Desarrollo de software de usuario para sistemas de control predictivo no lineal basado en modelo borroso
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Valencia Villa, Juan Sebastián
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Resumen: Los sistemas de control son de gran importancia para poder llevar a operación deseada y óptima los diferentes procesos que generan la cadena productiva de una empresa de manufactura. La implementación de aplicativos de software en la industria presentan entonces una solución para problemas complejos en la operación de dichos procesos. Se plantean entonces en este Trabajo Final de Maestría el desarrollo de un aplicativo de software en el cual se generan sistemas de control predictivo no lineal basado en modelos que hacen uso de métodos de inteligencia artificial para la identificación del proceso y es utilizado dentro del optimizador del controlador debido a la facilidad de operación y la velocidad en el tiempo de respuesta
Abstract: In the industry process control systems become very important due to the necessity of maintaining process variables in optimal and desirable values in order to maintain product quality factors and maintain active the productive chain. Implementing software applications in industry also present a solution to complex problems occurring in the processes. In this Master Final Work is shown a development of software application which generate nonlinear predictive control based on models that use artificial intelligence methods for the identification of the process and is used in the controller optimizer, it’s made due the facility of operation and implementation and the improvements of execution speed
Abstract: In the industry process control systems become very important due to the necessity of maintaining process variables in optimal and desirable values in order to maintain product quality factors and maintain active the productive chain. Implementing software applications in industry also present a solution to complex problems occurring in the processes. In this Master Final Work is shown a development of software application which generate nonlinear predictive control based on models that use artificial intelligence methods for the identification of the process and is used in the controller optimizer, it’s made due the facility of operation and implementation and the improvements of execution speed
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Palabras clave propuestas
Modelado de procesos; Inteligencia artificial; Sistemas de inferencia borrosa; Control predictivo; Sistemas no lineales; Modelos caja gris; Desarrollo de software; Programación orientada a objetos; Método UNC; Process modeling; UNC method; Object oriented programming; Artificial inteligence; Fuzzy systems; Predictive control; Non linear systems; Gray box models; Software development