Consentability and protocol design of multi-agent systems with stochastic switching topology

Zhang, Ya; Tian, Yu‐Ping

doi:10.1016/j.automatica.2008.11.005

Cited by 326 publications

(181 citation statements)

References 17 publications

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“…[10][11][12] In applications, whether the information exchanges or not between agents is also stochastic, the Markovian switching model was used to deal with this situation. Zhang and Tian 13 proved that the switching systems can realize mean-square consensus when the union of graphs has a globally reachable node. In Matei and John, 14 the consensus in almost sure sense can be achieved if and only if the union of graphs is strongly connected for both continuous-time and discrete-time systems.…”

Section: Introductionmentioning

confidence: 99%

Mean-square consensus of discrete-time multi-agent systems with Markovian switching topologies and persistent disturbances

Wang

Pan

et al. 2017

International Journal of Distributed Sensor Networks

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This article deals with the leader-following mean-square consensus problem of discrete-time general linear multi-agent systems with Markovian switching topologies and persistent disturbances. Assume that the communication topology is not connected at any time but the union topology is connected. First, the estimators are designed to calculate the states of agents when external disturbance not exists. Based on the error information between the truth-values and estimatedvalues of states, the compensators are proposed to subject to the effect of persistent disturbances. And then, a new mean-square consensus control protocol is proposed for each agent. Second, by using the property of permutation matrix, the original closed-loop system is transferred into an equivalent system. Third, sufficient conditions for meansquare consensus are obtained in the form of matrix inequalities. Finally, numerical simulations are given to illustrate the effectiveness of the theoretical results.

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Section: Introductionmentioning

confidence: 99%

Mean-square consensus of discrete-time multi-agent systems with Markovian switching topologies and persistent disturbances

Wang

Pan

et al. 2017

International Journal of Distributed Sensor Networks

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“…Some network topology structures for consensus are investigated, in which the topology is time-varying or stochastic. [7][8][9][10][11] On the other hand, convergence speed is also an important problem, which determines how fast consensus can be achieved. The maximum convergence speed has been conducted by designing weights associated with the edges of topology graph.…”

Section: Introductionmentioning

confidence: 99%

“…10,11,21 Most of the above researches consider switching communication topologies. However, the energy limitation is not concerned in these researches.…”

Section: Introductionmentioning

confidence: 99%

Guaranteed convergence control for consensus of mobile sensor networks with dynamical topologies

Cheng

Dong

et al. 2016

International Journal of Distributed Sensor Networks

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Mobile sensors need to reach consensus in many applications such as unmanned vehicles, multi-agent systems and environmental monitoring. In these scenarios, it is very important to reduce the power consumption as well as make sensors reach consensus as fast as possible. In this article, we propose a novel guaranteed convergence control algorithm to switch topologies of mobile sensors so that we can reduce power consumption in the sensor network and make the mobile sensors reach consensus with guaranteed convergence as well. The topology graphs over the mobile sensors are unconnected, directed, dynamical and switched periodically at any moment, while the joint graphs of dynamical topologies are connected in a bounded time period. The guaranteed convergence rate of consensus is derived on a method based on the variable decomposition. Some illustrative examples are provided to demonstrate the validity and effectiveness of the results.

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“…These stochastic switchings are often modeled by Bernoulli process [10] or Markov processes [11], then the problem of stochastic consensus is investigated. Stochastic consensus includes the following two classes: mean square (MS) and almost sure (AS).…”

Section: Introductionmentioning

confidence: 99%

Almost sure consensus for multi-agent systems with two level switching

Song¹,

Yang

et al. 2016

Information Sciences

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In most literatures on the consensus of multi-agent system (MAS), the agents considered are time-invariant. However in many cases (e.g. aerocrafts), the dynamics of agents have the characteristic of switching. Moreover, such switching in agent might be accompanied with the change of the interconnection topology of this MAS. This paper proposes a new model of two level switching structure to describe this type of MAS. The switching in the low level, which represents the variation of the agent dynamics, is deterministic and controllable. The switching in the upper level, which reflects the random change of the topology, fits for a Markov chain. Besides, the transition probability of the Markov chain in the upper level varies accordingly with the low level switching. This paper deals with the almost sure (AS) consensus for the MAS with two level switching. By analyzing the transient features of discrete-time Markov chain and based on the method of dwell time, a sufficient condition of AS consensus is proposed.

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Consentability and protocol design of multi-agent systems with stochastic switching topology

Cited by 326 publications

References 17 publications

Mean-square consensus of discrete-time multi-agent systems with Markovian switching topologies and persistent disturbances

Mean-square consensus of discrete-time multi-agent systems with Markovian switching topologies and persistent disturbances

Guaranteed convergence control for consensus of mobile sensor networks with dynamical topologies

Almost sure consensus for multi-agent systems with two level switching

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