An intelligent controller, based on interval type-2 fuzzy neural networks (IT2FNN) was proposed for controlling dissolved oxygen (DO) concentration in municipal wastewater treatment processes. First, IT2FNN was applied to design a DO concentration controller. Second, an adaptive learning algorithm was used to online adjust controller parameters such that self-adaptability of the IT2FNN-based DO controller could be improved. Finally, IT2FNN-based DO controller was tested in the benchmark simulation model no. 2 (BSM2). The experimental results demonstrate that the controller is able to accurately monitor DO concentration in the fifth unit and maintain excellent control.%针对城市污水处理过程溶解氧浓度难以精确控制的问题,提出了一种基于区间二型模糊神经网络(interval type-2 fuzzy neural networks, IT2FNN)的溶解氧浓度控制方法.先将IT2FNN应用在城市污水处理过程溶解氧浓度控制器的设计,获得了一种IT2FNN溶解氧浓度控制器.后采用自适应学习算法在线调整控制器的参数,提高了控制器的自适应能力.最后将提出的IT2FNN溶解氧浓度控制器应用于基准仿真2号模型(benchmark simulation model no.2, BSM2)平台,结果表明,IT2FNN控制器能够实现第5分区溶解氧浓度精确控制,具有较好的控制效果.
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