Browsing by Keyword "Smart control"
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Item Adaptive fixturing system for the smart and flexible positioning of large volume workpieces in the wind-power sector(2014) Olaiz, Edurne; Zulaika, Juanjo; Veiga, Fernando; Puerto, Mildred; Gorrotxategi, Ainhoa; Tecnalia Research & Innovation; MAQUINAS; FACTORYQuality and productivity in a manufacturing process depend considerably on the toolkits used, whose basic functions are to position the component into a right position relative to the cutting tool and to hold the component tightly to avoid displacements during the machining. In this document the design of a smart and adaptive fixture is presented for the accurate positioning of a planet carrier with very strict requirements of tolerances and for an intelligent adjustment during the machining process when required. This device will allow the manufacturer reducing the manual inspections, automatizing the adjustment tasks and improving the machining process setup time, increasing consequently the productivity and achieving the required accuracy and the required geometrical quality of the part. The development of the intelligent fixturing will be focused mainly in the conception of a high precision actuator capable of moving the large part with the required tolerance. Moreover, a testbench has been developed that will allow validating the actuator, assuring therefore its applicability in the future industrialization of the fixture device.Item Very short-term parametric ambient temperature confidence interval forecasting to compute key control parameters for photovoltaic generators(2022-06) Rodríguez, Fermín; Insausti, Xabier; Etxezarreta, Gorka; Galarza, Ainhoa; Guerrero, Josep M.; Tecnalia Research & Innovation; DIGITAL ENERGYIn recent years, various forecasters have been developed to decrease the uncertainty related to the intermittent nature of photovoltaic generation. While the vast majority of these forecasters are usually just focused on deterministic or probabilistic prediction points, few studies have been carried out in relation to prediction intervals. In increasing the reliability of photovoltaic generators, being able to set a confidence level is as important as the forecaster's accuracy. For instance, changes in ambient temperature or solar irradiation produce variations in photovoltaic generators’ output power as well as in control parameters such as cell temperature and open voltage circuit. Therefore, the aim of this paper is to develop a new mathematical model to quantify the confidence interval of ambient temperature in the next 10 min. Several error metrics, such as the prediction interval coverage percentage, the Winkler score and the Skill score, are calculated for 95%, 90% and 85% confidence levels to analyse the reliability of the developed model. In all cases, the prediction interval coverage percentage is higher than the selected confidence interval, which means that the estimation model is valid for practical photovoltaic applications.