CDS 110b: Kalman Filters

CDS 110b

Schedule

Project

Course Text

In this lecture we introduce the optimal estimation problem and describe its solution, the Kalman (Bucy) filter. We discuss the extension of Kalman filters to nonlinear systems (the EKF) as well as the Linear Quadratic Guassian (LQG) problem.

• Lecture notes (from 2007)
• HW #6 (due 27 Feb 08)
  • LN-200 IMU data sheet
  • PVTOL example: pvtol_run.m, pvtol.m

References and Further Reading

• R. M. Murray, Optimization-Based Control. Preprint, 2008: Chapter 5 - Kalman Filtering

Frequently Asked Questions

Q (2007): you asked what the estimator for the ducted fan would show (compared to eigenvalue placement). What should we be looking at and how would we be making those guesses?

This was not such a great question because you didn't have enough information to really make an informed guess. The main feature that is surprising about the result is that the convergence rate is much slower than eigenvalue placement.