本論文提出一種適用於一類具有內部連結之未知大尺度資料取樣非線性系統且具有閉迴路解藕特性的分散式模型化線性觀測器與軌跡追蹤器設計方法。首先利用離線的觀測器/卡爾曼濾波器鑑別方法計算出資料取樣非線性系統之適當階數(或低階)的分散式線性觀測器。然後此鑑別出來的觀測器可以進一步地以數位再設計方法來改善。接下來並提出一個具有高增益特性的分散式數位再設計之軌跡追蹤器設計方法，因此此閉迴路系統具有解藕的特性。所提出來的方法對於這種複雜的大尺度資料取樣系統不論其系統方程式為未知或已知皆相當簡單及有效。

Low-order modeling of decentralized linear observer and tracker for a class of unknown interconnected large-scale sampled-data nonlinear system with close-loop decoupling property is proposed in this thesis. First, the appropriate (low-) order decentralized linear observer for the sampled-data nonlinear system is determined by the off-line observer/Kalman filter identification (OKID) method. Then, the above observer has been further improved based on the digital redesign approach. Sequentially, the decentralized digital-redesign tracker with the high gain property is proposed, so that the closed-loop system has the decoupling property. The proposed approach is quite simple and effective for the complicate interconnected large-scale sampled-data system with know or unknown system.

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