ESE601: Hybrid Systems

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Course info:

Schedule: Monday,Wednesday 15.00 - 16.30 at LRSM 112B (new classroom)

Instructor: Agung Julius, agung@seas.upenn.edu

Teaching assistant: Ali Ahmadzadeh, aliahmad@grasp.upenn.edu

Office hours: Agung Julius Tue 2-3pm (Levine 465)

                        Ali Ahmadzadeh Fri 3-5pm (Main GRASP Lab, Levine 4th floor)

Course description: Hybrid systems are dynamical systems that have both continuous and discrete aspects. Hybrid systems has been used as modeling framework in many fields, including, embedded systems, robotics, real-time software, transportation systems, process control, biological systems, etc. The field of hybrid systems is relatively new, and it is rapidly growing. The reason behind the rapid growth is two-fold: from the practical side is the wide applicability of hybrid systems, and from the scientific side is its potential of being an ideal hotbed for cross fertilization of various disciplines, in particular, traditional control theory and theoretical computer science.

The course will be centered around the emerging field of hybrid systems. Started with introductory material, including a review on necessary background material, the course will cover a number of contemporary topics in hybrid systems. Topics such as, modeling and simulation, and verification of hybrid systems will be covered, together with an introduction to relevant software tools. We shall also discuss the use of hybrid systems in modeling real systems, such as robotics, biological systems, transportation systems, etc. Other relevant topics, such as, systems abstraction, stability analysis, controller synthesis and stochastic hybrid systems will also be covered, starting with introductory until state-of-the-art material.

The goal of the course is to provide students with necessary knowledge to: (a) apply hybrid systems in their research, or/and (b) do their own research in the field of hybrid systems.
 

Prerequisites: The course is open to graduate students that have taken undergraduate courses on linear algebra and calculus. Also, it is assumed that the students have some working knowledge on some programming language, such as C or MATLAB. Some knowledge about linear systems theory, discrete event systems theory and probability theory is an advantage. However, the course will provide a short review on the necessary background material.

Grading: There will be three homework sets and one course project. The homework sets make up 45% of the final grade. The final project makes up the remaining 55%.

Mailing list: The class mailing list has been set up. If you haven't received any email from the mailing list, and wish to be included, send me an email.

Course Outline (tentative):

Presentation schedule

Links:

Hybrid systems courses at:

• UC Berkeley (Shankar Sastry and others)
• U. Vanderbilt (John Koo)
• Stanford (Claire Tomlin)
• U. Toronto (Mireille Broucke)