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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.

In this study, the work-piece without using tailstock was considered as an elastic and deformable body under the external forces generated by the cutting tool. Such work-piece was studied by an Euler-Bernoulli beam, and a second order partial differential equation was established for the lateral forced vibrations. In addition, a model for the cutting tool vibration is also developed in a second order ordinary differential equation formulation. Combining these models permitted system full analysis and discussion of the interactions between work-piece and tool. Not only study the stability analysis of turning with using tailstock considering deflection in the previous cycle or not, but also analyze the difference of both. In chatter mechanism, considering the regenerative chatter, system characteristic equation could be yielded from the Laplace transformation of the dynamic equations. The frequency domain stability analyses and Nyquist Chart implied the governing equations of critical chip width for this case. During the machining process, the slot cutting was discussed. By the simulations, the conclusive results could be obtained in the following: larger the critical chip width would be resulted with various deflection method; the larger the critical chip width would be also resulted with considering lathe deflection in the previous cycle in high spindle speed. And the result obtained from rigid body case will always be the worst.

An Equivalent Current Injection (ECI) based Security-Constrained Optimal Power Flow (SCOPF) is presented in this paper and a Multiple Particle Swarm Optimization (MPSO) is developed for solving non-convex Optimal Power Flow problem. The OPF deals with both continuous and discrete control variables and is a mixed-integer OPF. The continuous control variables modeled are the active power output and generator-bus voltage magnitudes, while the discrete ones are the shunt capacitor devices. And first, security Analysis will be conducted before fault occurred in the system. Ranking method will be used to highlight the most severe event caused by the specific facility. Than, a preventive algorithm will make use of the contingency information, and could be kept the operator system security and avoided congestion when fault occurred.

This paper proposes a novel feedrate control scheme utilized in real-time non-uniform rational B-spline (NURBS) interpolation algorithm for the contouring control purpose. The objective is to improve the contour error performance to achieve high-precision standard. The proposed structure can provide the action that once the contour error is large in the relative sense, then the feedrate will be adequately reduced to provide sufficient time for controller to settle. By real-time adjusting the feedrate, contour error will not accumulate such that the precision can be effectively improved. Experiments are conducted to validate the effectiveness of the proposed method and comparison with other control methods is also arranged. All the obtained results indeed demonstrate the effectiveness of this method.

This paper proposes a novel feedrate interpolation strategy depending on the error feedback information. The proposed strategy incorporates the real-time non-uniform rational B-spline (NURBS) algorithm and is applied in a biaxial contouring stage system. The objective of the strategy is to improve the contouring accuracy to cope with the high-precision standard nowadays. The proposed method does achieve the control purpose that if the detected contouring performance is beyond a given specified value, then the feedrate controller will vary the actual feedrate to provide better contouring accuracy. By real-time adjusting the feedrate depending on the error feedback, contouring error will not accumulate such that the precision can be improved. Many experiments are conducted and the results do show the effectiveness of the proposed method.

This study develops and implements a SoC-based HW/SW (Hardware-Software) codesign for an intelligent diagnostic system. To improve the efficiency of the VLSI (Very Large Scale Integration) design process, the components of the intelligent diagnostic system are designed in the form of SIP (Silicon Intellectual Property) modules. The SIP modules, including the CPU module, the GPIO (General Purpose I/O) module and the NN (Neural Network) module, are then integrated to form the complete intelligent diagnostic system. In constructing the system, an embedded processor is employed to run software programs. In addition to integrating the hardware architecture, this study also develops application software, comprising a bootloader, a UARTcomm module and a main program for human-machine interface, to drive the embedded processor. The SoC-based HW/SW codesign method employed in this study increases the efficiency of the system design process and reduces the rebuild time. The results of the experimental trials verify the successful performance of the developed intelligent diagnostic system.

This paper presents preventive security-constrained optimal power flow (PSCOPF) with hybrid genetic-ant colony optimization (HGACO) is presented The PSCOPF can be divided into three steps involving security analysis, severest event selection, and preventive algorithm. First, Novel security analysis will be conducted before fault occurred in the system by current-based power flow technique. Second, ranking method will be used to highlight the most severe event caused by the specific facility. And finally, a preventive algorithm will make use of the contingency information, and could be kept the operator system security and avoided congestion when fault occurred. The HGACO is integrated with genetic algorithm and ant colony optimization, and the objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence.