Master the foundations of autonomous system modeling, from state-space representations to hybrid automata.
Master the foundations of autonomous system modeling, from state-space representations to hybrid automata.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Foundations of Autonomous Systems Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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English
What you'll learn
Model autonomous systems using state-space representations
Understand timed and hybrid automata concepts
Analyze system behaviors and compositions
Implement various system interconnection methods
Apply modeling techniques to real-world autonomous systems
Skills you'll gain
This course includes:
4 Hours PreRecorded video
6 assignments
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FullTime access
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There are 4 modules in this course
This comprehensive course explores the modeling of autonomous systems, covering everything from basic state diagrams to complex hybrid automata. Students learn fundamental principles of system modeling through real-world examples like the Ariane 5 rocket and self-driving cars. The curriculum progresses from foundational concepts to advanced topics in system composition and behavior analysis, incorporating both theoretical frameworks and practical applications in autonomous system design.
Course Introduction
Module 1 · 1 Hours to complete
Foundations of Autonomous Systems Modeling
Module 2 · 1 Hours to complete
Modeling Physical Systems and Hybrid Systems
Module 3 · 2 Hours to complete
Systems' Behaviors and Composition
Module 4 · 2 Hours to complete
Fee Structure
Instructor
Associate Professor
Majid Zamani is an Associate Professor in the Computer Science Department at the University of Colorado Boulder. He previously served as an Assistant Professor in the Department of Electrical Engineering at the Technical University of Munich from May 2014 to January 2019, where he led the Hybrid Control Systems Group. Dr. Zamani earned his Ph.D. and M.A. in Mathematics from the University of California, Los Angeles (UCLA) in 2012, along with an M.Sc. in Electrical Engineering from Sharif University of Technology in 2007 and a B.Sc. in Electrical Engineering from Isfahan University of Technology in 2005.His research focuses on critical areas such as verification and control of cyber-physical systems, secure-by-construction synthesis, information-based control, and the compositional analysis and synthesis of interconnected systems. Dr. Zamani has received numerous accolades for his work, including the George S. Axelby Outstanding Paper Award from the IEEE Control Systems Society in 2023, the NSF CAREER Award in 2022, and grants from the European Research Council in both 2018 and 2023.At CU Boulder, he teaches courses such as "Modeling of Autonomous Systems," "Requirement Specifications for Autonomous Systems," and "Verification and Synthesis of Autonomous Systems." Through his teaching and research initiatives, Majid Zamani is dedicated to advancing knowledge in autonomous systems and control theory, preparing students for future challenges in these rapidly evolving fields.
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