本論文提出一種以比例積分微分濾波器之頻率塑型法為基礎的比例積分模型預測追蹤器，以及一種基於函數型觀測器的等效輸出干擾估測器，用於控制具有未知外部干擾和輸入限制的最小相位資料採樣系統。首先，經由比例積分微分濾波器之頻率塑型法，原系統被擴增，有更多用來吸引閉路極點的控制零點設置在指定位置，使系統的穩定性和追蹤性能加強。之後，由具有輸入限制之模型預測控制法在有輸入限制情況下決定控制律，使控制律易於應用在實務上。對於消除未知干擾引起的負面輸出影響方面，先引入等效輸入干擾的概念，再透過線性函數型觀測器和全階狀態觀測器，建構一種不受未知干擾的維度或秩數條件限制，基於狀態回授之等效輸入干擾估測器。最後以例題說明本論文提出的比例積分模型預測追蹤器和等效輸入干擾估測器的效用。

For the minimum-phase sampled-data system with unknown external disturbances and input constraints, a proportional-integral-differential (PID) filter-shaped PI-MPC (model predictive control) tracker and a functional observer-based equivalent-input-disturbance (EID) estimator have been proposed in this thesis. First, with the PID filter-based frequency shaping approach, the system is augmented and more control zeros are assigned at the specified locations to attract the closed-loop poles, such that the stability and tracking performance of the system can be enhanced. Then, the input-constrained MPC determines the optimal control law with input constraints to facilitate the implementation. For the cancellation of negative output effects induced by unknown disturbances, the concept of the EID is introduced first, then a state-feedback-based EID estimator is constructed by the linear functional observer and the full-order state observer, without any constraints on the dimension or rank condition of unknown disturbances. Lastly, the effectiveness of the proposed PID filter-shaped PI-MPC tracker with input constraints and EID estimator for the system with unknown disturbances is revealed by the illustrative examples.

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