Networked Control Systems: Challenges and Opportunities

Related lectures (30)

Page 2 of 3

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

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

Covers graphical models for probability distributions and factor graphs representation.

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.

Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.

Explores the design of graph weights for consensus and applications in sensor networks.

Explores consensus in networked control systems through graph weight design and matrix properties.

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.