PILGRIM, RYAN ZACHARY. Source Coding Optimization for Distributed Average Consensus. (Under the direction of Dror Baron.) Consensus is a common method for computing a function of the data distributed among the nodes of a network. Of particular interest is distributed average consensus, whereby the nodes iteratively compute the sample average of the data stored at all the nodes of the network us...

The interrelationship between control and communication theory is becoming of fundamental importance in many distributed control systems, such as the coordination of a team of autonomous agents. In such a problem, communication constraints impose limits on the achievable control performance. We consider as instance of coordination the consensus problem. The aim of the paper is to characterize t...

The research field of networked systems has burgeoned during the last years attracting the attention of outstanding mathematicians, computer scientists and electrical engineers. This is due in no small part to the recent technological advances in communication and computation and to the miniaturization of electronic components which have made large groups of embedded systems, such as sensors an...

We consider how iterative strategies for asymptotic average consensus in directed graphs (digraphs) can be adapted so that the nodes can determine, in a distributed fashion, a stopping criterion that allows them to terminate the execution of the iteration when approximate average consensus has been reached. The nodes are said to have reached approximate average consensus when each of them has a...

We study the average consensus problem of multi-agent systems for general network topologies with unidirectional information flow. We propose two (linear) distributed algorithms, deterministic and gossip, respectively for the cases where the inter-agent communication is synchronous and asynchronous. Our contribution is that in both cases, the developed algorithms guarantee state averaging on ar...

This paper proposes two continuous-time dynamic average consensus filters for networks described by balanced and weakly-connected directed topologies. Our distributed filters, termed 1st-Order-Input (FOI-DCF ) and 2nd-OrderInput Dynamic (SOI-DCF ) Consensus Filters, respectively, allow agents to track the average of their dynamic inputs within an O(ǫ)-neighborhood. The convergence results and s...

In this note we give sufficient conditions for the convergence of the iterative algorithm called weighted-average consensus in directed graphs. We study the discrete-time form of this algorithm. We use standard techniques from matrix theory to prove the main result. As a particular case one can obtain well-known results for non-weighted average consensus. We also give a corollary for undirected...

We consider continuous-time average consensus dynamics in which the agents’ states are communicated through uniform quantizers. Solutions to the resulting system are defined in the Krasowskii sense and are proven to converge to conditions of “practical consensus”. To cope with undesired chattering phenomena we introduce a hysteretic quantizer, and we study the convergence properties of the resu...

This paper is motivated by the lack of distributed algorithm implementations on wireless sensor networks (WSN) in hardware. We deal exemplary with the implementation of the well-known average consensus algorithm. By formulating the algorithm into nesC, a C derivative, it is possible to enrich the knowledge of the algorithm with practical information, specific to embedded devices such as nodes. ...