模糊類神經網路於非仿射型非線性系統之觀察器暨適應控制器設計

Observer-Based Adaptive Controller Design for a Class of Nonaffine Nonlinear Systems via Fuzzy-Neural Method

鄭博仁(Po-Jen Cheng)

指導教授 ： 游文雄

大同大學/電機資訊學院/電機工程學系所/碩士(2007年)

摘要

在本文中, 我們在一個具有非線性性質的未知結構且單輸入單輸出(SISO)的非仿射(nonaffine) 非線性系統裡發展出一個以觀察器為基礎的適應模糊類神經控制器方案。由於使用適當的觀察器, 所提出的適應模糊類神經演算法並不需要狀態向量是可量測到的。藉由參數化系統的非仿射(nonaffine) 部分, 我們可將原來之系統化簡, 並且獲得模糊類神經控制器的權重更新法則。然後, 我們會設計一個監視控制來消除系統的近似誤差。基於李普諾夫(Lyapunov)理論, 我們可以驗證出閉迴路系統的穩定性, 且系統所包含的所有信號都是有界的。為了顯示所提出的方法的可行性, 本文的模擬結果將說明一切。

關鍵字

非仿射 ； 非線性 ； 觀察器 ； 適應 ； 模糊類神經

並列摘要

In this paper, an observer-based adaptive fuzzy-neural control (AFNC) scheme is developed for the (SISO) nonaffine nonlinear systems with unknown structure of nonlinearities. Because of using a suitable observer, the proposed adaptive fuzzyneural algorithm does not require the state variables to be measurable. By parameterizing the nonaffine part of the system, the original system is simplified, and the weight update law of the fuzzy-neural controller is derived. Afterwards, we design a supervisory control to estimate the approximation error of the system. Based on Lyapunov theory, the stability of the closed-loop system can be guaranteed, and all signals involved are bounded. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.

並列關鍵字

nonaffine ； nonlinear ； observer ； adaptive ； fuzzy-neural

參考文獻

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