(328b) The Moving Horizon State Estimation Problem: Formulation and Results

If memory serves, I met Jay H. Lee at the Chemical Process Control meeting, CPC
IV, in Padre Island, Texas, when he was a 26-year-old recently hired assistant
professor at Auburn University. He later invited me to visit his research group
at Auburn in May 1992. Over dinner during that visit Jay and I started a
collaboration on the state estimation technique known as moving horizon
estimation.

In honor of Jay's 60th birthday, this talk provides a summary of how research on
moving horizon estimation, and its predecessor, Kalman filtering of linear systems, has
grown and evolved during the intervening 30 years. The talk lays out the basic
problem formulation and assumptions, and summarizes the current state-of-the-art
in research. The talk concludes by summarizing some currently open research
challenges in state estimation.