本論文實作，具相關性分析系統識別功能之數位控制切換式電源轉換器。採用新穎的數位電源技術，結合相關性分析之系統識別技術，使數位控制器具備監測電源轉換系統之頻率響應的能力。對於相關性分析之不理想效應造成的問題，提出以適應調節滑動視窗平滑技術(adaptive sliding window smoothing, ASWS)，改善頻率響應監測結果。此外，亦利用本論文之數位控制器具備相關性分析系統識別能力，監測數位補償器與迴路增益之頻率響應。本論文以FPGA為實驗平台，透過SignalTapII傳輸監測資料至電腦端進行分析處理。並且利用Agilent網路分析儀進行量測作為對照，證明監測結果的正確性，以及驗證提出之方法確實能夠提升監測準確範圍，改善結果與預期相符。最後將驗證過的矽智財以TSMC 1P6M 0.18um Cell-Based製程下線。

This thesis presents a digitally-controlled switched-mode power supply(SMPS) with correlation-based system identification. An improvement to the correlation-based system identification technique, adaptive sliding window smoothing(ASWS), is proposed to improve the accuracy of the frequency response identification, particularly at high frequencies near the desired loop-gain bandwidth frequency. Additionally, an extension to the correlation-based system identification is proposed that allows identification of the digital compensator and loop-gain frequency response. The digital controller and part of identification module are implemented using an Altera DE2 FPGA. The data of the results of the identification are sent to the computer through SignalTapII (an embedded FPGA logic analyzer). Experimental results show that the proposed ASWS technique can be used to improves identified frequency response accurately and smoothly. The proposed digital controller has been implemented in TSMC 1P6M 0.18μm CMOS technology.

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