本博士論文中，具有多重離散式及分散式時間延遲的類比中性系統之有限時間/無限時間的最佳/次最佳混合追蹤控制問題將被格式化並且研究。為了去解這追蹤控制問題，一種新的交替式（間接式）數位再設計趨進結合一些方法和計技巧被提出來設計具有預測特性的數位追蹤器，這些可以簡述如下：(i)設計以預測型為基礎的數位追蹤器：首先，選擇性能指標的權重矩陣使其具有高增益的特性。然後，牛頓中心和線性插補公式，以及一種新修正的矩形規則，被利用來建構相關的離散模型。最後，透過離散時間最佳控制理論，將可得到以預測型為基礎的數位追蹤器。(ii)設計以觀測器為基礎的數位追蹤器：當回授狀態不可測量時，新的擴大式數位再設計觀測器被提出來估測擴大式離散時間狀態向量。然後，藉由結合已發展出的數位追蹤器增益和數位觀測器，以觀測器為基礎的數位追蹤器被發展來完成想要的追蹤控制。(iii)設計以觀測器為基礎的反覆學習數位追蹤器：因為反覆學習控制有能力將低精確高重複性的系統轉換成高精確的系統。因此，這個反覆學習的控制技術被利用來設計以觀測器為基礎的最佳反覆學習數位追蹤器。(iv)設計以進化規劃為基礎的數位追蹤器：取進化規劃方法論在全部最佳化的優勢，吾人使用這進化規劃去搜尋最佳權重矩陣。然後，結合高增益的特性， 反覆學習控制的技術，和進化規劃演算法，以便發展出以進化規劃為基礎的最佳數位追蹤器，去改善以進化規劃為基礎的混合控制中性系統之追蹤性能。本博士論文所開發的數位控制律經由舉例和電腦模擬，證實能夠有效地實現追蹤控制的目標。深信，本文提出的方法和結果將有助於文獻上對混合中性多時延系統在追蹤控制方面之理論與實現的完整性。

In this dissertation, the finite-time/infinite-time optimal/suboptimal hybrid tracking control problems for analog neutral systems with multiple discrete and distributed time delays are formatted and studied. In order to solve the tracking control problems, a new alternative (indirect) digital redesign approach together with some methods and techniques is proposed to design the digital trackers, which can be briefly stated as follows: (i) Design the prediction-based digital trackers: First, select the weighting matrices of the performance index to have the high-gain property. Then, the Newton center and linear interpolation formula, together with a newly modified rectangular ruler, are utilized to construct the associate discrete models. Finally, by the discrete-time optimal control theory, the prediction-based digital trackers can be obtained. (ii) Design the observer-based digital trackers: When the feedback states are unmeasured, the new augmented digital redesign observers are proposed to estimate the augmented discrete-time state vector. Then, by combining the developed digital tracker gains and digital observer, the observer-based digital trackers are developed to achieve the desired tracking control. (iii) Design the observer-based iterative learning digital tracker: Since the iterative learning control is capable of turning a low-accuracy, high-repeatability system into a high-accuracy system. Thus, the iterative learning control technique is utilized to design the observer-based optimal iterative learning digital trackers. (iv) Design the evolutionary programming (EP)-based digital trackers: Take the advantage of EP methodology for global optimization, we use the EP to search the optimal weighting matrices. Then, by combining the high-gain property, iterative learning control technique, and EP algorithm, the EP-based digital trackers are developed to improve the tracking performance of the EP-based hybrid control neutral system. The effectiveness of developed digital control laws in this dissertation are demonstrated by illustrative examples. It is believed that the presented methods and results of this dissertation is helpful to complete the theories and implements in the literature of optimal tracking control of hybrid neutral multiple time-delay systems.

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