EE 635 - Control System Theory

Announcement (Semester 1, 2017)

Exams

Homework

Lecture Notes

Acknowledgement: Most materials will be from the lecture notes of EE263 and EE363, Prof. Stephen Boyd, Stanford University. For each topic in the following, the lectures in () are the corresponding handouts which can be downloaded from EE263 and EE363 websites.

  1. Overview (lecture 1, EE263)
  2. Linear functions: engineering examples (lecture 2-3, EE263)
  3. Reviews on linear algebra
  4. Autonomous linear dynamical systems (lecture 24, EE263)
  5. Solution via Laplace transform and matrix exponential (lecture 25, EE263)
  6. Dynamic interpretation of eigenvectors (lecture 26, EE263)
  7. Jordan canonical form (lecture 27, EE263)
  8. Linear dynamical systems with inputs and outputs (lecture 28, EE263)
  9. Linear Least-squares and minimum-norm methods (lecture 12-17, EE263)
  10. Controllability and state transfer (lecture 29, EE263)
  11. Observability and state estimation (lecture 30, EE263)
  12. Canonical forms
  13. Minimal realization and PBH test
  14. Observer-Based controller design
  15. Basic Lyapunov theory (lecture 12, EE363)
  16. Stability of Linear systems and Lyapunov equation (lecture 13, EE363)
  17. LQR and Steady State Riccati equation (revised on 9/3/2012)
  18. LQG controller (revised on 9/3/2012)
  19. Estimation (lecture 7, EE363)
  20. The Kalman filter (lecture 8, EE363)
  21. Linear matrix inequalities in control theory (lecture 15, EE363), supplement note on LMI (revised on 9/16/2012)

Course Information

Course syllabus in English can be downloaded here.

Lectures:

EE 404, MW 1-2:30 PM

Textbooks:
  • C.T. Chen, Linear System Theory and Design, 2nd edition, 1995
  • C.T. Chen, Linear System Theory and Design, 3rd edition, 1998
  • T.Kailath, Linear Systems, Prentice-Hall, 1980
Grading:

Weekly Homework 30% Midterm 30% Final 25% Term project 15%

Prerequisites:

Students should have seen topics on linear algebra and matrices. However, a short review will be given briefly in week 1. These topics include vector space, basis/dimension, rank and null space of a matrix, vector/matrix norms, linear equations, eigenvalue problem.