This paper addresses consensus problems in networks of dynamic agents with fixed and switching topologies, as well as networks with communication time-delays. The authors analyze three scenarios: directed networks with fixed topology, directed networks with switching topology, and undirected networks with fixed topology and communication time-delays. They introduce two consensus protocols and provide a convergence analysis for all three cases. The paper establishes a connection between the algebraic connectivity (or Fiedler eigenvalue) of the network and the performance of the consensus protocol. It also introduces the concept of balanced digraphs, which play a crucial role in solving average-consensus problems. The authors use disagreement functions, which are Lyapunov functions for the disagreement dynamics, to analyze the convergence of the consensus protocols. The paper discusses the communication/sensing cost of protocols and provides analytical tools based on algebraic graph theory, matrix theory, and control theory. Simulations are presented to demonstrate the effectiveness of the theoretical results.This paper addresses consensus problems in networks of dynamic agents with fixed and switching topologies, as well as networks with communication time-delays. The authors analyze three scenarios: directed networks with fixed topology, directed networks with switching topology, and undirected networks with fixed topology and communication time-delays. They introduce two consensus protocols and provide a convergence analysis for all three cases. The paper establishes a connection between the algebraic connectivity (or Fiedler eigenvalue) of the network and the performance of the consensus protocol. It also introduces the concept of balanced digraphs, which play a crucial role in solving average-consensus problems. The authors use disagreement functions, which are Lyapunov functions for the disagreement dynamics, to analyze the convergence of the consensus protocols. The paper discusses the communication/sensing cost of protocols and provides analytical tools based on algebraic graph theory, matrix theory, and control theory. Simulations are presented to demonstrate the effectiveness of the theoretical results.