Time and Place: Tu&Th at 1:30-3:00pm in Room 1001 EECS Bldg.

Instructor: A. Galip Ulsoy, Professor of MEAM.

Office: Room 2236 G. G. Brown, Office Tel: 764-8464, Home Tel: 426-1427.

Office Hours: Drop in anytime during my office hours, which are TuTh at 3:00-3:30, and Wed 3-5pm. Otherwise call to make an appointment, or contact me via e-mail: ulsoy@engin.umich.edu

Description: This course will cover the theory and application of adaptive control systems. We will cover what adaptation is and when it is needed, parameter adaptation algorithms, direct and indirect adaptive methods, model reference adaptive control, self-tuning control systems, stability and convergence of adaptive algorithms, as well as robustness of adaptive controllers and averaging. Also discussed are auto-tuning, gain scheduling, alternatives to adaptive control, implementation aspects of adaptive control, and applications.

Objectives: To provide a graduate level introduction to Adaptive Control Systems. Students will be introduced to the basic concepts and terminology, the state-of-the-art, and basic methodologies. They will, upon completion of the course, be able to read the literature on this subject, and to do independent design, research and development work in the field.

Prerequisites: ME561/EECS561/AERO571 Digital Control Systems (or equivalent).

Textbook: Astrom, K.J., and B. Wittenmark, Adaptive Control, Addison-Wesley, Reading, Massachusetts, 2nd edition, 1995. There will be occasional handouts to supplement the textbook. See the attached Course Outline for specific reading assignments.

Homework: See the Course Outline for due dates for the homework sets. There is a separate handout listing the assigned problems from your textbook. Homework sets are due at the beginning of the class period on Thursdays, and late homework will not be accepted. Homework solutions will be handed out in class.

Project: A "mini" course project is incorporated into each of the homework sets. You choose a project topic at the beginning of the term, and one problem in each homework set is a part of your project. A final project report at the end of the term is also required.

Software: The course will require extensive use of computer simulation, and Matlab is highly recommended. A control tutorial for Matlab is available at http://www.engin.umich.edu/class/ctms/ and is highly recommended.

Examinations: A final examination will be given on the date indicated on the course outline. Failure to take the examination will result in a grade of zero, and a make up exam will not be given, except in cases of documented emergencies.

Grading: Homework & Project 60% Final examination 40%

Internet: This syllabus, homework assignments, and homework solutions will be on the world wide web at http://www-personal.engin.umich.edu/~ulsoy/ME661.html .

COURSE OUTLINE (Tentative)

DATE

TOPICS

READING

DUE DATES

Th 9/7

Intro. to course, and adaptive control

1.1-1.4

 

Tu 9/12

What is AC and when do we need it?

1.5-1.7, 12.1-12.9

 

Th 9/14

Parameter estimation algorithms

2.1-2.3

 

Tu 9/19

Parameter estimation algorithms

2.4-2.7

 

Th 9/21

Implementation of estimators

11.5-11.6

 

Tu 9/26

Self Tuning Regulators

3.1-3.2, 11.1-11.4

 

Th 9/28

Self Tuning Regulators

3.3-3.5

HW Set #1

Tu 10/3

Self Tuning Regulators

3.6-3.7

 

Th 10/5

Stochastic & Predictive STR

4.1-4.2

 

Tu 10/10

Stochastic & Predictive STR

4.3-4.4

 

Th 1012

Stochastic & Predictive STR

4.5-4.7

HW Set #2

Tu 10/17

Model Reference Adaptive Control

5.1-5.2

 

Th 10/19

Design of MRAC

5.3-5.5

 

Tu 10/24

Design of MRAC

5.6-5.7

 

Th 10/26

Design of MRAC

5.8-5.9

 

Tu 10/31

Force Control in Turning (Y. Koren)

handout

 

Th 11/2

Nonlinear A.C.

5.10-5.11

HW Set #3

Tu 11/7

Adaptive Systems Theory, Stability

6.1-6.3

 

Th 11/9

NO CLASS

 

 

Tu 11/14

Stability of Indirect and Direct A.C.

6.4-6.5

 

Th 11/16

Averaging

6.6-6.8

HW Set #4

Tu 11/21

Averaging, Robustness, Robust AC

6.9-6.10

 

Th 11/23

THANKSGIVING RECESS

 

 

Tu 11/28

NO CLASS

 

 

Th 11/30

NO CLASS

 

 

Tu 12/5

Stochastic AC, Auto-tuning

7.1-7.7, 8.1-8.7

 

Th 12/7

Gain Scheduling, Nonlinear transformations

9.1-9.6

HW Set #5

Tu 12/12

Alternatives to adaptive control

Review, preview & course evaluation

10.1-10.5

13.1-13.7

 

Fri 12/15

FINAL EXAM (4-6pm)

 

PROJ REPORT