本文讨论了下一代饮用水处理过程控制策略 植物，并说明为什么公用事业应该考虑在他们的操作中实现它们 工厂将在不久的将来帮助跟上处理法规并控制成本 活动对先进控制技术、设备要求、技术发展的回顾 使用人工神经网络（ANN）的过程模型，以及模型与工厂的集成 描述了控制系统。本文还展示了公用事业公司如何开始实施下一步 利用现有设备和系统（如在线分析仪）进行发电控制， 常规控制、SCADA（监控和数据采集）系统，以及 历史电厂性能数据。 本文介绍了“全厂控制”这一概念 工厂优化的整体方法，连接和集成各种模型（例如，过程、， 需求、生产和能源）、运营总成本、最终出水水质和其他 将管理目标转化为基于约束的决策系统。最后，两个案例研究 EPCOR供水服务公司管理的水厂实施的下一代控制措施 （加拿大艾伯塔省埃德蒙顿）也有介绍。包括7个参考文献、图表。

This paper discusses the next generation of process control strategies for drinking water treatment plants and illustrates why utilities should consider implementing them in the operation of their plants in the near future to help stay abreast of treatment regulations and to control costs of operation. A review of advanced control techniques, equipment requirements, development of process models using artificial neural networks (ANNs), and integration of models with plant control systems is described. The paper also shows how utilities can begin implementing next generation controls by leveraging their existing equipment and systems such as on-line analyzers, conventional controls, the SCADA (Supervisory Control and Data Acquisition) system, and historical plant performance data. The paper describes the concept of "plant-wide control", a holistic approach at plant optimization that links and integrates various models (e.g. process, demands, production, and energy), overall cost of operation, final effluent water quality and other management objectives into a constraint-based decision making system. Finally, two case studies of next generation controls implemented in water plants managed by EPCOR Water Services (Edmonton, Alberta, Canada) are also presented. Includes 7 references, figures.