Design and Monitoring of Cooperative, Distributed Control Systems for Nonlinear Processes

非线性过程协同分布式控制系统的设计和监控

• 批准号: 1027553
• 负责人: Panagiotis Christofides
• 金额: $ 35.35万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1027553&HistoricalAwards=false
• 关键词: Design; Monitoring; Cooperative; Distributed; Control

1027553ChristofidesOptimal operation and management of abnormal situations are major challenges in the process industries since, for example, abnormal situations account for at least $10 billion in annual lost revenue in the US alone. This realization has motivated significant research in the area of process control to ensure safe and efficient process operation. Traditionally, control systems rely on centralized control architectures utilizing dedicated, wired links to measurement sensors and control actuators to regulate appropriate process variables at desired values. While this paradigm to process control has been successful, when the number of the process state variables, manipulated inputs and measurements in a chemical plant becomes large - a common occurrence in modern plants -, the computational time needed for the solution of the centralized control problem may increase significantly and may impede the ability of centralized control systems (particularly when nonlinear constrained optimization-based control systems like model predictive control-MPC are used), to carry out real-time calculations within the limits set by process dynamics and operating conditions. One feasible alternative to overcome this problem is to utilize cooperative, distributed control architectures in which the manipulated inputs are computed by solving more than one control (optimization) problem in separate processors in a coordinated fashion. However, the rigorous design of cooperative, distributed control architectures for nonlinear processes is a challenging task that cannot be addressed with traditional process control methods dealing with the design of centralized control systems. To design cooperative, distributed control systems, key fundamental issues that need to be addressed include the design of the individual control systems and of their communication strategy so that they efficiently cooperate in achieving the closed-loop plant objectives, as well as the development of efficient strategies for fault detection, isolation and management.Intellectual Merit Motivated by the above considerations, the objective of this research program is to develop the theory and methods needed for the design and monitoring of cooperative, distributed control systems for large-scale nonlinear processes and demonstrate their application and effectiveness in the context of process systems of industrial importance. Rigorous methods and architectures will be developed for the design of cooperative, distributed control systems accounting explicitly for the effect of asynchronous and delayed measurements, and novel monitoring and reconfigurable fault-tolerant control strategies will be developed to deal with actuator/sensor/controller failures. Specifically, the research projects include: 1) Design of cooperative, distributed control systems for nonlinear processes using Lyapunov-based model predictive control techniques; control system architecture, model uncertainty and state estimation issues will be explicitly addressed, 2) Design of fault-detection and isolation systems for cooperative, distributed control systems, 3) Development of reconfigurable fault-tolerant control strategies accounting explicitly for stability, performance and robustness considerations, and 4) Applications to simulated and lab-scale process systems of importance to chemical and water industries.Broader Impact The development of cooperative, distributed control system design and monitoring methods for large-scale nonlinear processes is expected to significantly improve the operation and performance of chemical processes, increase process safety and reliability, and minimize the negative economic impact of process failures, thereby impacting directly the US economy. The integration of the research results into advanced-level classes in process control and operations and the writing of a new book on ?Fault-Tolerant Process Control? will benefit students and researchers in the field. The development of software, short courses and workshops and the on-going participation in the Abnormal Situation Management (ASM) Consortium will be the means for transferring the results of this research into the industrial sector. Furthermore, the involvement of a diverse group of undergraduate and graduate students in the research through participation in the Center for Engineering Education and Diversity (CEED) at UCLA, and outreach to the California State Polytechnic University in Pomona by offering summer internships to highly-qualified students, will be pursued. Finally, the research will benefit from and contribute to educational initiatives and innovations on the UCLA campus in the area of information technology directed by the co-PI.

1027553Christofides异常情况的优化运行和管理是过程工业中的主要挑战，因为例如，仅在美国，异常情况每年就造成至少 100 亿美元的收入损失。这一认识推动了过程控制领域的重大研究，以确保安全、高效的过程运行。传统上，控制系统依赖于集中控制架构，利用专用的有线链路连接到测量传感器和控制执行器，以将适当的过程变量调节到所需值。虽然这种过程控制范例已经取得了成功，但当化工厂中的过程状态变量、操纵输入和测量的数量变大时（现代工厂中常见的情况），解决集中控制问题所需的计算时间可能会显着增加，并可能会阻碍集中控制系统（特别是当使用基于非线性约束优化的控制系统（例如模型预测控制 MPC）时）在过程动态和操作条件设定的限制内进行实时计算的能力。克服这一问题的一种可行的替代方案是利用协作式分布式控制架构，其中通过以协调的方式解决单独处理器中的多个控制（优化）问题来计算操纵输入。然而，非线性过程的协作分布式控制架构的严格设计是一项具有挑战性的任务，无法用处理集中控制系统设计的传统过程控制方法来解决。为了设计协作式分布式控制系统，需要解决的关键基本问题包括各个控制系统及其通信策略的设计，以便它们有效地合作实现闭环工厂目标，以及开发高效的控制系统。故障检测、隔离和管理策略。 智力优点 出于上述考虑，本研究计划的目标是开发设计和监控大规模非线性过程的协作分布式控制系统所需的理论和方法，并演示它们在工业过程系统中的应用和有效性重要性。 将开发严格的方法和架构来设计协作式分布式控制系统，明确考虑异步和延迟测量的影响，并将开发新颖的监控和可重构容错控制策略来处理执行器/传感器/控制器故障。具体来说，研究项目包括： 1）使用基于李雅普诺夫的模型预测控制技术设计非线性过程的协作分布式控制系统；控制系统架构、模型不确定性和状态估计问题将得到明确解决，2）协作分布式控制系统的故障检测和隔离系统设计，3）开发可重构容错控制策略，明确考虑稳定性、性能和鲁棒性考虑因素，以及 4) 在对化学和水工业具有重要意义的模拟和实验室规模过程系统中的应用。 更广泛的影响 针对大规模非线性过程的协作式分布式控制系统设计和监测方法的开发预计将显着改善操作和控制。化学工艺性能，增加工艺安全性和可靠性，并最大限度地减少过程故障的负面经济影响，从而直接影响美国经济。将研究成果融入过程控制和操作的高级课程中，并撰写一本关于“容错过程控制”的新书。将使该领域的学生和研究人员受益。软件、短期课程和研讨会的开发以及对异常情况管理（ASM）联盟的持续参与将成为将这项研究成果转移到工业部门的手段。此外，通过参与加州大学洛杉矶分校工程教育和多样性中心 (CEED)，以及通过向高素质人才提供暑期实习机会，向位于波莫纳的加州州立理工大学进行推广，让不同的本科生和研究生群体参与到研究中。学生，将被追赶。最后，该研究将受益于并有助于加州大学洛杉矶分校校园在联合首席研究员指导的信息技术领域的教育举措和创新。