- 學位論文
自調式控制系統設計與應用
Designs and Applications of Self-Tuning Control Systems
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摘要
本論文之主旨係在於發展自調式控制系統，並廣泛的應用在一些具有非線性且不確定系統之閉迴路控制上。首先，針對非線性系統提出一個自調式比例積分微分控制系統，為驗證所提出的控制系統的有效度，所提出的控制系統被應用到雙軸機械手臂與混沌系統上。接著，針對直流轉換器提出一個自調式模糊控制系統，並以現場可编程邏輯閘陣列對所提出的控制系統進行硬體驗證。在控制工程上混沌同步控制是近年熱門的議題，因混沌系統具高度非線性，且混沌系統因初始值的微小差異將造成系統特性相當大的差異，為此本論文提出以小波函數為基底的類神經網路，提出自調式小波類神經網路同步控制系統對混沌系統進行同步控制。最後，透過結構式自調法則，本論文提出一個自組織模糊類神經網路，將所提出的控制系統應用在混沌電路的模擬及直流馬達控制的硬體驗證。經由模擬與實作的結果顯示，對於這些具有不確定量且非線性之系統，本論文所提出的控制系統均能達到令人滿意的控制性能。
並列摘要
The purpose of this dissertation is to develop some self-tuning control systems, and apply them to some uncertain nonlinear closed-loop control systems. Firstly, a self-tunning proportional-integral-derivative (SPID) control system is proposed. This SPID control system is applied to two nonlinear systems to illustrate its effectiveness. Next, a self-tuning fuzzy control (SFC) system is designed for the DC-DC converters. This SFC system is realized on a field programmable gate array chip to control the DC-DC converters. The behavior of the chaotic systems is highly nonlinear unpredictable, so how to synchronize this kind of systems becomes an impotrant subject in control engineering. Therefore, a self-tuning neuro-wavelet synchronization control (SNSC) is proposed for the chaotic systems. Finally, through the constructing self-tuning laws, a self-organizing fuzzy neural control (SFNC) system is proposed. This SFNC system is applied to a chaotic circuit and/or a DC motor control system to illustrate its effectiveness. In summary, the simulation and experimental results have illustrated the control performance and efficiency of theabove design methods.
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