Modeling, Identification and Validation of Uncertain Linear and Nonlinear Feedback Systems

所提出的工作的目标是开发一套集成的工具和方法的不确定系统的建模反馈控制设计的目的。 我们的建模框架是基于鲁棒控制理论，这是由几个复杂的控制设计方法的支持。 这些模型实际上是集合描述，其中集合是由模型内未知但有界的动态扰动产生的。 这些模型允许设计者捕捉物理系统将产生的各种不确定行为。 虽然这是一个强大的和灵活的建模框架，可用于建模的物理系统的工具是有限的。我们以前的工作的鲁棒控制模型的模型验证的基础上，这里提出的工作。 这种方法导致的工具，允许设计人员实验量化的物理系统和鲁棒控制模型集的最接近的成员之间的差异。 目前的工作着眼于将这些方法扩展到替代实验场景。 一个方向将是使用相关的扫描正弦实验，在工业实践中经常使用的程序。 第二个方向将是考虑来自不同信号类别的噪声和扰动;例如随机噪声和增益有界扰动。 这种模型与典型的物理系统更接近，并将使这些方法适用于更广泛的工业过程。 我们还建议开发一个强大的控制建模框架，将处理某些类别的非线性系统。 该项目将考虑两个工业动机的例子，从这些类：旋转失速喷气发动机压缩机和热声相互作用的燃烧室。这些方法将被应用到这些问题的简化模拟版本。 非线性行为和动态扰动的结合开辟了一个领域的非线性鲁棒性分析，这也将得到解决。三个实验是可用的，并将用于支持这项研究：（1）金属有机化学气相沉积（MOCVD）反应器，用于蓝色LED和蓝色激光二极管的外延晶体生长。(2)磁悬浮轴承系统，作为人工心脏泵（左心室辅助装置）的原型开发。(3)一种快速热处理系统，可模拟半导体和薄膜处理行业中典型处理步骤的动态。这些实验中的每一个都表现出共同的实际困难，理论建模和识别方法还没有很好地处理，使它们成为所提出的工作的理想测试平台。

The objective of the proposed work is to develop an integrated suite of tools and approached for the modeling of uncertain systems for feedback control design purposes. Our modeling framework is based upon robust control theory, which is supported by several sophisticated control design methods. These models are in effect set descriptions, where the sets are generated by unknown but bounded dynamic perturbations within the model. The models allow the designer to capture the variety of uncertain behaviors that a physical system will generate. Although this a powerful and flexible modeling framework, the tools available for modeling physical systems are limited.Our prior work on model validation for robust control models from the basis for the work proposed here. This approach has led to tools which allow the designer to experimentally quantify the difference between a physical system and the closest member of a robust control model set. The current work looks at extending these approaches to alternative experimentally scenarios. One direction will be the use of correlated swept-sine experiments; a procedure frequently used in industrial practice. A second direction will be the consideration of noise and perturbations from different signal classes; for example stochastic noise and gain bounded perturbations. Such models agree more closely with typical physical systems, and will make these methods applicable to a wider range of industrial processes. We also propose to develop a robust control modeling framework which will handle certain classes of nonlinear systems. The project will consider two industrially motivated examples from these classes: rotating stall in jet engine compressors; and thermo-acoustic interactions in combustors. The methods will be applied to simplified simulation versions of these problems. The combination of nonlinear behaviors and dynamic perturbations opens up an area of nonlinear robustness analysis which will also be addressed. Three experiments are available and will be used in support of this research: (1) A metalorganic chemical vapor deposition (MOCVD) reactor, used for epitaxial crystal growth of blue LEDs and blue laser diodes. (2) A magnetically levitated bearing system, developed as a prototype for an artificial heart pump (left ventricular assist device). (3) A rapid thermal processing system, which models the dynamics of typical processing steps in the semiconductor and film processing industries. Each of these experiments exhibits common practical difficulties which are not yet well handled by theoretical modeling and identification methods, making them ideal testbeds for the work proposed.