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In the paper, a cloud-dust based intelligent maximum power analysis system for photovoltaic is proposed. In order to resolve NP problem for photovoltaic, factors of photovoltaic are integrated to cloud-dust based intelligent maximum power analysis system for computing. This study is the development of the maximum power analysis system for photovoltaic, to improve the solar panels effects of the different region and enable them to get maximum efficiency of the power generation. The design methodology of this study includes: (1) The monitoring and control Module (2) The prediction and evaluation module (3) The performance diagnosis module (4) The maintenance prescription module. At last, we can find the advantages of the cloud-dust based intelligent maximum power analysis system for photovoltaic. It increases overall competitive performance of products, reduces cost of products and consummation rates of human resources.

This paper studies the dynamic feedrate control problem for mechanical stages performing contouring actions. In modern researches, feedrate is considered as a dynamic factor instead of simple constant value in the traditional methods, and should be properly controlled to meet higher precision standard nowadays. To incorporate the dynamic feedrate in the path interpolation, the so called non-uniform rational B-spline (NURBS) algorithm is utilized to form the fundamental real-time interpolation structure of this research. The result of a sophisticated intelligent feedrate control design is then proposed where the system feedrate is real-time determined based on both the feedback of the path curvature and the measured contour error. Experiments and comparative studies for free-form paths are also conducted where the results show that the proposed design indeed can provide significant precision improvement in overall contouring performance in contrast to the traditional method. Therefore, the effectiveness and the goal of the proposed method can be verified which suggests that the entire scheme has the potential for real industrial applications.

This paper proposes the development of a two-axis sun tracking solar energy system using fuzzy logic as intelligent quality policy. To achieve maximum efficiency for solar panels, it is necessary to follow the sun’s path in the sky. Therefore, the architecture for the two-axis sun tracking solar energy system uses software to control the hardware. The hardware comprises (i) solar cells; (ii) lead-acid batteries; (iii) a gear box; (iv) a stepping motor; and (v) a light detection circuit, while the software comprises (i) a detection system; (ii) a fuzzy tracking controller; and (iii) a database system. A fuzzy logic controller is designed as the software architecture of the system to decide the timing for tracking the sun. The nearest position that results in receiving direct sunlight is obtained from the database. Our system is fully automatic in a changing environment and takes into account meteorological changes and the effects of the external environment arising from a malfunction. This approach reduces the number of starting motors and results in smaller energy loss in cloudy, cloud mask, or unstable weather conditions.