Abstract

Almost all dynamical systems allow only partial observation of their states. To fully understand these dynamics, the remaining states need to be estimated.

In this talk, Dr. Emzir will intuitively discuss state estimation problems through examples. He will heuristically construct the Kalman filter from static localization problems. He will then discuss nonlinear variants of the Kalman filter and a few ongoing research directions on this vast topic.

About the Speaker

Dr. Muhammad Emzir is an Associate Professor of Control and Instrumentation Engineering in the Control and Instrumentation Engineering Department at King Fahd University of Petroleum and Minerals, Saudi Arabia. He earned his Ph.D. in Electrical Engineering at UNSW, then held postdoctoral positions at ANU and Aalto University. His research spans state estimation, nonlinear and data-driven control, and autonomous systems.