Networked Control Systems: Laplacian Operators and Microgrids

Related lectures (29)

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Covers the fundamentals of connectivity in graph theory, including paths, cycles, and spanning trees.

Explores the Laplacian matrix, time-varying consensus theorems, and balanced graphs in networked control systems.

Covers the concept of the exponential family and discusses forward and backward maps, expensive computations, parameters, functions, and convexity.

Explores the Laplacian matrix in electric and mechanical networks, consensus, and properties of Laplacian matrices in networked control systems.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Explores the properties of undirected and directed graphs, emphasizing connectivity and network topology modeling.

Explores coordination among agents in networked control systems through graph theory and real-world examples.

Explores the Laplacian matrix and consensus in networked control systems.

Covers sparsest cut, NP-completeness, Bougains Theorem, and concurrent flow in graphs.

Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.