Robust Dynamic Average Consensus Algorithms

George, Jemin; Freeman, Randy A.

doi:10.1109/tac.2019.2901819

Cited by 60 publications

(37 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where p < 1; (ii) select by (16); and (iii) update the parameters h ij (t) by (12) and w ij (t) by (13) for all i ∼ j. Then, if there exists k such that τ k (t) > ∆ τ > τ i (t) > 0 for all t ≥ t 0 = 0 and for all i = 1, • • • , N ls with i = k, the decision variable x k (t) asymptotically converges to the positive limit set:…”

Section: Resultsmentioning

confidence: 99%

“…In [15], a filter-based algorithm with state-dependent gains has enabled dynamic average tracking control of nonlinear second-order multi-agent systems. In [16], a robust approach has guaranteed arbitrarily small steady-state error of dynamic average consensus for directed networks. In [17], an integral-based dynamic consensus technique has robustly filtered the average of only nonzero sensor measurements.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Winner-Take-All Teleoperation of A Multi-Robot System

Yuan

Constantinescu

Shi

2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

In a distributed multi-master-multi-slave teleoperation system, the human users may compete against each other for the control of the team of slave robots. To win the competition, one operator would send the largest command to the slave group. For the sake of team cohesion, the slave group should follow the command of the winning operator and ignore the commands of the other users. To enable (i) the slave team to identify the winning operator, and (ii) each slave to determine whether to admit or discard the command it receives from its operator, this paper proposes a dynamic decision-making protocol that distinguishes the decision variable of the slave commanded by the winner from the decision variables of all other slave robots. The protocol only requires the slaves to exchange and evaluate their decision variables locally. Lyapunov stability analysis proves the theoretical convergence of the proposed decision-making algorithm. An experimental distributed winner-take-all teleoperation in a 3-masters-11-slaves teleoperation testbed validates its practical efficacy.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Winner-Take-All Teleoperation of A Multi-Robot System

Yuan

Constantinescu

Shi

2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

show abstract

“…Then, we prove that r i (t) −ξ(t) converges to 0 in a finite time. The proof of this step can be found in [27].…”

Section: Stability Analysismentioning

confidence: 99%

“…Considering the estimated positionξ i k (t), the following multi-targets geometric center estimator which is motivated by George and Freeman [27] is designed to collaboratively estimate the geometric center ξ * (t).…”

Section: Formation Circumnavigationmentioning

confidence: 99%

See 1 more Smart Citation

Bearing-Only-Based Formation Circumnavigation Guided by Multiple Unknown Targets

Chun

2020

IEEE Access

View full text Add to dashboard Cite

A distributed event‐triggered dynamic average consensus scheme with a time‐varying threshold and its application in DC microgrid

Yang

Wang

Chang

et al. 2023

Asian Journal of Control

View full text Add to dashboard Cite

We propose a distributed event‐triggered dynamic average consensus (DAC) scheme with a time‐varying threshold for a multi‐agent system (MAS) in a directed graph. In this scheme, each agent is not required to monitor its neighbors in real time, and a threshold is chosen related to consensus performance directly in an MAS, where the threshold is adjusted adaptively according to average consensus performance. Also, we introduce a bounded and monotonically increasing function in a time‐varying threshold, and this function is for guaranteeing the value of a threshold to locate in an appropriate range. Stability analysis shows that the tracking error is eventually bounded and the MAS achieves DAC without Zeno behaviors. Furthermore, the proposed event‐triggered DAC scheme is applied to voltage restoration and adjustable current sharing in DC microgrid. The effectiveness of the proposed scheme is verified by two examples.

show abstract

Robust Dynamic Average Consensus Algorithms

Cited by 60 publications

References 27 publications

Distributed Winner-Take-All Teleoperation of A Multi-Robot System

Distributed Winner-Take-All Teleoperation of A Multi-Robot System

Bearing-Only-Based Formation Circumnavigation Guided by Multiple Unknown Targets

A distributed event‐triggered dynamic average consensus scheme with a time‐varying threshold and its application in DC microgrid

Contact Info

Product

Resources

About