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Neurofuzzy control strategies for an electrodynamic desalter.

机译：电动除盐器的神经模糊控制策略。

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Electrodynamic desalters are frequently used in the petroleum industry to separate water, salts and suspended particulates from crude oil. These systems use high voltage AC and/or DC fields to induce coalescence and settling of water droplets, thereby dehydrating crude oil and carrying away salts and particulates.; Due to the inherent complexity, non-linearity and absence of suitable mathematical models of the underlying process, electrodynamic desalters are controlled manually. When perturbations or disturbances occur, an operator modifies the process parameters following a predetermined sequence of adjustments to produce the desired results.; This work uses neurofuzzy strategies to control an electrodynamic desalter. Fuzzy rules are used to specify control knowledge possessed by human operators, and a neural network architecture with reinforcement learning is used to refine the fuzzy rules based on experimental data. The results indicate that neurofuzzy controllers are well suited to controlling an electrodynamic desalter in the dehydration and desalting modes.
机译：电动脱盐器在石油工业中经常用于从原油中分离出水，盐和悬浮颗粒。这些系统利用高压交流和/或直流电场引起水滴的聚结和沉淀，从而使原油脱水并带走盐和微粒。由于固有的复杂性，非线性和缺少基础过程的合适数学模型，因此电动脱盐器需要手动控制。当发生扰动或干扰时，操作员按照预定的调整顺序修改过程参数，以产生所需的结果。这项工作使用神经模糊策略来控制电动除盐器。模糊规则用于指定操作员拥有的控制知识，而具有增强学习功能的神经网络体系结构则用于根据实验数据来完善模糊规则。结果表明，神经模糊控制器非常适合在脱水和脱盐模式下控制电动除盐器。

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