Best Achievable Control System Performance

摘要-Manousiouthakis-9312489近年来，流程工业缺乏重大资本投资，这使得实施控制项目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相关。在法规控制环境中，要求质量变量保持在控制范围内，并且不允许超过规范限制。如果一种控制策略可以达到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值，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，高度的不确定性与这些模型有关。化工过程也是大规模的相互关联的系统，其中有大量的变量被测量和/或操纵。这些相互连接的单元作业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往往阻碍了这种集中控制系统的实施。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，其中测量和操作被分类为子集，并且仅在相应的子集之间交换信息，以及20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指标。传感器/执行器等控制系统元件的故障往往会导致控制回路的手动操作。希望控制系统能够容易地重新配置，从而即使具有降级的动态性能特性也能保持工厂的运行。这一研究项目的目标是开发一种方法来解决以下问题：在存在外部干扰的情况下，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的最佳动态性能是什么。这些控制问题的形成导致了二次约束的无限维优化问题。对这些问题的全球解决方案的计算技术的研究是将要解决的主要问题之一。将寻求分支定界、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.