EnergyWay srl Via Sant'Orsola, 33, 41121 Modena, Italy.
University of Florence, Piazza di San Marco, 4, 50121 Firenze FI, Italy E-mail:
Water Sci Technol. 2020 Jun;81(11):2391-2400. doi: 10.2166/wst.2020.298.
Two separate goals should be jointly pursued in wastewater treatment: nutrient removal and energy conservation. An efficient controller performance should cope with process uncertainties, seasonal variations and process nonlinearities. This paper describes the design and testing of a model predictive controller (MPC) based on neuro-fuzzy techniques that is capable of estimating the main process variables and providing the right amount of aeration to achieve an efficient and economical operation. This algorithm has been field tested on a large-scale municipal wastewater treatment plant of about 500,000 PE, with encouraging results in terms of better effluent quality and energy savings.
在污水处理中，应同时追求两个目标：去除营养物质和节能。高效的控制器性能应能应对工艺不确定性、季节性变化和工艺非线性。本文介绍了一种基于神经模糊技术的模型预测控制器 (MPC) 的设计和测试，该控制器能够估算主要工艺变量，并提供适量的曝气，以实现高效、经济的运行。该算法已在一个 50 万当量人口的大型城市污水处理厂进行了现场测试，在改善出水质量和节能方面取得了令人鼓舞的结果。
