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

摘要：pi: Panagiotis Christofides and James F. Davis机构：加州大学洛杉矶分校提案号：0529295题目：过程控制中的传感器故障：分析、设计和应用。化学工业是美国经济的一个重要部门。化工过程操作日益面临安全性和盈利性的要求，广泛依赖自动化控制系统，涉及到大量的传感器。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，偏差测量等），导致控制系统失效，并可能导致一系列经济，环境和安全问题，这些问题可能严重降低过程的运行效率。管理由传感器故障引起的异常情况是化工行业面临的一个挑战，因为仅在美国，异常情况每年就会造成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，开发一个通用和实用的框架，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生产实际可实现的反馈控制系统，该系统明确地说明传感器故障的发生，并在闭环系统中强制执行所需的稳定性，性能和鲁棒性规格。混合系统和控制理论随后将用于：a)建模和分析传感器故障情况，b)构建新的监督控制方案，以确保局部控制系统在过程中及时协调响应，从而实现故障恢复并最小化性能下降。动机由以下方面提供：A)化学过程操作中传感器故障的常见发生，b)由于过程非线性、模型不确定性和约束，化学过程中存在大量复杂动力学，c)缺乏实际的非线性化学过程控制策略，可以明确地同时处理复杂动力学、传感器数据丢失和传感器故障，d)通信和计算技术的进步，e)持续需要改进化工过程操作，减少产品变异性，提高能源效率，尽量减少环境和安全危害。具体而言，研究将集中在：1。受传感器数据丢失影响的控制与估计系统的分析与设计本文将研究状态反馈和输出反馈控制问题。传感器完全失效情况下的集成容错控制与估计系统设计对传感器故障检测与识别问题和传感器故障诱导控制重构问题进行了研究。控制多个互连单元在传感器故障的情况下。应用于化学过程中，控制对实现预期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，开发明确考虑传感器故障的实际可实施的控制算法，解决传感器故障检测和重构方法与工业决策支持技术的集成问题，并说明这些方法在化学过程中的应用。更广泛的影响。这些控制方法对于受传感器故障影响的过程有望显著改善化学过程的操作和性能，提高过程的安全性和可靠性，并最大限度地减少故障对整个过程运行的负面经济影响。本研究解决了反馈控制和估计系统的设计，明确地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，并为在实际实施中可能存在的平衡提供了重要的见解。将研究与教育相结合将有利于教育工作者教授过程控制和操作的高级课程。软件的开发、短期课程和讲习班以及与工业联盟成员的合作将是将这项研究成果转移到工业部门的手段。

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.