以氣體做為動力的系統在作動過程中，受氣壓、熱流、不確定時變參數變化的影響，導致系統狀態參數難以準確獲得；以傳統的PID控制方法要達到所需控制效能及精度相當困難，故採用進階控制方法來提升效能的需求也日益增加，像是屬於智慧型控制方法之一的模糊控制。模糊控制方法因具有不需數學模型的優點，常被應用於氣動系統的定位控制。雖然模糊控制可適用於非線性系統，卻難以確保系統的強健性，而強健控制方法則在系統具有不確定參數時仍可確保一定程度的控制效能。有鑑於此，有學者提出結合智慧型控制與強健控制來提升控制效能和結合各自優點，例如適應性模糊強健控制。雖然此法的結果證實混合控制的可行性，但如何改善系統動態的週期性誤差仍有待探討。本研究提出一混合反覆/智慧型控制架構來進行氣壓致動系統的運動控制；除了保留智慧型控制於非線性氣壓系統的既有效果，亦藉由反覆控制改善系統的週期性動態控制效能，並以此控制架構達到改善系統整體效能。但若採用智慧型控制方法會使得混合反覆控制架構難以驗證其強健穩定度，為此本文提出結合強健μ控制與反覆控制之混合控制架構來確保系統的強健性。在研究過程中以一具有300 kg重負載和複雜耦合關係的四軸氣壓致動平台做為實驗系統，並給予週期性訊號進行反覆上下運動的追跡控制，且驗證所提之混合反覆/智慧型控制方法可改善系統整體效能。藉由連續切換至不同操作區間持續進行動態追跡實驗，結果證實了所提混合反覆/強健控制方法的優異效能與強健性。本文並提出以權重分配法求得混合反覆/強健控制的輸出最佳權重。最後，本研究將混合反覆/智慧型控制與混合反覆/強健控制應用於氣壓致動平台的單軸追跡、強健性測試及多軸同步控制驗證所提控制方法的實用性。

Due to the influences of uncertain time varying parameters caused by air pressure and thermal flow in pneumatic dynamic systems, it is sometimes difficult to obtain detailed model for control design and attain satisfactory performance if using traditional methods such as PID control. As a result, non-model based advanced control such as fuzzy control and intelligent control related methods have been widely applied to pneumatic position control in recent years. Although applicable to nonlinear pneumatic systems, the main issue of the fuzzy design is its difficulty in analyzing stability and robustness. Therefore, applying robust control which considers known system uncertainties during the design process is another popular alternative for pneumatic servo designers. Moreover, some researchers have also combined the advantages of fuzzy control and robust control as Adaptive Fuzzy Sliding Mode Control to improve the pneumatic control performance and justified the feasibility of such hybrid control idea. However, discussion on how to reduce periodic errors occurred in the repetitive motion process for better pneumatic position control is still very limited. This thesis first proposes a hybrid repetitive/intelligent control architecture for precision motion control of pneumatic actuating systems, in which intelligent control is used to handle the nonlinearities and the repetitive control is used to improve periodic tracking performance. To perform robust analysis and assure robust stability in this hybrid control architecture, this study also replaces the intelligent controller with a robust μ controller designed through a D-K iteration process. Periodic up-and-down motion experimental results on a 300 kg heavy duty pneumatic actuating table demonstrate the effectiveness of the proposed control methods. Particularly, this work applies a Weighted Average Method to find the optimal performance weighing between given two control actions while not violating the robust stability. The results show that the proposed hybrid control with fine tuning achieves good tracking performance even at perturbed operating regions.

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