Event‐Triggered Communication and Control for Multi‐Agent Average Consensus

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

2017

This paper investigates coordination problems over packet-based communication channels. We consider the scenario in which the communication between network nodes is corrupted by unknown-but-bounded noise. We introduce a novel coordination scheme, which ensures practical consensus in the noiseless case, while preserving bounds on the nodes disagreement in the noisy case. The proposed scheme does not require any global information about the network parameters and/or the operating environment (the noise characteristics). Moreover, network nodes can sample at independent rates and in an aperiodic manner. The analysis is substantiated by extensive numerical simulations.

Section: Summary Of Contributionsmentioning

confidence: 99%

Self-triggered network coordination over noisy communication channels

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

2017

“…At each update time, the node polls its neighbors, collects the data, and determines whether it is necessary to modify its controls along with its next update time. Similar to event-triggered control [16], [17], self-triggered control [18]- [21] features the remarkable property that the communication among nodes occurs only at discrete time instants. Moreover, the nodes can sample independently and aperiodically.…”

Section: Introductionmentioning

confidence: 99%

Self-Triggered Network Coordination Over Noisy Communication Channels

IEEE Trans. Automat. Contr.

2020

This paper deals with the coordination problems over noisy communication channels. We consider a scenario where the communication between network nodes is corrupted by unknownbut-bounded noise. We introduce a novel coordination scheme which ensures: 1) boundedness of the state trajectories and 2) a linear map from the noise to the nodes disagreement value. The proposed scheme does not require any global information on the network parameters and/or the operating environment (the noise characteristics). Moreover, network nodes can sample at independent rates and in an aperiodic manner.

“…The second direction has methodically exploited the graph structure underlying large-scale systems to design distributed control laws that uses information available only locally, while achieving a global coordination task, such as consensus or synchronization [4][5][6]. The third research direction has investigated the combined problem, in which each local controller collects information from its neighbours and schedules new control values in an event-based fashion [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

On the benefits of saturating information in consensus networks with noise

Systems & Control Letters

2020

In a consensus network subject to non-zero mean noise, the system state may be driven away even when the disagreement exhibits a bounded response. This is unfavourable in applications since the nodes may not work properly and even be faulty outside their operating region. In this paper, we propose a new control algorithm to mitigate this issue by assigning each node a favourite interval that characterizes the nodes desired convergence region. The algorithm is implemented in a self-triggered fashion. If the nodes do not share a global clock, the network operates in a fully asynchronous mode. By this algorithm, we show that the state evolution is confined around the favourite interval and the node disagreement is bounded by a simple linear function of the noise magnitude, without requiring any priori information on the noise. We also show that if the nodes share some global information, then the algorithm can be adjusted to make the nodes evolve into the favourite interval, improve on the disagreement bound and achieve asymptotic consensus in the noiseless case.