E1 246: Topics in Networked and Distributed Control (3:0), August 2024

Instructor

Vaibhav Katewa
Assistant Professor
Robert Bosch Center for Cyber-Physical Systems (RBCCPS)

Class timings

Tue-Thu, 2:00-3:30 PM.

Venue

IDR Building, Room 329

Class logistics

We will have in-person classes. Once the class registration is finalized, the students will be added to a Class group in Microsoft Teams. All the course correspondence will happen in this Teams group. We will occasionally use the Matlab software for simulations.

Course overview and syllabus

Networked control systems is broad term used to describe dynamical systems that are distributed in nature and are integrated with communication, computation and processing technologies. This interplay of control, communication and computation presents several new and interesting problems that are typically not encountered in traditional systems. This course will provide students an exposure to this emerging interdisciplinary field. We will study key problems, frameworks and results using research papers and monographs.

Students will be asked to read research papers and discuss them in the class. They will also go into depth in one of topics through a class project that can be aligned with their current research or project.

The course structure is flexible and we can add/remove topics, go into detail/skip the details based on the interests of the students. I plan to cover the following topics:

1. Consensus over networks with applications in synchronization and opinion dynamics

2. Estimation and control over imperfect communication channels (erasure, delay, etc.) 

3. Stabilization over rate-limited and quantization channels

4. Decentralized optimal control and information patterns

5. Data-driven and learning-based control

6. Security and privacy in networked control systems

7. Any other topic of interest if time permits

Pre-requisites

Background in linear algebra/matrix theory and probability is required. Some exposure to graduate level linear systems theory, estimation theory or random processes is preferred. I will have a discussion with the students to assess their suitability for the class.

Grading

1. Assignments: 25%

2. Class Project: 45%

3. Paper readings and presentations: 30%

References

There is no required textbook for the course and most of the material is based on research papers. These papers will be made available to the students as the course proceeds. A minor portion of the course material is based on the following textbooks:

1. Alberto Bemporad, Maurice Heemels, and Mikael Vejdemo-Johansson. Networked Control Systems. Lecture Notes in Control and Information Sciences, Vol. 406, Springer-Verlag London, 2010.

2. Serdar Yüksel and Tamer Başar. Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints. Springer Science & Business Media, 2013.

3. Mehran Mesbahi and Magnus Egerstedt. Graph Theoretic Methods in Multiagent Networks. Princeton University Press, 2010.

4. Francesco Bullo. Lectures on Network Systems (http:motion.me.ucsb.edu/book-lns)

5. Francesco Bullo, Jorge Cortes, and Sonia Martinez. Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms. Princeton University Press, 2009.