Sensors: Sensor Malfunctions in Process Control: Analysis, Design and Applications

传感器：过程控制中的传感器故障：分析、设计和应用

• 批准号: 0529295
• 负责人: Panagiotis Christofides
• 金额: $ 32万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0529295&HistoricalAwards=false
• 关键词: Sensors; Sensor; Malfunctions; Process; Control

ABSTRACTPI: Panagiotis Christofides and James F. Davis Institution: University of California - Los AngelesProposal Number: 0529295Title: Sensor Malfunctions in Process Control: Analysis, Design and ApplicationsIntellectual merit. The chemical industry is a vital sector of the US economy. Increasingly faced with the requirements of safety and profitability, chemical process operation is relying extensively on automated control systems, involving a large number of sensors. The reliance on sensors, however, tends to increase vulnerability of the process to sensor malfunctions (e.g., sensor failure, intermittent sensor data losses, biased measurements, etc.,), leading to the failure of the control system and potentially causing a host of economic, environmental, and safety problems that can seriously degrade the operating efficiency of the process. Management of abnormal situations resulting from sensor malfunctions is a challenge in the chemical industry since abnormal situations account for $10 billion in annual lost revenue in the US alone. The objective of this project is to develop a general and practical framework for handling sensor malfunctions in feedback control of chemical processes by explicitly dealing with sensor data losses and failures in the control system design and implementation. Nonlinear and predictive control theory will be used to produce practically-implementable, feedback control systems that account explicitly for the occurrence of sensor faults and enforce the desired stability, performance and robustness specifications in the closed-loop system. Hybrid systems and control theory will subsequently be used to: a) model and analyze sensor failure situations, and b) construct novel supervisory control schemes that ensure the timely and coordinated response of the local control systems in the process, in a way that achieves fault recovery and minimizes performance deterioration. The motivation is provided by: a) the common occurrence of sensor malfunctions in chemical process operation, b) the abundance of complex dynamics in chemical processes due to process nonlinearities, model uncertainties and constraints, c) the lack of practical control strategies for nonlinear chemical processes that can deal explicitly and simultaneously with complex dynamics, sensor data losses and sensor failures, d) advances in communication and computation technologies, and e) the continuing need to improve chemical process operation, reduce product variability, improve energy efficiency and minimize environmental and safety hazards. Specifically, the research will focus on:1. Analysis and design of control and estimation systems subject to sensor data losses; both the state and output feedback control problems will be studied.2. Design of integrated fault-tolerant control and estimation systems subject to complete sensor failures; both the sensor fault-detection and identification problem and the problem of sensor fault-induced control reconfiguration will be studied.3. Control of multiple interconnected units subject to sensor malfunctions.4. Applications to chemical processes where control is critical in achieving the desired stability and performance objectives.The research will also provide fundamental insight into the problems and limitations that sensor malfunctions cause on process control, develop practically-implementable control algorithms accounting explicitly for sensor malfunctions, address the integration of sensor fault-detection and reconfiguration methods with industrial decision support technologies, and illustrate the application of these methods to chemical processes. Broader impact. These control methods for processes subject to sensor malfunctions are expected to significantly improve the operation and performance of chemical processes, increase process safety and reliability, and minimize the negative economic impact of failures on overall process operation. This research addresses the design of feedback control and estimation systems accounting explicitly for the occurrence of sensor faults and uniquely integrates controller design, sensor fault-detection and isolation, and decision support technologies and provides the potential for significant insight on the balance that can exist between these in practical implementation. The integration of the research into education would benefit educators teaching advanced-level classes in process control and operations. The development of software, short courses and workshops, and the collaboration with the members of an industrial consortium will be the means for transferring the results of this research into the industrial sector.

摘要：Panagiotis Christofides 和 James F. Davis 机构：加州大学洛杉矶分校提案编号：0529295 标题：过程控制中的传感器故障：分析、设计和应用智力价值。化学工业是美国经济的重要部门。化学过程操作越来越面临安全性和盈利性的要求，广泛依赖涉及大量传感器的自动化控制系统。然而，对传感器的依赖往往会增加过程对传感器故障的脆弱性（例如，传感器故障、间歇性传感器数据丢失、测量偏差等），从而导致控制系统故障并可能导致一系列问题。经济、环境和安全问题会严重降低流程的运行效率。管理由传感器故障引起的异常情况是化学工业中的一项挑战，因为仅在美国，异常情况每年就造成 100 亿美元的收入损失。该项目的目标是通过明确处理控制系统设计和实施中的传感器数据丢失和故障，开发一个通用且实用的框架，用于处理化学过程反馈控制中的传感器故障。非线性和预测控制理论将用于产生实际可实现的反馈控制系统，该系统明确地考虑传感器故障的发生并在闭环系统中强制执行所需的稳定性、性能和鲁棒性规范。随后，混合系统和控制理论将用于：a）对传感器故障情况进行建模和分析，b）构建新颖的监控方案，确保过程中本地控制系统及时、协调地响应，从而实现故障排除恢复并最大限度地减少性能下降。其动机是：a）化学过程操作中传感器故障的普遍发生，b）由于过程非线性、模型不确定性和约束，化学过程中存在丰富的复杂动态，c）缺乏非线性化学的实用控制策略能够明确地同时处理复杂动态、传感器数据丢失和传感器故障的过程，d) 通信和计算技术的进步，以及 e) 改进化学工艺操作、减少产品变异性、提高能源效率和最大限度地减少环境和影响的持续需求安全隐患。具体来说，研究将集中在： 1．分析和设计受传感器数据丢失影响的控制和估计系统；研究状态反馈控制问题和输出反馈控制问题； 2．设计受完全传感器故障影响的集成容错控制和估计系统；研究传感器故障检测与识别问题以及传感器故障引起的控制重构问题。 3．受传感器故障影响的多个互连单元的控制。4．在化学过程中的应用，其中控制对于实现所需的稳定性和性能目标至关重要。该研究还将提供对传感器故障对过程控制造成的问题和限制的基本见解，开发可实际执行的控制算法，明确说明传感器故障，解决将传感器故障检测和重新配置方法与工业决策支持技术相集成，并说明这些方法在化学过程中的应用。更广泛的影响。这些针对传感器故障过程的控制方法预计将显着改善化学过程的操作和性能，提高过程安全性和可靠性，并最大限度地减少故障对整个过程操作的负面经济影响。这项研究解决了反馈控制和估计系统的设计，明确考虑了传感器故障的发生，并独特地集成了控制器设计、传感器故障检测和隔离以及决策支持技术，并为深入了解传感器故障之间可能存在的平衡提供了潜力。这些在实际执行中。研究与教育的结合将有利于教育工作者教授过程控制和操作方面的高级课程。软件开发、短期课程和研讨会以及与工业联盟成员的合作将成为将这项研究成果转移到工业部门的手段。