ECE 2680: Adaptive
Control (3 Credits, Fall 2023)
Description: Adaptation and learning play an essential role in
biological systems, and these characteristics have
been widely incorporated in modern control systems. This course introduces the
general principles of adaptive control and learning. Topics to be covered
include: real-time parameter estimation, self-tuning regulators,
model-reference adaptive systems, adaptive control of nonlinear systems,
practical aspects and implementation of adaptive control systems, and
introduction to computational learning theory.
Prerequisite: Knowledge of feedback control systems and linear
system theory.
Time and Place: Tuesday 6 pm−8:30 pm; 235 Cathedral of
Learning.
Instructor: Dr. Zhi-Hong Mao, (email) maozh@engr.pitt.edu, (office hours over
Zoom) Monday 3:30 pm−5 pm, (Zoom link) https://pitt.zoom.us/j/6288281300.
Text: S. Sastry and M. Bodson, Adaptive
Control: Stability, Convergence, and Robustness, Prentice-Hall,
1989-1994, Sastry & Bodson,
1994, available for free download at http://www.ece.utah.edu/~bodson/acscr/.
Course Evaluation: Homework 25%, class participation 10%, midterm exam
25%, and final exam 40%.
Tentative schedule for
lectures:
|
Date |
Topic |
|
|
August 29 |
Lecture 1: Course
organization and introduction to adaptive control |
Chapter 0 of the textbook |
|
Sep 5 |
Lecture 2: Mathematical
description of systems |
|
|
Sep 12 |
Lecture 3: Lyapunov stability theory (I) |
Section 1.4 |
|
Sep 19 |
Lecture 4: Lyapunov stability theory (II) |
Section 1.4 |
|
Sep 26 |
Lecture 5: System
identification (I) |
Section 2.0 |
|
Oct 3 |
Lecture 6: System
identification (II) |
Sections 0.3, 1.3, 2.0-2.3,
and 2.5 |
|
Oct 10 |
Lecture 7: Model reference
adaptive control (MRAC) (I) |
Material about the MIT rule |
|
Oct 17 |
Midterm exam |
|
|
|
|
|
|
Oct 24 |
Lecture 8: MRAC (II) |
Section 3.0 |
|
Oct 31 |
Lecture 9: MRAC (III) |
Section 1.5.3 (Lyapunov lemma) and Section 2.6.2 (SPR transfer
functions) |
|
Nov 7 |
Lecture 10: MRAC (IV) |
Section 2.6.2 (SPR transfer
functions) |
|
Nov 14 |
Lecture 11: Self-tuning
control (I) |
Sections 2.0-2.3 and
2.5-2.6 |
|
Nov 21 |
No class (due to
Thanksgiving) |
|
|
Nov 28 |
Lecture 12: Self-tuning
control (II) |
Section 3.2 and notes from
ECE 2646 about state feedback and state estimator |
|
Dec 5 |
Lecture 13: Reinforcement
learning |
|
|
Dec 12 |
Final exam |
|
Course Policies:
Academic Integrity
Students in this course
will be expected to comply with the University of Pittsburgh's Policy on Academic Integrity.
Any student suspected of violating this obligation for any reason during the
semester will be required to participate in the procedural process, initiated
at the instructor level, as outlined in the University Guidelines on Academic
Integrity. This may include, but is not limited to, the confiscation of the
examination of any individual suspected of violating University Policy.
Furthermore, no student may bring any unauthorized materials to an exam,
including dictionaries and programmable calculators.
To learn more about
Academic Integrity, visit the Academic Integrity Guide for an overview
of the topic. For hands-on practice, complete the Academic Integrity Modules.
The Swanson School's
Academic Integrity Guide can be found here: SSOE_AI_Policy.pdf.
Disability Services
If you have a disability
for which you are or may be requesting an accommodation, you are encouraged to
contact both your instructor and Disability Resources and Services (DRS),
140 William Pitt Union, (412) 648-7890, drsrecep@pitt.edu, (412) 228-5347 for P3
ASL users, as early as possible in the term. DRS will verify your disability
and determine reasonable accommodation for this course.