本論文提出三種以伺服控制方法控制高度非線性的PUMA560機械手臂，分別為根據線性最佳化方法設計之最優化二次數位追蹤器、離線與在線觀測器/控制器鑑別方法的模型預測控制，隨之，一些針對高度非線性系統的系統辨識與伺服控制上之見解，也在本論文中被描述。首先，根據多輸入多輸出的非線性系統，我們使用線性最佳化方法找出此非線性系統之精確的狀態相關線性模型，接著，根據此狀態相關的線性系統，提出了最優化二次數位追蹤器，進而控制原來的PUMA 560機械手臂。此外本論文也分別提出了離線與在線觀測器/控制器鑑別方法，並應用於高度非線性的PUMA 560機械手臂控制。隨後，一種新型的觀測器/控制器鑑別方之模型預測控制也在本論文中提出。最後，針對上述三種方法的比較與見解也在結論中提出。

Three approaches for the servo control of the highly nonlinear PUMA 560 manipulator, i.e., an optimal linearization method-based linear quadratic digital tracker (LQDT), the off-line and on-line observer/control identification (OCID) method-based model predictive controls (MPC), are proposed in this thesis. Consequently, some insights on the system identification and servo control on the highly nonlinear systems are depicted in this thesis. First, for the multi-input multi-output (MIMO) nonlinear system, we use the optimal linearization method to find the explicit state-dependent linear model of this nonlinear system without any approximation. Then, the optimal linear quadratic digital tracker is proposed based on the explicit state-dependent linear model to control the original PUMA 560 manipulator. Besides, the off-line and on-line observer/control identification (OCID) methods are also proposed in this thesis for the system identification of highly nonlinear PUMA 560 manipulator. Sequentially, the OCID method-based MPC are newly proposed. Finally, some comparisons and insights into the above three methods are also presented in the conclusions.

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