| Summary: | 碩士 === 建國科技大學 === 電子工程系暨研究所 === 100 === Although increasing the reusing times of samples in the data-reusing least-mean-square (DR-LMS) algorithms could decreases the error of the estimation system, the computational complexity required is also increased. Therefore, a method with adjusting the reusing times of samples in DR-LMS algorithms based on the status of error convergence of the system is proposed which dynamically increases or decreases the necessary computational complexity during estimation processing. Accordingly, this research proposes a method to use a fuzzy logic-controlled DR-LMS (Fuzzy DR-LMS) to adjust the parameters of membership functions in the fuzzy logic mechanism to investigate their effects on the reusing times of DR-LMS algorithm for enhancing the estimation convergence.
Recently, numerous tracking techniques that improve the supplying capacity of solar energy have been presented in the literature. On the conditions of sufficient data of illumination intensity being applied to the tracking algorithms, the resulted more accurate voltages at maximum power can hence be obtained. In addition, this study also proposes a non-tracking algorithm that uses the data of given illumination intensity and voltage at maximum power, and adopts the estimation ability of the adaptive filter with the least-mean-square algorithm to avoid the complicated solar energy tracking algorithm for maximum power estimation.
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