Abstract-To explore the design of solar power management circuit, the fuzzy logic control algorithm based on MPPT, which has fast control speed and good environment robustness, is adopted as the control algorithm. In addition, the MPPT solar battery charge and discharge power management circuit is designed and successfully applied in the on-line measurement projects of dielectric loss of wireless sensor network in Jilin Province LG Electronics Company. The results show that the charging efficiency of solar battery charge and discharge power management circuit can reach above 80%, and the current of static power management circuit is less than 1mA. In different light intensities, the dynamic power management is intelligently carried out. At last, it is concluded that the stability and reliability of circuit are quite high.Keywords-Wireless sensor, power management, circuit design IntroductionIn the research on solar power supply, the control algorithms of MPPT in the past are divided into the following three categories: indirect control method based on parameter selection, direct control method based on sampled data, and intelligent control method based on modern control theory. Among them, the algorithm based on parameter selection is comparatively simple, but it cannot adapt to the influence of environment change on the parameters of solar panel. The control method based on sampled data is dynamic, which makes the maximum power point tracking according to environmental conditions, but the tracking is too slow. The MPPT algorithm based on the modern control theory makes up for the shortcomings of the above two algorithms, and it can achieve better maximum power point tracking. Compared with the previous two algorithms, this algorithm is more complex. Fuzzy logic control algorithm has the characteristics of fast control speed, good environment robustness and simple algorithm realization. As a result, it is chosen as the control algorithm for further study.

A novel personal identification method based on the fusion of multi-finger knuckleprints is proposed in this paper. The identification process can be divided into the following stages: extracting and matching the knuckleprint's line feature, fusing of the matching scores of the multi-finger knucklerprints to get the total matching score and then certifying the identity of the user. The approach was tested on a database of 98 people (1,579 Knuckleprint images). The experimental results showed the effectiveness of the method: it improved the correct recognition rate to 96.62% which is more than 6 percentages higher than the best result of using a single finger knuckleprint.

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