Best Achievable Control System Performance

提取- Manousiouthakis - 9312489 近年来，由于过程工业缺乏主要的资本投资，控制项目的实施成为提高工厂盈利能力的一种模式。 这些经济效益通常与先进控制提供的改进的动态性能有关。 在监管控制背景下，质量变量需要保持在控制限值内，并且不允许超过规格限值。 如果一种控制策略可以实现比另一种更严格的控制极限，则可以改变该质量变量的设定点，以提高过程经济性。 动态性能不是选择控制系统的一个标准。 不确定性、复杂性和可靠性也是关键问题。 化工过程模型往往是经验性的，忽略了复杂的物理化学现象或缺乏过程参数的信息。 因此，这些模型具有很高的不确定性。 化学过程也是大规模互连系统，其中测量和/或操纵大量变量。 这些相互连接的单元操作的地理位置将需要安装复杂的通信网络，以便将信息从测量传输到中央位置，然后传输到操作。 这种网络的安装和维护成本以及复杂性通常阻碍了这种集中式控制系统的实现。 相反，控制系统的简单性是通过以下方式实现的：1）使用分散控制系统，其中测量和操纵被分类为子集，并且信息仅在相应的子集之间交换，以及使用人类操作员熟悉的简单低阶控制策略。 可靠性是控制系统设计的另一个标准。 控制系统元件（例如传感器/致动器）的故障通常导致控制回路的手动操作。 控制系统最好是这样的，即它可以容易地重新配置，以便即使动态性能特性下降也能保持设备运行。 本研究项目的目标是开发一种方法，解决这个问题：什么是最好的可实现的动态性能，分散和/或低阶同时稳定和/或可靠的反馈控制系统可以提供在存在外部干扰。 这些控制问题的制定导致二次约束，无限维优化问题。 这些问题的全球解决方案的计算技术的调查是将解决的主要问题之一。 将寻求分支和界限、分解、区间算术技术及其组合和计算实现。

Abtract - Manousiouthakis - 9312489 In recent years, the lack of major capital investments in the process industries has made the implementation of control projects one mode to increased plant profitability. These economic benefits are typically associated with the improved dynamic performance offered by advanced controls. In a regulatory control context, a quality variable is desired to stay within control limits and is not allowed to exceed specification limits. If one control strategy can achieve tighter control limits than another, then the setpoint of this quality variable may be changed so as to enhance process economics. Dynamic performance is not one criterion in selecting a control system. Uncertainty, complexity and reliability are also critical issues. Chemical process models are often empirical, neglect complex physicochemical phenomena or lack information on process parameters. Consequently, high levels of uncertainty are associated with these models. Chemical processes are also large scale interconnected systems in which a large number of variables are measured and/or manipulated. The geographical location of these interconnected unit operations would necessitate the installation of a complex communication network for the purpose of transferring information from the measurements to a central location and then to the manipulations. The installation and maintenance costs and the complexity of such a network often prevent the implementation of such a centralized control system. Instead, control system simplicity is attained by: 1) the use of a decentralized control system in which measurements and manipulations are classified into subsets and information is exchanged only between corresponding subsets, and 20 the use of simple low order control strategies with which human operators are familiar. Reliability is another criterion in control system design. Failures of control system elements such as sensors/actuators often lead to the manual operation of control loops . It is desirable that the control system be such that it can be readily reconfigured so as to maintain plant operation albeit with degraded dynamic performance characteristics. The objective of this research project is the development of a methodology that addresses the question: What is the best achievable dynamic performance that a decentralized and/or low order simultaneously stabilizing and/or reliable feedback control system can deliver in the presence of external disturbances. The formulation of these control problems leads to quadratically constrained, infinite dimensional optimization problems. The investigation of computational techniques for the global solution of such problems is one of the main issues that will be addressed. Branch and bound, decomposition, interval arithmetic techniques and combinations thereof and computational implementations will be sought.