US-France Cooperative Research (INRIA): Control of Interactive Structures with Dynamic Shells

0226961Lasiecka 这项为期三年的美法应用数学合作奖涉及弗吉尼亚大学和位于法国罗康古和索菲亚安提波利斯的国家信息与自动化研究所 (INRIA) 的研究团队。 由美国的 Irena Lasiecka 和法国的 Michel Bernadou 领导的研究人员提议研究偏微分方程描述的控制理论模型的一般领域的问题。 这些主题与动态壳模型的稳定性和优化控制有关，其中控制动作和传感是通过智能材料技术实现的。 其中包括压电陶瓷或压电元件、磁致伸缩装置和流变液。理论分析，重点是逆估计类型，将通过数值算法和收敛分析达到高潮。 将采用两种控制建模方法。 第一个是压电壳建模，将由法国团队进行研究。 美国在基于连接到弯曲壁的压电贴片的方法方面的专业知识对此进行了补充。 这些互补的方法将导致两种不同的控制模型。该奖项代表了美国方面向 NSF 和 INRIA 提出的并行提案。 NSF 将为美国调查员和研究生每年访问法国提供旅费和生活费。 INRIA 将支持法国研究人员访问美国。该项目将增进对控制模型及其在智能材料技术和材料工程中的应用的理解。

0226961LasieckaThis three-year award for US-France collaboration in applied mathematics involves research teams at the University of Virginia and the Institut National pour la Recherche en Informatique et en Automatique (INRIA) in Rocquencourt and Sophia Antipolis, France. Led by Irena Lasiecka in the US and Michel Bernadou in France, the researchers propose to study problems in the general area of control theory models described by partial differential equations. The topics are related to stabilization and optimal control of dynamical shell models where control actions and sensing are implemented via smart materials technology. These include piezoceramic or peizoelectric elements, magnetostrictive devices and rheological fluids. The theoretical analysis, with a focus on inverse type of estimates, will culminate with numerical algorithms and convergence analysis. Two approaches to control modeling will be pursued. The first, piezoelectric shell modeling, will be investigated by the French team. This is complemented by US expertise in an approach based on piezoelectric patches attached to a curved wall. These complementary approaches will lead to two different control models.This award represents the US side of parallel proposals to the NSF and INRIA. NSF will cover travel funds and living expenses for annual visits to France by the US investigator and graduate student. INRIA will support visits by French researchers to the United States. The project will advance understanding of control models and their applications to smart materials technology and materials engineering.