Mathias Hudoba de Badyn: Catalogue data in Spring Semester 2023 |
| Name | Dr. Mathias Hudoba de Badyn |
| Department | Information Technology and Electrical Engineering |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 227-0680-00L | Building Control and Automation MIBS: This course must be taken in the first year of coursework. | 3 credits | 2V + 2U | V. Behrunani, R. Smith, C. Gähler, M. Hudoba de Badyn, M. Yazdanie | |
| Abstract | Introduction to basic concepts from automatic control theory and their application to the control and automation of buildings. | ||||
| Learning objective | Introduce students to fundamental concepts from control theory: State space models, feedback. Demonstrate the application of these concepts to building control for energy efficiency and other objectives. | ||||
| Content | Introduction to modeling State space models and differential equations Laplace transforms and basic feedback control Discrete time systems Model predictive control for building climate regulation Regulating building energy consumption and energy hub concepts Practical implementation of Building Automation (BA) systems: - Energy-efficient control of room air quality, heating and cooling, domestic hot water, shading, etc. - Stability and robustness; Cascaded control | ||||
| Prerequisites / Notice | Exposure to ordinary differential equations and Laplace transforms. | ||||
| 227-0690-12L | Advanced Topics in Control | 4 credits | 2V + 2U | F. Dörfler, M. Hudoba de Badyn | |
| 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 2020, the course will cover a range of topics in distributed systems control. | ||||
| Learning objective | By the end of this course you will have developed a sound and versatile toolkit to tackle a range of problems in network systems and distributed systems control. In particular, we will develop the methodological foundations of algebraic graph theory, consensus algorithms, and multi-agent systems. Building on top of these foundations we cover a range of problems in epidemic spreading over networks, swarm robotics, sensor networks, opinion dynamics, distributed optimization, and electrical network theory. | ||||
| Content | Distributed control systems include large-scale physical systems, engineered multi-agent systems, as well as their interconnection in cyber-physical systems. Representative examples are electric power grids, swarm robotics, sensor networks, and epidemic spreading over networks. The challenges associated with these systems arise due to their coupled, distributed, and large-scale nature, and due to limited sensing, communication, computing, and control capabilities. This course covers algebraic graph theory, consensus algorithms, stability of network systems, distributed optimization, and applications in various domains. | ||||
| Lecture notes | A complete set of lecture notes and slides will be provided. | ||||
| Literature | The course will be largely based on the following set of lecture notes co-authored by one of the instructors: http://motion.me.ucsb.edu/book-lns/ | ||||
| Prerequisites / Notice | Sufficient mathematical maturity, in particular in linear algebra and dynamical systems. | ||||