Nonlinear Adaptive Control Theory Applied for Chemical Process Control

通过实施补偿过程变量之间相互作用的控制策略，可以显著提高化工过程控制系统的性能和可靠性。这项研究的目的是证明稳定性和被动算子理论(在这个意义上的被动指的是属性的保留--例如，在所有此类过程中(质量守恒)可用于激励和开发非线性自适应控制器，用于聚合物和非均相共沸精馏系统等复杂过程控制问题。PI计划研究和开发一种替代的非线性过程控制方法，这种方法是由物理考虑驱动的，并利用热力学封闭系统的无源性。这一性质是通用的，因为化学过程是由能量和材料守恒关系来模拟的。传递系统的例子包括放热反应器、热交换器、蒸馏塔和推流反应器。以连续搅拌任务反应器(CSTR)、聚合物反应器和非均相共沸精馏过程为例说明了该方法的适用性。会议将讨论两个主题。第一个问题是如何利用稳定性理论来选择测量变量和操纵变量的可行组合。这个问题被称为非线性结构问题。第二个要解决的问题是具有不确定和/或完全未知参数的非线性过程的自适应控制器的设计。这就是暂态稳健性问题。结果将用于定义前向信号。由于其简单性和通用性，本研究也可能对过程控制的教学产生重大影响。

Significant improvements in the performance and the reliability of chemical process control systems can be achieved by implementing control strategies the compensate for the interaction between process variables. The objective of this research is to demonstrate that stability and passive operator theory (passivity in this sense refers to the preserving of a property--for example, in all such processes mass is conserved) can be used for motivate and develop nonlinear adaptive controllers for difficult process control problems like polymer and heterogeneous azeotropic distillation systems. The PI plans to investigate and develop an alternative approach to nonlinear process control, an approach that is motivated by physical considerations and exploits a passivity property of thermodynamically closed systems. This property is generic since chemical proceses are modelled by energy and material conservation relationships. Examples of passsive systems include exothermic reactors, heat exchangers, distillation columns and plug flow reactors. A continuous stirred task reactor (CSTR), a plymer reactor and a heterogeneous azeotropic distillation process will be used to illustrate the applicability of the proposed approach. Two topics will be addressed. The first is how to use stability theory to select a feasible combination of measured and manipulated variables. This problem is referred to as the nonlinear structure problem. The second problem to be addressed is the design of adaptive controllers for nonlinear processes that have uncertain and/or completely unknown parameters. This is the transient robustness problem. The result will be used to define feedfoward signals. Due to its simplicity and generality this research may also have a significant impact on the teaching of process control.