本論文首先針對穩定、積分及不穩定連續程序，提出一完整有效的鑑別方法。考慮到含偏位替續器實驗可針對各種穩定性的程序，在穩定閉環操作下激發出包含豐富程序訊息的輸入/輸出數據，該鑑別法直接利用替續器所產生之數據，發展時間加權積分轉換來將微分方程模式轉換成代數方程式，然後應用最小平方演算法來估測訊息未知程序的階次、時延以及模式參數。該法僅需少量的實驗數據就可獲得極佳的鑑別結果，且對量測雜訊及模式結構不吻合的情況具有高強韌性。此外，對於任意指定之模式階次，亦可輕易地估測適當的時延來取得簡化模式。

　　在鑑別實驗過程中，各種不同動態且未量測的負載擾動會造成嚴重的估測誤差。針對這個問題，本文提出以時間及頻率加權積分轉換式來進行程序鑑別。當有未知負載擾動發生於替續器測試實驗時，所提鑑別方法可排除負載擾動的影響以獲得正確的參數模式。另外，藉由在替續器和程序之間放置一積分元件，該法亦可作為模式簡化技術，利用所產生之量測數據，輕易地決定任意指定階次所對應之適當時延，並獲得一個與重要頻率應答吻合的簡化模式。相較於其他須不斷反覆修正以消除負載擾動導致之訊號扭曲的方法，該法可直接利用扭曲數據來得到滿意的鑑別結果。

　　為了滿足特定的設計規格，工業上有一些程序必須選擇開環不穩定操作點。本文將含一個或兩個不穩定極點的程序區分成三種動態類型，每一種動態類型對於控制器設計皆具有特殊的重要性。針對這些不穩定動態類型，本文推導出增益及替續器可安定性所須滿足的必要及充分條件，同時依不同的實驗操作條件，使用兩種非線性元件(其中之一為替續器)來激發程序輸入/輸出數據，並發展一有效步驟來鑑別具有適當階次(二階或三階)的不穩定時延模式。最後根據鑑別模式，以加權ISE為目標函數來設計最佳PID控制器。所設計之控制器可同時處理負載擾動及設定點改變，並且藉由滿足最大增益邊距來加強其強韌性。對於非線性連續攪拌槽反應器程序，所提之鑑別及控制器設計方法皆能獲得極佳的結果。

　　有了正確之參數模式，本論文接著針對各種穩定、積分及不穩定程序動態，提出一控制器設計法，可藉由指定期望之閉環應答，輕易獲得具有簡單結構的強健控制器(PI、PID或高階型)。一般而言，雖然高階控制器可達成較佳的控制性能，但其強韌性卻較差，而且傳統的增益和相位邊距指標常無法偵測出此現象。因此，本文提出一新型強韌性指標來取代傳統的增益邊距，最佳強健控制器設計即可在相位邊距和該指標的不等式限制下，透過將負載擾動產生之誤差積分最小化來完成。同時透過對控制演算法的巧妙調整，可讓該控制器在處理設定點改變時，亦能產生具有低超越量之快速應答。

　　多數化工程序的動態是非線性的，當有較大的設定點改變或負載擾動發生時，傳統線性控制器常難以達成理想的操作品質。因此，本文針對非線性穩定及不穩定程序，提出利用連續線性化的觀念來設計非線性控制器的方法。此法可在整個操作範圍直接利用現有的線性控制技術，也能確實反映一階項動態隨著操作點不同而變化的情況。對於非線性液位槽及連續攪拌槽反應器系統，模擬結果顯示所合成之非線性控制器確實可有效改善系統之動態應答。

　　This dissertation first addresses the complete identification of stable, integrating and unstable continuous processes. Despite the stability of the process, a biased relay experiment can be performed to provide abundant process input-output data in stable closed-loop operation. Using the relay-induced data, an effective method is developed to estimate the order and time delay as well as the model parameters for a process with unknown information. The method is based on a time-weighted integral transform that converts continuous data sets into a number of algebraic equations for least-squares parameter estimation. The method utilizes merely a small amount of experimental data and is robust with respect to measurement noise and model structure mismatch. Furthermore, it can easily be applied as a model reduction technique by estimating an apparent delay for any specified order.

　　Unmeasured load disturbances with widely different dynamics could cause significant errors in process identification. To remedy this issue, this dissertation presents a time- and frequency-weighted integral transform. The resultant identification method can determine the order and delay of the process and provide an accurate parametric model in the face of unknown load disturbances arising in relay tests. It can also be applied as a model reduction technique by inserting an integrating element between the relay and the process for plant tests. On the basis of the produced data, the technique can easily infer an apparent delay for any specified order and provide a reduced model valid for all frequencies of interest. In contrast with those methods that take iterative corrective action to remove distortion, the proposed method yields satisfactory results directly from disturbance-distorted data.

　　There are some instances where a process must be operated at an open-loop unstable steady state to meet certain design specifications. In this dissertation, the process dynamics, involving one or two unstable poles, are classified into three types, which are of paramount importance in controller design. Necessary and sufficient conditions are addressed for gain and relay stabilizability of such dynamics. Two nonlinear elements, one being a relay, are employed to excite rich process input-output data for identification of three types of unstable processes. A design procedure is then developed to identify an unstable delayed model of appropriate order (second or third order), followed by the optimal PID controller design established based on the weighted ISE index. The resultant controller can cope with both load disturbances and set-point changes simultaneously and provide good robustness by satisfying the maximum gain margin criterion. The method is tested with good results on a nonlinear CSTR process.

　　With a parametric model, a method is developed to design a robust controller for a wide range of stable, integrating and unstable process dynamics. The controller with a simple structure can be a PI, PID or higher-order type, whose parameters are determined simply by specifying the desired closed-loop response. However, the design of high-order controllers may result in good performance but very poor robustness, which is not detectable by the conventional indices of gain and phase margins. To avoid this, a robustness index is proposed as a replacement for the gain margin. Optimal controller design is then achievable by minimizing a designated error integral criterion for a load disturbance subject to inequality constraints on phase margin and the new robustness index. By a clever adjustment in control algorithms, the optimal design for a load disturbance can also give a fast response with a desired overshoot for a step set point change.

　　The dynamics of most chemical processes are nonlinear. The conventional linear control techniques cannot achieve satisfactory performance quality when larger variations appear in set point or load. Therefore, a method is proposed to design a nonlinear controller by means of the concept of successive linearization for nonlinear stable and unstable processes. The main advantage of this approach is that the available linear control techniques can be applied around the whole equilibrium manifold. Moreover, it can account for the variations of the first-order terms with respect to the operating points. For nonlinear level-tank and continuous stirred tank reactor systems, the simulation results reveal that the synthesized nonlinear controller indeed can improve the dynamic responses of the system.

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