在工業程序中，廣義最小變異量控制(GMVC)能夠減少隨機擾動的影響，使得程序輸出和目標值之間的變異量達到最小。傳統GMVC的設計缺乏一個系統化的方式來滿足被控程序的特定需求，例如設定目標值改變或確定性負載擾動發生時無法保證消除穩態偏移；在追求最小變異量時無法兼顧強健性的問題。

本論文提出內模式控制(IMC)架構下的改良式GMVC設計方法。在IMC架構下GMVC各個參數的定義與用途變得更為明確，可區分為消除穩態偏移的參數、增加強健性的參數和改善操作性能的參數。吾人據此提出數個系統化的參數設計法，首先指定兩個參數以保證消除穩態偏移，然後在三種強健性指標的限制下藉由調整其餘兩個參數來達到最佳的性能指標。

In industrial processes, generalized minimum variance control (GMVC) can reduce the influence from stochastic disturbances and minimize the variance between the process output and the target value. The conventional design of GMVC lacks a systematic way to satisfy specific requirements on the controlled process. For example, the elimination of the steady-state offset cannot be ensured when the target value changes or a deterministic disturbance occurs; the robustness problem cannot be dealt with in pursuit of the minimum variance.

This thesis proposes an improved GMVC design method in the IMC structure. In the IMC structure, the definition and use of each GMVC design parameter become clearer. These parameters can be distinguished into the one eliminating the steady-state offset, the one increasing robustness, and the one improving performance. We then develop several systematic methods for designing GMVC parameters. First, two parameters are specified to eliminate the steady-state offset. Then, the optimum performance index is achieved by adjusting the rest two parameters under the constraints of three robustness indices.

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