本篇論文提出一個適用於未知閉迴路系統結合強制型特徵系統實現演算法的新型觀測/控制器鑑別法之容錯控制輸入補償。此鑑別法的目標是用以滿足當控制器發生損壞時，我們可以透過觀測/控制器鑑別法來加以補償修復，並盡可能保持良好的軌跡追蹤能力。首先利用觀測/卡爾曼濾波器鑑別法來鑑別一個未知線性/非線性系統，轉換求得其等效數學模型，透過此等效數學模型來做為分析與設計觀測器與控制器之工具，接著，我們再運用觀測/控制器鑑別法來鑑別與求得此閉迴路系統之等效數學模型，藉由鑑別出的模型參數來分析控制器當下的狀態，作為系統容錯控制輸入補償的依據；然而，傳統觀測/控制器鑑別法的補償能力不佳，在初始狀態的軌跡追蹤誤差甚大，因此，本篇論文提出一種強制型特徵系統實現演算法來改進軌跡追蹤的效能，最後，以許多範例來證明與闡述該設計的有效性。

This thesis proposes a new observer/controller identification (OCID) with the fault-tolerant control-input for the unknown closed-loop system with the assigned eigensystem realization algorithm (ERA).The principle idea is to satisfy when the controller of the system is broken, we can use the OCID to do compensation for the controller, without losing the good tracking performance as possible. First, the observer/Kalman filter identification (OKID) is utilized to identify the unknown linear/nonlinear system into the equivalent mathematical model. The equivalent mathematical model is used as an analytic and designed tool for the controller and observer. And then, we use OCID to identify the closed-loop system into the equivalent mathematical model. The parameters of the model can be used to analyze the current status of the controller in order to do compensation of the fault-tolerant control-input for the system. However, the traditional OCID has poor performance in compensation case. That is the tracking error in the initial state is large. Therefore, this thesis offers a method called the assigned ERA to improve the tracking performance. Finally, illustrative examples demonstrate the effectiveness of the proposed design.

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