Kristi A. Morgansen
A A 549
Fundamentals of state estimation for linear and nonlinear systems. Discrete and continuous systems. Probability and stochastic systems theory. Models with noise. Kalman-Bucy filters, extended Kalman filters, recursive estimation. Numerical issues in filter design and implementation. Prerequisite: either A A 547, E E 547, or M E 547. Offered: jointly with E E 549/M E 549.
A great many control design and analysis applications involve systems that are not well-understood, and for which detailed models are unavailable. Without an estimate of the state variables of a system, standard control theoretic techniques cannot be applied. To address this problem, system observers have been developed for a number of classes of systems.
This course will focus on development of oberservers and optimal observers for both discrete and continuous time with emphasis on continuous time. Both linear and nonlinear systems will be considered. The course will include a project - with students working in small groups.
The goal of this course is to enable all students to have the skills and knowledge to successfully apply estimation techniques to a variety of applications.
Student learning goals
General method of instruction
Class assignments and grading