University of California at Berkeley
Department of Electrical Engineering and Computer Sciences
EECS221A
Linear System Theory
Fall Semester 2013
Course information:
UCB OnLine Course Catalog and Schedule of Classes
Lecture Information: TuTh 9.3011, 240 Bechtel
Section Information: F 122, 240 Bechtel
Instructor

Shankar Sastry
717 Sutardja Dai Hall
sastry at eecs.berkeley.edu
Office hours: W 45 (320 McLaughlin), Th 45 (320 McLaughlin) or by appointment
Teaching Assistant

Lillian Ratliff
337 Cory Hall, Desk #11
ratliffl at eecs.berkeley.edu
Office hours: M 12, Th 12, or by appointment. Office hours will be held in Cory Hall 337B.
Course Description
This course provides an introduction to the modern state space theory of linear systems for students of circuits, communications, controls and signal processing. In some sense it is a second course in linear systems, since it builds on an understanding that students have seen linear systems in use in at least some context before. The course is on the one hand quite classical and develops some rather well developed material, but on the other hand is quite modern and topical in that it provides a sense of the new vistas in embedded systems, computer vision, hybrid systems, distributed control, game theory and other current areas of strong research activity.
Topics include:
 A review of linear algebra and matrix theory. The solutions of linear equations.
 Leastsquares approximation, linear programming, singular value decomposition and principal component analysis.
 Linear ordinary differential equations: existence and uniqueness of solutions, the statetransition matrix and matrix exponential.
 Numerical considerations: matrix sensitivity and condition number, numerical solutions to ordinary differential equations, and stiffness.
 Inputoutput and internal stability; the method of Lyapunov.
 Controllability and observability; basic realization theory.
 Control and observer design: pole placement, state estimation.
 Linear quadratic optimal control: Riccati equation, properties of the LQ regulator and Kalman filtering.
 Advanced topics such as robust control, hybrid system theory, linear quadratic games and distributed control will be presented based on allowable time and interest from the class.
It is recommended that students have previously taken a linear algebra course (MATH 110 or equivalent).
Handouts and Lecture Notes
Homework
Announcements
 Instructions on how to install/use Python for scientific computing will be given during the first discussion section. Please bring your machine to the discussion section if one is available to you.
 How to Install Python
Discussion
Links
 The textbook Linear System Theory by Callier and Desoer can be found online through Springer. Link to C&D on Springer Website You must use Berkeley library credentials to access the book. Remotely, you may use a vpn service or a proxy. Instructions for VPN are located here. Instructions for setting up a proxy are located here.

Tutorial for Scientific Computing using Python
 Python Documentation
 Numpy and Scipy Documentation
 Richard Murray's Control Systems Library for Python
 PythonControl Toolbox Documentation
 Matplotlib (Python Plotting Tool)
 Python Bootcamp and corresponding youtube video
 Prof. Claire Tomlin's video lectures on selected topics:
Introduction and Functions , Field and Vectors , Subspaces and Bases
Linear Maps , Matrix Representation of Linear Maps , Change of Basis
Norms , Induced Norms, Inner Products, Adjoints
Hermitian Matrices, Singular Value Decomposition
Fundamental Theorem of Ordinary Differential Equations, BellmanGronwall Lemma
Dynamical Systems, Linearity and Time invariance
Linear Time Varying Systems, State Transition Matrix, Solutions to Linear Time Varying Systems, Jacobian Linearization
The Matrix Exponetial
Cayley Hamilton Theorem
Grading
Homework 30%, there will be 810 problem sets
Midterm 20%, in class and currently scheduled for 29 October
Final 50%
Recommended Reading
Systems:
 F. Callier & C. A. Desoer, Linear System Theory, SpringerVerlag, 1991.
 C.T. Chen, Linear Systems Theory and Design, Holt, Rinehart & Winston, 1999.
 T. Kailath, Linear Systems Theory, PrenticeHall.
 R. Brockett, Finitedimensional Linear Systems, Wiley.
 W. J. Rugh, Linear System Theory, PrenticeHall, 1996.
 D. F. Delchamps, State Space and InputOutput Linear Systems,
Springer Verlag, 1988.
Algebra:
 G. Golub and C. Van Loan, Matrix Computations, Johns Hopkins Press.
 M. Gantmacher, Theory of Matrices, Vol 1 & 2, Chelsea.
 G. Strang, Linear Algebra and its Applications, 3rd edition, 1988.
 G. Strang, Introduction to Linear Algebra, 4th ed., WellesleyCambridge Press, 2009.
Analysis:
 J. Hale, Ordinary Differential Equations, Wiley.
 W. Rudin, Principles of Mathematical Analysis, McgrawHill.
 W. Rudin, Real and Complex Analysis, McgrawHill.
 B. Rynne and M.A. Youngson, Linear Functional Analysis, Springer, 2007.