本論文旨在應用自我調整控制器做多變數時延系統的控制以及容錯控制。本文利用狀態空間自我調整控制器方法，對於輸入和系統有非同時延時的複雜的系統，可以自我調整出線性控制器加以有效控制。在被控系統的系統參數未知、系統和量測雜訊也未知、系統狀態不能直接取得的狀況下，本文推導其存在的等效線性非時延模型，此等效的線性非時延模型可以由自我調整控制器的系統參數估測過程中得之，因而線性控制器和觀測器可據以設計。這種方式，可以大大地簡化針對複雜被控系統的追蹤控制器設計。此外，本文將自我調整控制器加以修改，發展出一種對未知多變數隨機系統的容錯控制法。當被控系統有故障發生時，經由比較卡爾曼濾波器參數估測演算法的更新過程誤差，可以在自我調整控制器結構中做故障檢測，並且，經由重設卡爾曼濾波器估測演算法的估測參數的協方差矩陣，改善故障系統的參數估測，發展出加權矩陣重設法則，可用以做故障系統控制復原。此方法可以有效地復原當系統有突發性或逐漸性部份故障，以及控制輸入有突發性或逐漸性部份故障的容錯控制系統。

　　This dissertation is dedicated to develop the self-tuning control for some time-delayed systems and the fault tolerant control. Based on the state-space self-tuning control methodology, a complex stochastic system with input and state delays and deterministic disturbances can be controlled. In this approach, an equivalent delay-free linear model is obtained for the concerned system, which may have unknown system parameters, system and measurement noises, and inaccessible system states. The equivalent delay-free linear model is obtained in the estimating process of the self-tuning control loop, and then a linear controller and an observer are designed. The proposed method significantly simplifies the design and the implementation procedures of the tracker. Besides, by modifying the conventional self-tuning control, fault tolerant control schemes for unknown multivariable stochastic systems are also developed. For the detection of fault occurrence, a quantitative criterion is developed by comparing the innovation process errors occurring in the Kalman filter estimation algorithm. Also, for control recoveries of faulty systems, a weighting matrix resetting methodology is developed by adjusting and resetting the covariance matrices of parameter estimate obtained in the Kalman filter estimation algorithm to improve the parameter estimation of the faulty systems. The proposed method can effectively cope with partially abrupt and/or gradual system faults and/or input failures with fault detection.

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