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Controlling biological wastewater treatment plants using fuzzy control and neural networks

机译:使用模糊控制和神经网络控制生物废水处理厂

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Improving the performance of wastewater treatment plants by optimising the control systems is a very cost efficient method but it involves risks caused by the time variant and non linear nature of the complex biochemical processes. Key problem is the removal of nitrogen combined with an optimal processing of the sludge water. Different control strategies are discussed. A combination of neural network for predicting outflow values one hour in advance and a fuzzy controller for dosing the sludge water are presented. This design allows the construction of a highly non-linear predictive controller adapted to the behaviour of the controlled system with a relatively simple and easy to optimise fuzzy controller. The system has been successfully tested on a municipal wastewater treatment plant of 60.000 inhabitant equivalents.
机译:通过优化控制系统来提高废水处理厂的性能是一种非常经济高效的方法,但是它涉及到复杂生物化学过程的时间变化和非线性性质所带来的风险。关键问题是脱氮和污泥水的最佳处理。讨论了不同的控制策略。提出了一种神经网络,可以提前一小时预测出水量,而模糊控制器可以对污泥水进行计量。这种设计允许构建一个高度非线性的预测控制器,该控制器采用相对简单且易于优化的模糊控制器来适应受控系统的行为。该系统已在60.000个居民当量的市政废水处理厂成功进行了测试。

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