US-Sweden Cooperative Research: System Identification and Control of the Clarification Process

该奖项将支持新罕布什尔大学Paul J. Ossenbruggen博士和瑞典隆德理工学院Gustaf Olsson教授之间的合作研究。拟议的项目侧重于活性污泥处理（AST）过程的澄清阶段，这是一种高度复杂的生物处理废水的方法。尽管它在世界范围内很受欢迎，但我们对这一过程的理解是有限的，目前还没有足够的方法来控制这一过程。即使在运作良好的工厂，经常违反排放标准也是很常见的。AST过程中许多物理、水力和生物因素的相互作用使得系统识别和开发有效的动态控制算法变得困难。在这个项目中，提出了一个析因实验来识别显著影响澄清过程的参数。关注的因素是：混合液悬浮物、回流污泥流量、溶解氧和污泥层深度。响应、受控参数和非受控参数的测量将以每分钟一次观测的频率进行测量。这些关键因素的时间序列将使用Box-Jenkins技术进行分析，以制定数学模型并开发控制算法。所有实验和控制器验证研究将在全规模的处理厂进行。这项研究工作将在隆德理工学院与Olsson教授合作进行，Olsson教授是公认的系统建模和控制专家。这项研究建立在先前在休斯顿和加拿大进行的研究的基础上，使用了全面的处理厂。通过提供专门为时间序列技术和因果研究的特殊需要而设计的实验数据，该研究应有助于更好地了解AST过程及其控制。

This award will support collaborative research between Dr. Paul J. Ossenbruggen, University of New Hampshire and Professor Gustaf Olsson, Lund Institute of Technology, Sweden. The proposed project focuses on the clarification phase of the activated sludge treatment (AST) process, a highly complex, biological method of treating wastewater. In spite of its popularity around the world, our understanding of the process is limited, and at present there are not adequate methods to control the process. Frequent violations of effluent standards are common even at well-operated plants. The interaction of a number of physical, hydraulic and biological factors in the AST process make system identification and development of effective dynamic control algorithms difficult. In this project, a factorial experiment to identify parameters that significantly affect the clarification process is proposed. The factors of concern are: mixed liquor suspended solids, return sludge flow rate, dissolved oxygen, and sludge blanket depth. Measurements of response, controlled and uncontrolled parameters will be measured at a frequency of one observation per minute. Time series of these critical factors will be analyzed using Box-Jenkins techniques to formulate mathematical models and to develop a control algorithm. All experiments and controller validation studies will be performed on full-scale treatment plants. This research effort will be conducted at the Lund Institute of Technology in cooperation with Professor Olsson, a recognized expert on system modelling and control. The study builds on previous research conducted in Houston and Canada using full-scale treatment plants. By providing data from experiments specifically designed for the special needs of time-series techniques and cause-effect studies, the research should lead to a better understanding of the AST process and its control.