MODELADO ADAPTATIVO PARA CELDAS DE MANUFACTURA FLEXIBLE USANDO REDES DE PETRI INTERPRETADAS (ADAPTIVE MODELING OF FLEXIBLE MANUFACTURING CELLS USING INTERPRETED PETRI NETS)

Resumen Debido a las características de producción que presentan las celdas de manufactura flexible es necesario contar con modelos capaces de representar su comportamiento para posteriormente analizar propiedades como la ausencia de bloqueos o para implementar controladores. El objetivo es presentar un enfoque de modelado adaptativo basado en el proceso de identificación asintótico para celdas de manufactura flexible utilizando redes de Petri interpretadas. La principal contribución es que con este enfoque se pueden construir modelos a partir de ciclos de producción observados durante la ejecución del sistema. Esto permite actualizar el modelo calculado cada vez que se presente un nuevo comportamiento generado por diferentes planes de producción. El principio de modelado consiste en leer las señales de salida del sistema y calcular la estructura de una red de Petri interpretada. Los modelos obtenidos utilizando este enfoque son equivalentes a los calculados con otras herramientas. Palabras Clave: Modelado, Redes de Petri, Sistemas de Manufactura Flexible. Abstract Given the production characteristics of flexible manufacturing cells, it is necessary to have adaptable models capable of representing their behavior to analyze properties such as the absence of deadlocks or to implement controllers. The objective is to present an adaptive modeling approach based on the asymptotic identification process for flexible manufacturing cells using interpreted Petri nets. The main contribution is that using this approach models can be built from production cycles observed during the execution of the system. This fact allows updating the model each time a new behavior generated by different production plans occurs. The modeling approach consists in reading the output signals of the system to compute the structure of an interpreted Petri net. The models obtained using this approach are equivalent to those computed using other techniques. Keywords: Flexible Manufacturing Systems, Modeling, Petri nets

DETECCIÓN ACTIVA DE FALTAS EN SISTEMAS DE EVENTOS DISCRETOS

ResumenEl objetivo de este trabajo es presentar una propuesta de solución de Diagnóstico Activo en Sistemas de Eventos Discretos modelado por redes de Petri. La propuesta se basa en un controlador llamado Circuito de Regulación Inteligente que reduce la distancia relativa entre las transiciones que modelan faltas y las del resto de la red de Petri, permitiendo la detección y diagnóstico de faltas mientras se mantiene la vivacidad del sistema y se reduce la flexibilidad del sistema sólo en los estados requeridos. Finalmente, los resultados presentados se ilustran en un ejemplo.Palabras Claves: Detección activa, diagnosticabilidad, redes de Petri, sistemas de eventos discretos. ACTIVE FAULT DETECTION IN DISCRETE EVENT SYSTEMSAbstractThe aim of this work is to present a proposal of Active Diagnosis in Discrete Event Systems modeled by Petri nets. This approach is based on a controller named Intelligent Regulation Circuit which reduces the relative distance among the system transition allow in the detection and diagnosis of faults while maintaining the liveness of the system. Finally, the results presented are illustrated by an example.Keywords: Active detection, diagnosability, discrete event system, Petri nets

Stability Analysis for Autonomous Dynamical Switched Systems through Nonconventional Lyapunov Functions

The stability of autonomous dynamical switched systems is analyzed by means of multiple Lyapunov functions. The stability theorems given in this paper have finite number of conditions to check. It is shown that linear functions can be used as Lyapunov functions. An example of an exponentially asymptotically stable switched system formed by four unstable systems is also given

Tuning of a TS Fuzzy Output Regulator Using the Steepest Descent Approach and ANFIS

The exact output regulation problem for Takagi-Sugeno (TS) fuzzy models, designed from linear local subsystems, may have a solution if input matrices are the same for every local linear subsystem. Unfortunately, such a condition is difficult to accomplish in general. Therefore, in this work, an adaptive network-based fuzzy inference system (ANFIS) is integrated into the fuzzy controller in order to obtain the optimal fuzzy membership functions yielding adequate combination of the local regulators such that the output regulation error in steady-state is reduced, avoiding in this way the aforementioned condition. In comparison with the steepest descent method employed for tuning fuzzy controllers, ANFIS approximates the mappings between local regulators with membership functions which are not necessary known functions as Gaussian bell (gbell), sigmoidal, and triangular membership functions. Due to the structure of the fuzzy controller, Levenberg-Marquardt method is employed during the training of ANFIS

Retos Sobre el Modelado del Transistor de Compuerta Flotante de Múltiples Entradas en Circuitos Integrados

Resumen: En este artículo se presentan las consideraciones que hay que adoptar para el uso del transistor de compuerta flotante de múltiples entradas para el diseño de circuitos integrados analógicos. Para ello se presentan las principales características de este transistor así como sus principales ventajas con respecto al transistor MOSFET convencional que este dispositivo ofrece. También, se exponen los principales problemas que han frenado el uso de este dispositivo en el ámbito comercial debido a la falta de modelos precisos. Palabras clave: CMOS, Analógico, Circuitos, Integrados, Compuerta-flotante, muy bajo voltaj

Recursive Least Squares for a Manipulator which Learns by Demonstration

[EN] In this work, a control system is developed to allow a manipulator to learn and plan trajectories from demonstrations given by the hand of an user. The input of data is acquired by a sensor, and its behavior is learned through an automatic learning algorithm based on the recursive least squares. A trajectory profile of interpolators to stretches is used to avoid the impulsive jerk on manipulators motion. Direct and inverse kinematics analysis is done for obtaining the joints variables values of the manipulator. A dynamic model is created using Newton-Euler formulation. A proportional derivative control is applied to the system. The monitoring and control systems are implemented in an embedded platform for testing purposes.[ES] En este trabajo, se desarrolla un sistema de control automatizado para permitir que un manipulador aprenda y planifique las trayectorias a partir de las demostraciones dadas por la mano de un usuario. La entrada de datos es adquirida por un sensor, y se aprende su comportamiento a través de un algoritmo de aprendizaje automático basado en los mínimos cuadrados recursivos. Se utiliza un perfil de trayectoria de interpoladores a tramos para evitar el movimiento impulsivo del manipulador. Se realiza el análisis de las cinemáticas directa e inversa para obtener los valores de las variables articulares para el manipulador. Se crea un modelo dinámico usando la formulación de Newton-Euler. Se aplica un control proporcional derivativo al sistema. Los sistemas de monitoreo y control se implementan en una plataforma embebida para fines de prueba.Los autores agradecen al editor y a los revisores por sus valiosos comentarios y sugerencias que permitieron mejorar esta investigación significativamente. Así como al Instituto Politécnico Nacional, al Consejo Nacional de Ciencia y Tecnología (CONACYT), y a la Secretaría de Investigación y Posgrado (SIP) por el apoyo otorgado.Rubio, JDJ.; García, E.; Aquino, G.; Aguilar-Ibáñez, C.; Pacheco, J.; Meda-Campaña, JA. (2019). Mínimos Cuadrados Recursivos para un Manipulador que Aprende por Demostración. Revista Iberoamericana de Automática e Informática. 16(2):147-158. https://doi.org/10.4995/riai.2019.8899SWORD14715816

Synchronization of Discrete-Time Chaotic Fuzzy Systems by means of Fuzzy Output Regulation Using Genetic Algorithm

The synchronization of chaotic systems, described by discrete-time T-S fuzzy models, is treated by means of fuzzy output regulation theory. The conditions for designing a discrete-time output regulator are given in this paper. Besides, when the system does not fulfill the conditions for exact tracking, a new regulator based on genetic algorithms is considered. The genetic algorithms are used to approximate the adequate membership functions, which allow the adequate combination of local regulators. As a result, the tracking error is significantly reduced. Both the Complete Synchronization and the Generalized Synchronization problem are studied. Some numerical examples are used to illustrate the effectiveness of the proposed approach

Role of age and comorbidities in mortality of patients with infective endocarditis

Purpose: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. Methods: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015. Patients were stratified into three age groups:<65 years, 65 to 80 years, and = 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. Results: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 = 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients =80 years who underwent surgery were significantly lower compared with other age groups (14.3%, 65 years; 20.5%, 65-79 years; 31.3%, =80 years). In-hospital mortality was lower in the <65-year group (20.3%, <65 years;30.1%, 65-79 years;34.7%, =80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%, =80 years; p = 0.003).Independent predictors of mortality were age = 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI = 3 (HR:1.62; 95% CI:1.39–1.88), and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared, the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. Conclusion: There were no differences in the clinical presentation of IE between the groups. Age = 80 years, high comorbidity (measured by CCI), and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

A novel algorithm for the modeling of complex processes

summary:In this investigation, a new algorithm is developed for the updating of a neural network. It is concentrated in a fuzzy transition between the recursive least square and extended Kalman filter algorithms with the purpose to get a bounded gain such that a satisfactory modeling could be maintained. The advised algorithm has the advantage compared with the mentioned methods that it eludes the excessive increasing or decreasing of its gain. The gain of the recommended algorithm is uniformly stable and its convergence is found. The new algorithm is employed for the modeling of two synthetic examples