ResearchOur group develops scalable control design and verification methods for applications where the system size and complexity are beyond the reach of traditional methods. We particularly address systems with many interconnected components, nonlinear dynamics, and learning and decision making capabilities. Our broad approach is to obtain system-level guarantees from appropriate abstractions of the components with compositional, hierarchical and learning-based procedures, and to exploit structural system properties for scalability. We uncover such properties in applications and generalize them to broader classes of systems. Current research topics include control of autonomous systems, networks and multi-agent systems. Please follow the link to Research Areas on the left for further descriptions of these topics. Course Materials
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