Cleveland State University

Department of Electrical Engineering and Computer Science

EEC 693/793, Section 50 - Special Topics

State Estimation

Fall 2016

Description: This course covers mathematical approaches to the best possible way of estimating the state of a dynamic system. Although the course is firmly grounded in mathematical theory, the approaches are given with the goal of eventual implementation in software. The goal of the course is to present state estimation theory in the most clear yet rigorous way possible, while providing enough advanced material and references so that the student is prepared to contribute new material to the state of the art. Engineers are usually concerned with implementation, and so the material presented is geared towards discrete time systems. However, continuous time systems are also discussed since many system models are formulated with real-time dynamics.

Text: Optimal State Estimation, by Dan Simon (John Wiley & Sons, 2006)

Prereqs: - EEC 510 (Linear Systems)
- Familiarity with basic concepts in probability and stochastic processes
- Mathematical maturity (calculus, control theory, signal processing, etc.)
- Experience with Matlab programming (http://www.mathworks.com/)

Time: M W 4:00 - 5:50

Place: TBD

 Instructor: Dan Simon Phone: 216-687-5407 Fax: Email: 216-687-5405 d.j.simon@csuohio.edu Web: Course web site: Office: http://academic.csuohio.edu/simond/courses/eec693a Stilwell Hall 343 Office Hours: M W 2:00 - 3:50

Feel free to email, call, or stop by my office any time and I'll be happy to help you if I'm available.

References: See Appendix B in the text.

Homework............................... 20%

Quizzes and Participation.......... 20%

Midterm................................... 20%

Project..................................... 20%

Final Exam................................ 20%

A................ 93 - 100

A minus...... 90 - 93

B plus......... 87 - 90

B................ 83 - 87

B minus...... 80 - 83

C plus......... 77 - 80

C................ 70 - 77

No extra credit assignments will be available.

Homework: Late homework will not be accepted. Sometimes unexpected events occur that prevent a student from being in class on the day that homework is due. The best way to make sure that these unexpected events do not affect your grade is to finish the homework early, and then if you have to miss class you can fax your homework to the instructor, or send it to class with one of your classmates. Students are encouraged to work together on homework, but students who hand in identical assignments will be given a grade of zero on that assignment.

Tests: Quizzes and Exams will be open book and open notes. No makeup quizzes or exams will be allowed without the prior permission of the instructor.

Topics: Introductory material: Linear systems, Probability, Least squares estimation
Kalman filtering
H-infinity filtering
Nonlinear filtering

Important Dates:

September 2 - Last day to drop with full refund

September 4 - Last day to add

September 5 - Holiday

September 9 - Last day to drop

November 4 - Last day to withdraw

December 12 - Final exam