Nonlinear System Identification with Application to Combustion Instability Control

robert R Bitmead，加州大学圣地亚哥分校机械与航天工程系。系统辨识是利用实验测量数据和物理推理的候选模型结构拟合数学动态模型的科学。在分析复杂和不精确的已知系统之前，识别是开发模型的关键。这个项目是关于发展技术和基础理论的非线性系统识别。目前缺乏关于如何在这种情况下进行的工具和指导。虽然重点是科学和广泛的，但研究将继续考虑与理论相结合的燃烧不稳定控制的主要驱动应用，在喷气发动机和燃气动力涡轮机中感兴趣。该项目有几个阶段，其中一般概念被开发，然后在燃烧不稳定性的背景下进行探索。制定合适的拟合措施，然后对模型进行信心测试，将是早期的目标。这些应该捕捉非线性振荡系统数据记录中的重要特征，而忽略不重要的细节。在这里，可以用已经与数据拟合的模型进行测试。具体地说，诸如分岔分析之类的非线性工具可以用于评估模型属性，这些属性可以从一个实验保存到另一个实验，并可能形成控制设计的基础。主要的理论任务是解决模型验证的概念，如振荡器系统。也就是说，一个人如何开发一个实验，能够揭示使用某些标准拟合的特定候选模型的弱点。这与对已确定模型的信心以及对其使用适用性的不确定性密切相关。如果开发出一般化的概念和有意义的测试，这些工具的应用就有现成的市场。的确，非线性控制设计近年来在理论和实践上都取得了很大的进展，但它需要已知可靠度的良好模型才能走得更远。

Abstract-0200449Robert R. Bitmead, U. of Cal-San DiegoNonlinear System Identification with Application to Combustion Instabillty ControlRobert R Bitmead, Department of Mechanical & Aerospace Engineering, U of California-San Diego.System Identification is the science of fitting mathematical dynamical models using measured data from experiments together with candidate model structures from physical reasoning. Identification is critical in developing models of complex and imprecisely known systems prior to their analysis. This project is concerned with developing techniques and underpinning theories for nonlinear system identification. At present there is a dearth of tools and guidance of how to proceed in this case. While the focus is scientific and broad, the study will proceed by considering in tandem with theory a major driving application of combustion instability control, of interest in jet engines and gas power turbines.The project has phases in which general concepts are developed and then are explored in the context of the combustion instabilities. Developing suitable measures of fit and then tests of confidence of models will be early goals. These should capture the important features in the data records from the nonlinear oscillating system while ignoring the unimportant detail. Here tests can be made with models already fitted to the data. Specifically nonlinear tools such as bifurcation analysis then can be applied for the assessment of model properties which are preserved from experiment to experiment and which might form the basis of control design.Chief among the theoretical tasks is to address the concept of model validation for such systems as oscillators. That is, how might one develop an experiment, which is capable of revealing the weaknesses of a particular candidate model fitted using some criterion. This is intimately connected with confidence in the identified model and with uncertainty in its suitability for a use. Should generalized concepts and meaningful tests be developed, there is a ready market for the application of these tools. Indeed, nonlinear control design has moved forward greatly recently in theory and practice, but it needs good models of known reliability to go much further.