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This lecture covers distributed algorithms for networked control systems, including topics such as consensus on time-varying communication networks, applications of consensus algorithms, distributed computation of least-squares regression, and time-varying consensus algorithms. The instructor explains the concepts using examples and theoretical explanations, highlighting the importance of robustness to changes in graph topology, lossy communication, transmission delays, and quantization. The lecture also delves into the distributed computation of least-squares regression, explicit formulas for LS estimation, and the distributed computation of BLUE. Various theorems and examples are presented to illustrate the effectiveness and challenges of implementing these algorithms in practical sensor networks.