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Instructor Class Description

Time Schedule:

Kristi A. Morgansen
A A 549
Seattle Campus

Estimation and System Identification

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.

Class description

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

Recommended preparation

Class assignments and grading

The information above is intended to be helpful in choosing courses. Because the instructor may further develop his/her plans for this course, its characteristics are subject to change without notice. In most cases, the official course syllabus will be distributed on the first day of class.
Last Update by Kristi A. Morgansen
Date: 02/28/2005