课题基金 / 基金详情

Robust Adaptive Control Based on Kharitonov Theory and Its Extensions

Robust Adaptive Control Based on Kharitonov Theory and Its Extensions
基于Kharitonov理论及其扩展的鲁棒自适应控制
批准号:
9417004
负责人:
Aniruddha Datta
金额:
$28.28万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1995
资助国家:
美国
项目状态:
已结题
起止时间:
1995-09-01 至 2000-08-31

项目摘要

项目成果

Aniruddha Datta的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
August 2, 19959417004 Datta The research proposed here addresses fundamental problems in three distinct areas: a)Robust Control with an emphasis on parametric uncertainty b)Adaptive Control with an emphasis on robustness and performance issues and c)Robust Adaptive Control with the thrust being the development of new quantitative analysis and design methods exploiting the recent explosion of results obtained using Kharitonov's Theorem and its extensions. First, we intend to develop "best case" results involving the parametric stability margin, Hoo stability margin (norm), gain and phase margins over a parametrized set of transfer functions, such as an interval plant. These robustness results in the area of Robust Parametric Stability, would then be used for non- conservatively quantifying the robustness of adaptive control schemes. The second objective is to develop extremal parametric results involving the H2 and L1 norms which, we believe, will play an important role in studying adaptive system performance. The third objective is to address some important open problems in each of the areas of adaptive control and robust parametric stability. The objectives mentioned above are motivated from our prior research which has not only enabled us to identify some of the outstanding unresolved problems in the areas of adaptive control and robust parametric stability, but has also highlighted the need for inter-twined research efforts in these two traditionally very diverse fields. None of the existing theory in either of these fields can solve the problems related to this proposal in a practical or satisfactory manner. However, successful resolution of these problems is imperative from both a theoretical and a practical point of view. Indeed, practitioners of both robust and adaptive control stand to benefit a lot from the "non- conservative" parametric L1 and Hoo robustness results that we seek to develop. ***
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
I-Corps: Model-driven precision oncology for cancer therapy design
Cancer Therapeutics through Theory and Experiment: From Cell Lines to Canine Tumors Grown on the Back of Mice
Identification of Drug Targets and Their Validation in Cancer Therapy Design
Exploiting The Heterogeneous Composition Of Tumor Tissue And The Altered Metabolism Of Tumor Cells For Cancer Therapy Design
海外基金