Schedule Textbook Videos Diderot KeYmaera X
- This course will use Diderot for active learning quizzes and Q&A. If you do not have access to Diderot, look through your email for instructions on how to activate your account and drop me an email if it does not work.
Cyber-physical systems (CPSs) combine cyber
capabilities (computation and/or communication) with physical
capabilities (motion or other physical processes).
Cars, aircraft, and robots are prime examples, because they
move physically in space in a way that is determined
by discrete computerized control algorithms.
Designing these algorithms to control
CPSs is challenging due to their tight coupling with physical behavior.
At the same time, it is vital that these algorithms be correct,
since we rely on CPSs for safety-critical tasks like keeping aircraft from colliding.
In this course we will strive to answer the fundamental question posed by Jeannette Wing:
"How can we provide people with cyber-physical systems they can bet their lives on?"
Students who successfully complete this course will:
- Understand the core principles behind CPSs.
- Develop models and controls.
- Identify safety specifications and critical properties of CPSs.
- Understand abstraction and system architectures.
- Learn how to design by invariant.
- Reason rigorously about CPS models and their differential equations.
- Verify CPS models of appropriate scale with logic.
- Understand the semantics of a CPS model.
- Develop an intuition for operational effects.
This course will give you the required skills to formally analyze the CPSs that are all around us -- from power plants to pace makers and everything in between -- so that when you contribute to the design of a CPS, you are able to understand important safety-critical aspects and feel confident designing and analyzing system models. It will provide an excellent foundation for students who seek industry positions and for students interested in pursuing research.
- METHOD OF EVALUATION:
- Grading will be based on a final exam with a bonus that can be earned by successfully completing homework exercises.
- PRIOR INSTANCES:
- Prior instances of the course: F2013, F2014, S2016, S2017, F2018, F2019, F2020, F2021 by André Platzer at Carnegie Mellon University.
The instructor greatly appreciates the help by other members of the Alexander von Humboldt Professor group for Logic of Autonomous Dynamical Systems at KIT and the Logical Systems Lab, Carnegie Mellon University, especially Noah Abou El Wafa for helping with some recitations and Stefan Mitsch, for advancing KeYmaera X.