报告内容摘要

Adaptive/neural network control is a nonlinear controller design for systems with uncertainties. However, lack of transient analysis and tuning guidance greatly prevents its large scale industrial implementation. Utilizing fast and robust adaptation, an L1 adaptive control architecture is developed to handle time-varying parameters instead of constant or slowing varying ones. In addition, it can be extended to systems with nonlinear time-varying uncertainties and unmodelled dynamics.  The L1 adaptive control has already been applied to various applications, including flight tests on unmanned aerial vehicles.

报告人简介

Dr. Chengyu Cao is currently an Associate Professor in the Mechanical Engineering Department at the University of Connecticut. He received his Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology in 2004. He earned his B.S. degree in Electronics and Information Engineering from Xi'an Jiaotong University, China and M.S in Manufacturing Engineering from the Boston University in 1995 and 1999, respectively. Dr. Cao’s research is in the area of adaptive control & estimation, unmanned and intelligent systems with an emphasis in aerospace applications. He has published one book and over one hundred papers in journals and peer-reviewed conference proceedings. His current research projects are mainly supported by NSF, NASA, and Pratt & Whitney, etc.

欢迎广大师生光临！