报告题目：New Ways to Find and Estimate Leak Size: Moving Horizon Estimation for Pipeline Leak Detection and Localization
报告时间：2025年6月16号（星期一）上午9.30开始
报告地点：中南大学岳麓山校区（校本部）民主楼210会议室
报告人：Stevan Dubljevic教授，University of Alberta.
报告简介：
Effective pipeline leak detection and localization are essential for mitigating greenhouse gas emissions in hydrocarbon transportation systems. However, the complex spatiotemporal dynamics, limited sensor coverage, and measurement disturbances pose significant challenges. This talk presents advanced estimation and control strategies designed for pipeline networks modeled by infinite-dimensional systems governed by partial differential equations (PDEs). Specifically, a novel moving horizon estimation (MHE) framework is introduced for constrained estimation of leak size and location, using a discrete-time pipeline hydraulic model derived via the structure-preserving Cayley-Tustin discretization. By leveraging coordinate transformation, the estimation problem is decoupled to improve leak localization accuracy. On the other hand, a discrete Luenberger observer is designed for state reconstruction under limited measurements, and support vector machines (SVM) are employed for data-driven leak classification and localization. The MHE framework is further extended by integrating state and parameter estimation with model predictive control (MPC) for set-point tracking in PDEs-governed pipeline network systems. Finally, an industrial application involving a pipeline system in Alberta will be discussed.
有效的管道泄漏检测和定位对于减少碳氢化合物运输系统中的温室气体排放至关重要。在实际应用中，复杂的时空动态特性、有限的传感器覆盖以及测量干扰等因素使其面临显著挑战。本次报告重点介绍针对偏微分方程（PDEs）描述的无穷维管道系统所设计的先进估计和控制策略。我们提出了一种新型滚动时域估计（MHE）框架，实现在约束条件下对管道泄漏量与位置的精准估计；采用Cayley-Tustin离散化方法构建离散时间无穷维管道水力模型，并通过坐标变换解耦估计问题，从而提高泄漏定位精度。此外，我们设计了离散Luenberger观测器用于有限测量信息下的时空状态重构，并采用支持向量机（SVM）实现数据驱动的泄漏分类与定位。为解决复杂管网系统的设定点跟踪问题，进一步设计了MHE与模型预测控制（MPC）相结合的控制算法。最后，将探讨在阿尔伯塔省管道系统中的工业应用案例。
报告人简介：
Stevan Dubljevic is a full Professor at the Chemical and Materials Engineering Department at the University of Alberta. He received his Ph.D. in 2005 from the Henry Samueli School of Engineering and Applied Science at University of California Los Angeles (UCLA) and his M.S. degree (2001) from the Texas A&M University (Texas). He is the recipient of the America Heart Association (AHA) Western States Affiliate Postdoctoral Grant Award (2007–2009) and the recipient of the O. Hugo Schuck Award for Applications, from American Automatic Control Council (AACC) 2007. His research interests include systems engineering, with the emphasis on model predictive control of distributed parameter systems, dynamics and optimization of materials manufacturing (crystal growth) and chemical process operations, computational modeling and simulation of biological systems (cardiac electrophysiological systems) and biomedical engineering.
