Continuum Deformation of Multi-Agent Systems Under Directed Communication Topologies

Author(s):  
Hossein Rastgoftar ◽  
Ella M. Atkins

A leader follower model has recently been proposed for homogeneous deformation of a multi-agent system (MAS) in ℝn. Researchers have shown how a desired homogeneous transformation can be designed by choosing proper trajectories for n + 1 leader agents and can be learned by every follower through local communication. However, existing work requires every follower to communicate with n + 1 adjacent agents, where communication between every two adjacent followers is constrained to be bidirectional. These requirements limit the total allowable number of agents, so an arbitrary number of agents may not be able to acquire a desired homogeneous mapping by local interaction. Additionally, if followers are not allowed to communicate with more than n + 1 neighboring agents, the convergence rate of actual positions to the desired positions (defined by a homogeneous transformation) may not be sufficiently high. The system may then considerably deviate from the desired configuration during transition. The main contribution of this article is to address these two issues, where each follower is considered to be a general linear system. It will be proven that followers can acquire desired positions prescribed by a homogeneous mapping in the presence of disturbance and measurement noise by applying a new finite-time reachability model under either fixed or switching topologies, if: (i) communication among followers is defined by a directed and strongly connected subgraph, (ii) each follower applies a consensus protocol with communication weights that are consistent with the positions of the agents in the initial configuration, and (iii) every follower i is allowed to communicate with mi≥n+1 local agents. With this strategy, an MAS with an arbitrary number of agents with linear dynamics can acquire a desired homogeneous mapping in the presence of disturbance and measurement noise, where convergence rate can be enhanced by increasing the number of communication links.

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Cui-Qin Ma ◽  
Yun-Bo Zhao ◽  
Wei-Guo Sun

Event-triggered bipartite consensus of single-integrator multi-agent systems is investigated in the presence of measurement noise. A time-varying gain function is proposed in the event-triggered bipartite consensus protocol to reduce the negative effects of the noise corrupted information processed by the agents. Using the state transition matrix, Ito^ formula, and the algebraic graph theory, necessary and sufficient conditions are given for the proposed protocol to yield mean square bipartite consensus. We find that the weakest communication requirement to ensure the mean square bipartite consensus under event-triggered protocol is that the signed digraph is structurally balanced and contains a spanning tree. Numerical examples validated the theoretical findings where the system shows no Zeno behavior.


Author(s):  
Ke-cai Cao ◽  
Yun Chai ◽  
Chenglin Liu

AbstractConsensus problem with faster convergence rate of consensus problem has been considered in this paper. Adding more edges such as that connecting each agent and its second-nearest neighbor or changing the consensus protocol such as mixing asymptotic terms and terms of finite-time has been proved to be possible ways in increasing the convergence rate of multi-agent system in this paper. Based on analysis of Laplacian matrix, increasing of the convergence rate has been proved using the second-smallest eigenvalue for the first method. Concerning the second method, advantages of asymptotic consensus protocol and finite-time consensus protocol have been mixed together with the help of homogeneity function and theory of Lyapunov. Simulation results using matlab are also presented to illustrate the newly designed consensus protocols in increasing the convergence rate.


2021 ◽  
pp. 107754632110340
Author(s):  
Jia Wu ◽  
Ning Liu ◽  
Wenyan Tang

This study investigates the tracking consensus problem for a class of unknown nonlinear multi-agent systems A novel data-driven protocol for this problem is proposed by using the model-free adaptive control method To obtain faster convergence speed, one-step-ahead desired signal is introduced to construct the novel protocol Here, switching communication topology is considered, which is not required to be strongly connected all the time Through rigorous analysis, sufficient conditions are given to guarantee that the tracking errors of all agents are convergent under the novel protocol Examples are given to validate the effectiveness of results derived in this article


2019 ◽  
Vol 13 (6) ◽  
pp. 755-762 ◽  
Author(s):  
Xiurong Chen ◽  
Juan Li ◽  
Ziku Wu ◽  
Jiashang Yu

Author(s):  
Yangzhou Chen ◽  
Guangyue Xu ◽  
Jingyuan Zhan

This paper studies the leader-following state consensus problem for heterogeneous linear multi-agent systems under fixed directed communication topologies. First, we propose a consensus protocol consisting of four parts for high-order multi-agent systems, in which different agents are allowed to have different gain matrices so as to increase the degree of design freedom. Then, we adopt a state linear transformation, which is constructed based on the incidence matrix of a directed spanning tree of the communication topology, to equivalently transform the state consensus problem into a partial variable stability problem. Meanwhile, the results of the partial variable stability theory are used to derive a sufficient and necessary consensus criterion, expressed as the Hurwitz stability of a real matrix. Then, this criterion is further expressed as a bilinear matrix inequality condition, and, based on this condition, an iterative algorithm is proposed to find the gain matrices of the protocol. Finally, numerical examples are provided to verify the effectiveness of the proposed protocol design method.


2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Haiying Ma ◽  
Xiao Jia ◽  
Ning Cai ◽  
Jianxiang Xi

In this paper, adaptive guaranteed-performance consensus control problems for multiagent systems with an adjustable convergence speed are investigated. A novel adaptive guaranteed-performance consensus protocol is proposed, where the communication weights can be adaptively regulated. By the state space decomposition method and the stability theory, sufficient conditions for guaranteed-performance consensus are obtained and the guaranteed-performance cost is determined. Moreover, the lower bound of the convergence coefficient for multiagent systems is deduced, which is linearly adjustable approximately by changing the adaptive control gain. Finally, simulation examples are introduced to demonstrate theoretical results.


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