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.

1027553 Christofides优化操作和异常情况管理是流程工业的主要挑战，因为例如，仅在美国，异常情况就造成至少100亿美元的年度收入损失。这一认识激发了过程控制领域的重大研究，以确保安全和有效的过程操作。传统上，控制系统依赖于集中式控制架构，该集中式控制架构利用到测量传感器和控制致动器的专用有线链路来将适当的过程变量调节为期望值。虽然这种过程控制的范例是成功的，但是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（这在现代工厂中是常见的），解决集中控制问题所需的计算时间可能显著增加（特别是当使用基于非线性约束优化的控制系统，如模型预测控制-MPC时），以在由过程动态和操作条件设定的限制内执行实时计算。一个可行的替代方案，以克服这个问题是利用合作，分布式控制体系结构，其中的操纵输入计算通过解决一个以上的控制（优化）问题，在单独的处理器在一个协调的方式。然而，严格的合作，分布式控制体系结构的非线性过程的设计是一个具有挑战性的任务，不能与传统的过程控制方法处理集中式控制系统的设计。为了设计协同分布式控制系统，需要解决的关键基本问题包括各个控制系统的设计及其通信策略，以便它们有效地合作实现闭环工厂目标，以及开发用于故障检测，隔离和管理的有效策略。智力优势出于上述考虑，本研究计划的目标是发展大规模非线性过程的协同分布式控制系统的设计和监控所需的理论和方法，并在工业重要性过程系统的背景下证明其应用和有效性。 严格的方法和体系结构将被开发的合作，分布式控制系统的设计明确的异步和延迟测量的影响，和新的监测和可重构的容错控制策略将被开发来处理执行器/传感器/控制器故障。具体而言，研究项目包括：1）基于李雅普诺夫模型预测控制技术的非线性过程协同分布式控制系统设计;控制系统结构，模型不确定性和状态估计问题将明确解决，2）设计故障检测和隔离系统的合作，分布式控制系统，3）明确考虑稳定性、性能和鲁棒性的可重构容错控制策略的开发，和4）应用于对化学和水工业具有重要意义的模拟和实验室规模的过程系统。大规模非线性过程的分布式控制系统设计和监控方法有望显著改善化工过程的操作和性能，提高过程安全性和可靠性，并将过程故障的负面经济影响降至最低，从而直接影响美国经济。将研究成果整合到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？将使该领域的学生和研究人员受益。软件开发、短期课程和讲习班以及持续参与异常情况管理（ASM）联盟将是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），以及通过向高素质学生提供暑期实习机会，向波莫纳的加州州立理工大学提供外展服务，让不同群体的本科生和研究生参与研究。最后，这项研究将受益于并有助于教育举措和创新的加州大学洛杉矶分校校园在信息技术领域的共同PI指导。