Lectures related to Networked Control Systems

Networked Control Systems: Laplacian Matrix and Consensus

Explores the Laplacian matrix and consensus in networked control systems.

Networked Control Systems: Laplacian Flow and Heat Equation

Explores Laplacian flow, heat equation analogies, and microgrid networked controllers.

Networked Control Systems: Consensus and Laplacian Flow

Explores the Laplacian flow and achieving consensus in networked control systems through examples and theorems.

Distributed Computation: Consensus Algorithms in Networked Control Systems

Explores consensus algorithms in networked control systems, covering topics like Metropolis-Hasting models and distributed computation of Least-Squares regression.

Time-Varying Consensus Algorithms

Explores time-varying consensus algorithms in networked control systems and the Laplacian matrix's role in achieving average consensus.

Networked Control Systems: Convergence Rate and Digraphs

Explores convergence rate in networked control systems and consensus in digraphs, emphasizing the challenges of computing Pess(A) and weight assignment.

Networked Control Systems: Properties and Connectivity

Explores properties of matrices, irreducibility, and graph connectivity in networked control systems.

Consensus in Networked Control Systems

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

Networked Control Systems: Laplacian Matrix and Graph Association

Explores Laplacian matrices of graphs, graph-digraph association, and physical system examples.

Networked Control Systems: Strongly Connected Components and Condensation Digraphs

Explores strongly connected components and condensation digraphs in networked control systems, demonstrating their practical implications.

Networked Control Systems: Laplacian Operators and Microgrids

Explores Laplacian operators on graphs and the model of DC microgrids.

Consensus with GR Nodes

Explores consensus with GR nodes in networked control systems, focusing on condensation digraphs and the main result.

Laplacian Matrix in Networked Control Systems

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

Irreducible Matrices and Strong Connectivity

Explores irreducible matrices and strong connectivity in networked control systems, emphasizing the importance of adjacency matrices and graph structures.

Graphical Models: Representing Probabilistic Distributions

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Consensus Theorem for Communication Networks

Explores the consensus theorem for communication networks and the implications of various consensus properties in networked control systems.

Primitive Matrices and Spectral Properties in Networked Control Systems

Explores primitive matrices, dominant eigenvalues, and spectral properties in networked control systems.

Expander Graphs: Properties and Eigenvalues Log in to Mediaspace to watch this video

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

Notion of Transfer Function Log in to Mediaspace to watch this video

Introduces the concept of transfer function in dynamic systems analysis.

Graph Algorithms: Basics Log in to Mediaspace to watch this video

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.