报告摘要：This talk focuses on how control and identification are used in developing a next generation CT scanner. The problem considered is to improve imaging quality and to reduce contrast dose and radiation exposure of a modern CT scanner. To combat mismatch of the bolus peak density and the imaging aperture in a modern CT, an optimal adaptive bolus chasing controller is proposed and experimentally tested. The controller estimates and predicts the unknown two dimensional bolus density on line and then determines the optimal control actions. Tracking errors are mathematically quantified in terms of estimation errors. The test results not only support the analytical analysis and exhibit its superior performance over the current constant velocity controller, but also demonstrate the clinical feasibility.

报告人简历：Erwei Bai received his PhD degree from University of California in Berkeley, U.S.A. He is Professor of Electrical Engineering at the University of Iowa and also holds the title of World Leading Class Research Professor, Queen's University, Belfast, UK. He teaches and conducts research in identification, signal processing and their applications in engineering and life science.

Dr. Bai is a Fellow of IEEE and a recipient of the Presidential Award for Teaching Excellence and the Board of Regents Award for Faculty Excellence.