傳統系統鑑別的方法，大多是在時域或頻域裡，對於量測訊號之分析而進一步作系統鑑別。 近幾年來，發展出許多使用時-頻域技巧：小波分析於系統鑑別領域的技術。 本論文旨在提出一利用Daubechies小波函數展開之系統鑑別理論，來鑑別出主動式四極磁浮軸承系統運動方程式之參數。 鑑別過程則是利用Daubechies小波基底展開系統運動方程式，並且在對應之子空間利用最小誤差平方觀念求解，同時與特徵系統實現運算法作一比較。 本文所提出之鑑別法則，藉由數值模擬與實際之系統，驗證其可行性。 本研究所使用之測試設備是以dSPACE DS-1104為主體所建立並且搭配MATLAB/Simulink程式語言。 由數值模擬及實驗結果可知：本論文所提出之小波鑑別理論具有較佳之收斂性及準確性。

Most traditional methods in system identification are based on the analysis of measured signal in either time or frequency domain. In recent years, some technologies in time-frequency domain which utilize wavelet analysis in the context of system identification were developed. The purpose of this thesis is to develop an algorithm based upon Daubechies wavelet expansions to identify unknown system parameters of the 4-pole active magnetic bearing systems (AMBs). The procedure stems from the equation of motion obtained by Daubechies wavelet and means of Least Squared Method. The wavelet identification method is compared with another populary-used method: Eigensysem Realization Algorithm (ERA). The proposed algorithms were examined by numerical simulations and experiments. The test rig is equipped with dSPACE DS-1104 and MATLAB/Simulink. The results of numerical simulations and experiments verify that the Wavelets System Identification Method has better efficacy in convergence and accuracy.

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