Adaptive and Robust Nonlinear Control

9528370科科托维奇这是一项继续我们的国家科学基金#ECS-9203491补助金的建议，该补助金将于1995年8月31日到期。提案的第一部分总结了我们目前拨款的成果，这些成果已在550页的专著中提出，并在20多篇参考期刊论文和更多的会议论文中发表。我们的主要成就之一是针对具有参数和函数不确定性的非线性系统的新的递归、自适应和健壮的设计方法(“反推”)。对于我们的自适应设计，我们得到了性能界，在线性系统的情况下，表明它们的性能优于传统的自适应方案。尽管我们目前的成果得到了研究界的极大好评，也激发了人们对应用程序的兴趣，但我们对其局限性的批判性审查促使我们提出了这项建议的主要主题：第一，继续从可行设计到可实施设计的发展，第二，为更大类别的系统开发新的设计程序。我们还建议开始深入研究非线性反馈回路的结构特定的鲁棒性，特别是那些通过我们的自适应过程诊断的反馈回路。为了使我们的递归过程对应用程序更有吸引力，我们建议开发精益回溯设计，以避免浪费的取消并减少控制工作量。为此，我们将进一步发展我们的逆最优设计。为了扩展系统的类别，我们计划开发新的转发过程，作为反推的上三角类似。我们将通过应用程序驱动的“形状”不确定性来扩展不确定性的表征，并开发“形状稳健”控制器。我们的稳健性研究将量化性能稳健性的权衡，并开发重新设计以增强稳健性，同时将性能损失降至最低。我们由NSF支持的研究为我们与联合技术公司、福特汽车公司和罗克韦尔国际公司的工业合作提供了理论基础，并受到了这些合作的推动。***

9528370 Kokotovic This is a proposal for continuation of our NSF Grant #ECS-9203491 which expires on August 31, 1995. Part one of the proposal summarizes the results under our current grant which have been presented in a 550-page monograph, and in over 20 refereed journal papers and more numerous conference papers. Among our major accomplishments are new recursive adaptive and robust design procedures ("backstepping") for nonlinear systems with parametric and functional uncertainties. For our adaptive designs we have derived performance bounds which, in the case of linear systems, show that they outperform traditional adaptive schemes. Although our current results have been extremely well received by the research community and have also stimulated interest in applications, our critical examination of their limitations has motivated the main topics of this proposal: first, to continue to the development from feasible to implementable designs, and, second, to develop new design procedures for larger classes of systems. We also propose to initiate an in-depth study of structure-specific robustness properties of nonlinear feedback loops, especially those diagnosed by our adaptive procedures. To make our recursive procedures more attractive for applications, we propose to develop lean backstepping designs which avoid wasteful cancellations and reduce control effort. For this purpose we will further develop our inverse-optimal designs. To extend the classes of systems, we plan to develop new forwarding procedures as upper-triangular analogs of backstepping. We will extend characterizations of uncertainties by application-motivated "shape" uncertainties and develop "shape-robust" controllers. Our robustness studies will quantify performance-robustness trade-offs and develop redesigns to enhance robustness while minimizing the loss of performance. Our NSF-supported research provides a theoretical base for, and is motivated by, our industrial cooperation with United Technologies, Ford Motor Company and Rockwell International. ***