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Object-oriented approach applied to ANFIS modeling and control of a distillation column

机译:面向对象的方法应用于蒸馏塔的ANFIS建模和控制

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Neurofuzzy networks are hybrid systems that combine neural networks with fuzzy systems, and the Adaptive Neuro-Fuzzy inference system (ANFIS) is a particular case in which a fuzzy system is implemented in the framework of an adaptive neural network. This neurofuzzy approach represents an effective structure to the modeling of plant dynamics, and the oriented-object programming environments offer an intuitive way to address this task. In this paper the MODEUCA object-oriented environment has been applied to the ANFIS modeling and indirect control of the heavy and light product composition in a binary methanol-water distillation column by using the adaptive Levenberg-Marquardt approach. The results obtained demonstrate the potential of the adaptive ANFIS scheme under MODEUCA for the dual control of composition both for changes in set points with null stationary error even when disturbances are present.
机译:Neurofuzzy网络是将神经网络与模糊系统结合在一起的混合系统,而自适应神经模糊推理系统(ANFIS)是在自适应神经网络框架内实现模糊系统的一种特殊情况。这种神经模糊方法代表了植物动力学建模的有效结构,而定向对象编程环境提供了解决此任务的直观方法。本文采用自适应Levenberg-Marquardt方法将MODEUCA面向对象的环境应用于ANFIS建模以及对二元甲醇-水蒸馏塔中重,轻产品组成的间接控制。获得的结果表明,在MODEUCA下,自适应ANFIS方案具有双重控制成分的潜力,即使在存在干扰的情况下,设定点的变化也具有零静态误差。

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