Search

El presente trabajo de investigación propone el diseño de un algoritmo de control difuso Takagi-Sugeno-Kang, basado en inecuaciones matriciales lineales y técnicas de optimización convexa, para la ampliación del rango de operación de un sistema no lineal. Esto es estabilizar el sistema y dar seguimiento de la referencia para un intervalo del punto de operación elegido arbitrariamente pero cuidando de las limitaciones reales de la planta. El algoritmo de control consiste en un compensador (matriz de ganancia y estimador) difuso además del diseño de un sistema de seguimiento tipo 1 para sistemas sin integrador, en este caso se trabajará con un sistema de levitación magnética, haciendo uso de un esquema extendido difuso. El esquema de control se diseñó de tal manera que garantice la estabilidad y el desempeño deseado del sistema en lazo cerrado. Este sistema se implementó y evaluó en Matlab y Simulink, además del uso de la Toolbox Yalmip para Matlab. This paper proposes the design of a Takagi-Sugeno-Kang Control Fuzzy algorithm based on Linear Matrix Inequalities and convex optimization techniques, therefore extending to a wide working range around the equilibrium point for the Non-linear system. This means to stabilize the system and signal tracking the reference, in a chose working range, regarding the actual limitation of the system. The control algorithm consists in a fuzzy compensator (gain matrix and estimator) with a Type 1 signal tracking system for plants without integrator, for instance a Magnetic Levitator System, using an extended fuzzy scheme. So the schematic control is designed to guarantee the stability and desire performance for the closed loop system. This algorithm has been implemented and evaluated using Matlab and Simulink, also using Yalmip Toolbox for Matlab.

La implementación de un método de ensayo asegura la confiabilidad analítica del resultado de ensayo, razón por la cual el presente trabajo aborda la implementación del método analítico descrito en el Standard Methods 3111 D - Direct Nitrous Oxide - Acetylene Flame Method para la determinación de bario, en la matriz de agua residual, utilizando un espectrómetro de absorción atómica. Está implementación tiene el enfoque del sistema de gestión de calidad de laboratorios de ensayo ISO/IEC 17025:2005, siendo los parámetros estadísticos evaluados: la exactitud (veracidad y precisión), límite de detección del método, límite de cuantificación, rango de trabajo, linealidad, sensibilidad y robustez. Palabras clave.- Espectrómetro de absorción atómica, Bario, Implementación, Exactitud, Límite de detección del método, Agua residual, ISO/IEC 17025. ABSTRACTThe implementation of a test method ensures the analytical reliability of the test result, reason why the present paper deals with the implementation of the analytical method described in the Standard Methods 3111 D - Direct Nitrous Oxide - Acetylene Flame Method for the determination of barium in the matrix of wastewater, using an atomic absorption spectrometer. It is implementation has the approach of the system of management of quality of testing laboratories ISO/IEC 17025: 2005, being evaluated statistical parameters: accuracy (trueness and precision), method detection limit, quantification limit, working range, linearity, sensitivity and robustness. Keywords.- Atomic absorption spectrometer, Barium, Implementation, Accuracy, Method detection limit, Wastewater, ISO/IEC 17025.

Increasing the working calibration range by means of artificial neural networks for the determination of cadmium by graphite furnace atomic absorption spectrometry (Hernández C., Edwin A.; Ávila G., Rita M.; Rivas E., Francklin I.; Burguera, Marcela y Burguera, José Luis) Abstract Feed-forward artificial neural networks (ANNs), trained with the generalized delta rule, were evaluated for modeling the non-linear behavior of calibration curves and increasing the working range for the determination of cadmium by graphite furnace atomic absorption spectrometry (GFAAS). Selection of this analyte was made on the basis of its short linear range (up to 4.0 µg l-1). Two-layer neural networks, comprising one node in the input layer (linear transfer function); a variable number of neurons in the hidden layer (sigmoid transfer functions), and a single neuron (linear transfer function) in the output layer were assessed for such a purpose. The (1:2:1) neural network was selected on the basis of its capacity to adequately model the working calibration curve in the range of study (0-22.0 µg l-1 Cd). The latter resulted in a nearly six fold increase in the working range. Cadmium was determined in the certified reference material "Trace Elements in DrinkingWater" (High Purity Standards, Lot No. 490915) at four concentration levels (2.0, 4.0, 8.0 and 12.0 µg l-1 Cd), which were experimentally within and above the linear dynamic range (LDR). No significant differences (P < 0.05) were found between the expected concentrations and the results obtained by means of the neural network. The proposed method was compared with the conventional "dilution" approach, and with fitting the working calibration curve by means of a second-order polynomial. Modeling by means of an ANN represents an alternative calibration technique, for its use helps in reducing sample manipulation (due to the extension of the working calibration range), and may provide higher accuracy of the determinations in the non-linear portion of the curve (as a result of the better fitness of the model). Artículo publicado en: Talanta 63 (2004) 425-431 ehernandez@ucla.edu.ve pascu@ula.ve burguera@ula.ve ritaavila@ucla.edu.ve rivas@ula.ve Nivel monográfico