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Advanced Topics in Control
Last Updated: 2026-06-03 00:14:06
Abstract
Advanced Topics in Control (ATIC) covers advanced research topics in control theory. It is offered each Spring semester with the topic rotating from year to year. Repetition for credit is possible, with consent of the instructor. During the spring of 2026, the course will cover a range of topics in logic-constrained control systems.
Objective
In this course, we study control problems involving dynamical systems whose behavior is constrained by logical system specifications. By the end of the course, you will have developed a solid and versatile toolkit for translating formal specifications into verified controllers. We will build methodological foundations in three main areas: • Formal modeling of specifications: Boolean and temporal logics, as well as stability and invariance properties. • System verification: sum-of-squares programming, first-order logic solvers, and barrier or Lyapunov functions. • Logic-based control: mixed-integer programming and automata-theoretic methods. Depending on the interests of the participants, we may also explore emerging connections between control, machine learning, and AI — for instance, links between large language models and logic or verification and control of learning-enabled systems. Building on these foundations, we will discuss a range of applications in autonomous systems and robotics.
Content
Logic-constrained control systems arise in a wide range of applications, including multi-robot disaster response, autonomous transportation, and manufacturing. Such systems are typically safety-critical, requiring formal safety certificates, while also being expected to satisfy complex logical specifications that go beyond the stability and invariance properties addressed in standard control courses. The challenges of designing and analyzing these systems stem from their complex dynamics coupled with nonconvex and nonsmooth requirements. This course lies at the intersection of logic, verification, and control, bridging ideas from formal methods (traditionally studied in computer science) and control theory. Students will learn key concepts from both communities and how to integrate them into a unified framework for verified control design. Throughout the course, we will critically assess limitations of the various design methods we encounter.
Resources
Lecture Notes
A complete set of lecture notes and slides will be provided.
Literature
The course will be largely based on lecture notes and research papers/books that will be provided throughout the course.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Advanced Topics in Control |
|
2 h weekly |
| exercise | Advanced Topics in Control |
|
2 h weekly |
Offered In
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Biomedical Engineering Master (Only courses offered under "GESS Science in Perspective" count in this category. See "Offered in" tab in course view. For more information, please refer to )
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Recommended Elective Courses (These courses are particularly recommended for the Bioelectronics track. Please consult your track adviser if you wish to select other subjects.)
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Track: Signal Processing and Machine Learning (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Signal Processing and Machine Learning ", see . The individual study plan is subject to the tutor's approval.)
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Specialization Courses (These specialization courses are particularly recommended for the area of "Signal Processing and Machine Learning", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialization courses during the MSc EEIT.)
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Tracks (all): Electives (Courses from the ETH course catalogue may be chosen in agreement with your tutor. As an alternative to the elective courses, students may do a second semester project or an internship in industry. Please consult your tutor.)
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Doctorate Information Technology and Electrical Engineering (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see sub-categories for details) More Information at )
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Subject Specialisation (The courses on offer below are but a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.)
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