Digital Control of Nonlinear Processes

非线性过程的数字控制

• 批准号: 9403432
• 负责人: Costas Kravaris
• 金额: $ 23.14万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-05-01 至 1998-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9403432&HistoricalAwards=false
• 关键词: Digital; Control; Nonlinear; Processes

Abstract - Kravaris - 9403432 The chemical industry is dominated by processes that exhibit nonlinearities. For example, polymerization reactors, high-purity distillation columns, bioprocesses, etc. are highly nonlinear processes. The digital computer-based implementation of nonlinear control laws in industry has motivated the development of nonlinear, discrete-time process control methods. The cornerstone of all the discrete-time control algorithms is the inevitable time-discretization of a continuous-time, nonlinear dynamic system, which is an open problem. The development of a reliable discretization procedure for nonlinear, continuous-time systems, especially when the sampling period becomes large, based on the fact that in many industrial control problems, certain measurements are performed at low sampling rates. For example, chemical composition measurements are usually performed under a much lower sampling rate (e.g. gas chromatography) compared to temperature measurements. The overall objective of this research is the development of methods for analyzing the behavior of nonlinear chemical processes subject to slow sampling and synthesizing stable and robust, digital control systems that meet design specifications. The conceptual framework of differential geometry will be use to: 1. Develop a time-discretization procedure for nonlinear, continuous-time systems, especially where the sampling period becomes large. 2. Study the effect of sampling and the particular discretization procedure upon the nonminimum-phase characteristics of a nonlinear, discrete-time process model. 3. Develop nonlinear multirate control algorithms which use the infrequent and frequent measurements effectively in order to induce a desirable closed-loop behavior for the process under consideration. 4. Design discrete-time, nonlinear state estimators which will be used to reconstruct the unmeasurable state variables. 5. Experimentally verify these control strategies by application to polymerizat ion reactors.

摘要- Kravaris - 9403432 化学工业以非线性过程为主。 例如，聚合反应器、高纯度蒸馏塔、生物过程等是高度非线性的过程。 工业中基于数字计算机的非线性控制律的实现促进了非线性、离散时间过程控制方法的发展。 所有离散时间控制算法的基石是连续时间非线性动态系统的不可避免的时间离散化，这是一个开放的问题。 针对非线性、连续时间系统，特别是当采样周期变大时，基于在许多工业控制问题中，某些测量是在低采样率下进行的这一事实，开发了一种可靠的离散化方法。 例如，与温度测量相比，化学成分测量通常在低得多的采样率（例如气相色谱法）下进行。 本研究的总体目标是开发用于分析非线性化学过程的行为的方法，这些过程受到慢采样和合成满足设计规格的稳定和鲁棒的数字控制系统的影响。 微分几何的概念框架将用于：1。 为非线性、连续时间系统开发一个时间离散化程序，特别是当采样周期变大时。 2. 研究采样和离散化过程对非线性离散过程模型非最小相位特性的影响。 3. 开发非线性多速率控制算法，有效地使用不频繁和频繁的测量，以诱导一个理想的闭环行为的过程中考虑。 4. 设计离散时间，非线性状态估计器，将用于重建不可测的状态变量。 5. 并将这些控制策略应用于聚合反应器中进行了实验验证。