可以使用線性控制理論來針對非線性系統進行穩定性分析與控制 器的設計。此外,線性參數變化(LPV)控制技術在最近亦受到增益排程領域相關控制學者專 家的注意,因為非線性系統可以透過參數的Jacobian 線性化使之轉化成以LPV 的模型來表 示。本計畫中,我們將利用Langevin 方程式架構出非線性隨機系統的LPV 隨機T-S 模糊模 型。為了探討雜訊對非線性隨機系統之影響,我們所考慮的LPV 隨機T-S 模糊模型也將加 入外部雜訊的干擾。利用被動理論,本計畫將開發模糊控制器與觀測器以使非線性隨機系 統達到消除外部雜訊干擾之性能。 在本計畫中,我們提出了三年的研究計畫,期望針對具乘積雜訊之連續型與離散型非 線性隨機系統,探討滿足系統穩定性與被動性之控制問題。在第一年計畫中,我們首先利 用LPV 隨機T-S 模糊模型考慮具乘積雜訊非線性隨機系統的穩定性分析與解析,我們將發 展一狀態迴授之模糊控制器設計程序,以使具乘積雜訊之LPV 隨機T-S 模糊模型達到穩 定。第二年,我們將針對具乘積雜訊非線性隨機系統探討以觀測器作為迴授之模糊控制器 十一、研究計畫中英文摘要:請就本計畫要點作一概述,並依本計畫性質自訂關鍵詞。 (一)計畫中文摘要。(五百字以內) 表 C011 共 4 頁 第 2 頁 設計。透過模糊觀測器的設計,在系統狀態無法完全量測的情況下,我們亦可以用觀測器 作為迴授信號,以完成利用狀態估測迴授來設計穩定模糊控制器的目標。在第三年的計畫 中,被動特性將被考慮在針對具乘積雜訊之時間延遲LPV 隨機T-S 模糊模型的模糊控制器 與模糊觀測器設計中。結合里亞普諾夫函數 (Lyapunov function)及被動特性限制,一個以 模糊觀測器為基礎的模糊控制器設計方法將被發展來滿足連續型與離散型具乘積雜訊之時 間延遲LPV 隨機T-S 模糊模型的穩定性與被動特性。有關本計畫的內容,我們將以下表作 為整合說明。
Abstract:Fuzzy Controller and Observer Design for Linear Parameter Varying Stochastic Takagi-Sugeno Fuzzy Systems with Multiplicative Noises Recently, many researchers pay their attentions to study the control problem for the stochastic systems. In stochastic modeling techniques, the Langevin equation is widely applied for describing the behaviors of stochastic systems. The Langevin equation uses the multiplicative noise terms to structure the stochastic systems; hence, the stochastic systems can be considered as bilinear systems. For stochastic systems with multiplicative noise terms, the Itô’s formula was developed for analyzing the stability of stochastic systems. The Takagi-Sugeno (T-S) fuzzy model provides an effective and useful technique to approximate nonlineaties of nonlinear systems. Based on the T-S fuzzy model, the concept of Parallel Distribution Compensated (PDC) technique can be employed to design stable fuzzy controller and fuzzy observer. By using the T-S fuzzy control approach, the linear control theory can be used to analyze and synthesize the stability of nonlinear systems. Besides, research attention has been primarily focused on Linear Parameter Varying (LPV) control techniques in gain scheduling community recently. Because nonlinear plant can be reformulated as LPV model via parameterized Jacobian linearization. The LPV stochastic T-S fuzzy model structured by Langevin equation is proposed to represent the nonlinear stochastic systems in this proposal. In order to discuss the disturbance effect on nonlinear stochastic systems, the LPV stochastic T-S fuzzy model with external disturbance is considered. By applying the passivity theory, a fuzzy controller and observer will be developed in this proposal such that the nonlinear stochastic systems achieve the attenuation performance. In this proposal, we will carry on our research results for guaranteeing the stability and passivity of continuous and discrete nonlinear stochastic systems with multiplicative noises in three years. In the first year, we will discuss the stability analysis and synthesis of nonlinear stochastic systems with multiplicative noises via LPV stochastic T-S fuzzy model. We will develop a state feedback fuzzy controller design process for LPV stochastic T-S fuzzy model with multiplicative noises. In the second year, the observer-based fuzzy control for the nonlinear stochastic systems with multiplicative noises is studied. With fuzzy observer, the information of system states can be measured to realize the fuzzy controller with estimated state feedback law when the state variables cannot be measured. In the third year, the passivity property is considered in the fuzzy controller and fuzzy observer design for the time-delay LPV stochastic T-S fuzzy model with multiplicative noises. Combining the Lyapunov function and passivity constraint, an observer-based fuzzy controller design approach is developed to achieve the stability and passivity for the continuous and discrete time-delay LPV stochastic T-S fuzzy model with multiplicative noises. The contents of this proposal can be collated as the following table.
Relation: NSC100-2221-E019-023
URI: http://ntour.ntou.edu.tw/handle/987654321/30841
Appears in Collections:[輪機工程學系] 研究計畫

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