在這個研究裡，非線性隨機系統對於參數時變的問題，我們提供了一個模糊轉換穩定度的方法藉由輸出回授控制。多模組轉換方法已經被使用去處理線性時變參數系統。換言之，Takagi-Sugeno (TS) 模糊建模系統通常被使用去近似非線性非時變系統。結合多模組轉換方法和模糊建模系統，並且利用模糊輸出回授控制和模糊轉換建模系統被提供去對付非線性時變隨機系統穩定度的問題。為了去降低近似誤差和外部干擾的影響， 模糊觀測狀態回饋轉換控制可以最小化估測誤差的 所規範的 上界在 的規範在一個被期許的值之下。在這些條件之下， 模糊觀測狀態回饋轉換控制能夠被改善藉由線性矩陣不等式 (LMIs), 線性矩陣不等式能夠允許convex最佳化過程去解決非線性時變的強健 控制問題。最後，模擬例子是被提供的去證實 模糊觀測狀態回饋轉換控制方法。
第一章 簡介
實際上的應用，動態非線性系統一般都是存在時變參數或結構，因此控制器的設計是困難的去處理，尤其是在干擾不知道或者存在不確定的因素之下。所以我們利用以下要點來對付動態非線性系統。
1. 結合多模組轉換方法和模糊建模系統來對付隨機非線性時變系統。
2. 模糊輸出回授控制和模糊轉換建模系統被提供去對付非線性時變隨機系統穩定度的問題。
3. 利用 模糊觀測狀態回饋轉換控制最小化估測誤差。
第二章 系統模型與架構
本章主要介紹隨機非線性轉換系統與以模糊理論和likelihood function為基礎的架構，這些數學模型可以讓大家知道如何得到一個整合量測信號。而以模糊理論和likelihood function為基礎的架構可以知道演算彼此之間關係，此章分成下列兩個部分來介紹：
A. 系統模型
B. 估測誤差模型建構
最後得到系統模式與以模糊理論和likelihood function為基礎的架構將在下一章被使用。
第三章 穩定度分析
本章主要分析我們所建立模型的穩定度，為了使估測誤差在穩定狀態下估測誤差是否能趨近於0。
第四章 模糊觀測狀態回饋轉換控制設計
本章主要介紹以模糊理論和likelihood function為基礎的演算法如何運用數學推導找出影響精切度的參數。此章包含五個部分來介紹：
A. Hinf 模糊轉換控制器設計
B. H2 模糊轉換控制器設計
C. H2/Hinf模糊轉換控制器設計
D. 估測誤差值最小化設計
E. Likelihood function演算法
這將可使我們知道誤差大小及找出影響我們提出方法的干擾源及複雜度。
第五章 模擬結果
在此章節中，我們提出以模糊理論和likelihood function為基礎的演算法，去對付一些隨機非線性時變系統，去探討方法的可行性。
第六章 討論
在此篇論文研究中，我們提出以模糊理論和likelihood function為基礎的演算法。這將是一個很堅韌性方法，將來可運用在實際控制系統來對付隨機非線性時變系統中估測問題。

In this study, the problem of robust control for nonlinear stochastic systems subject to time-varying parameter is treated by a proposed switching fuzzy stabilization scheme via output feedback. Switching multiple-modeling approach has been used to deal with linear systems with time-varying parameters or structure. Conventionally, Takagi-Sugeno (TS) fuzzy modeling method is usually adopted to approximate the nonlinear time-invariant systems, but not suitable for nonlinear time-varying systems. Combining the switching multiple-modeling approach and TS fuzzy modeling method, a robust fuzzy observer-based controller, based on the switching TS fuzzy model, is proposed for the stabilization of the nonlinear time-varying stochastic systems. In order to mitigate the model approximation error and external disturbance in the systems, the proposed H2/Hinf switching fuzzy observer-based control achieves H2 suboptimal control and Hinf attenuation of external disturbance simultaneously. The conditions for the existence of the proposed H2/Hinf switching fuzzy observer-based controller are provided in terms of linear matrix inequalities (LMIs), allowing the use of standard convex optimization procedures to solve the proposed robust H2/Hinf output control design problem for nonlinear time-varying stochastic systems. Finally, numerical simulations are provided to illustrate the design procedure and to confirm the performance of the proposed robust H2/Hinf switching fuzzy observer-based controller for nonlinear time-varying stochastic systems.

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