Consensus of Multi-Agent Systems With General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols

By Zhongkui Li, Wei Ren, Xiangdong Liu, M. Fu. IEEE Transactions on Automatic Control, 2011

764 citations recorded by the source corpus.

This technical brief considers the distributed consensus problems for multi-agent systems with general linear and Lipschitz nonlinear dynamics. Distributed relative-state consensus protocols with an adaptive law for adjusting the coupling weights between neighboring agents are designed for both the linear and nonlinear cases, under which consensus is reached for all undirected connected communication graphs. Extensions to the case with a leader-follower communication graph are further studied. In contrast to the existing results in the literature, the adaptive consensus protocols here can be implemented by each agent in a fully distributed fashion without using any global information.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2590f90b0245059e828b9c2598625720e559bed9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Zhongkui Li
2. Frank L. Lewis
3. Z. Duan
4. Qing-Long Han
5. Guanghui Wen
6. Wei Ren
7. Xiangdong Liu
8. Lihua Xie

In Electrical and Electronic Engineering

1. Frank L. Lewis
2. Zhongkui Li
3. Xiaohua Ge
4. Kristian Hengster-Movrić
5. Z. Duan
6. Xiangdong Liu
7. Wei Ren
8. Guanghui Wen

Citations in the corpus

• Adaptive Consensus of Multi-Agent Systems With Unknown Identical Control Directions Based on A Novel Nussbaum-Type Function (2014, background): “Moreover, in [12] and [13], an adaptive idea is”
• Designing Fully Distributed Consensus Protocols for Linear Multi-Agent Systems With Directed Graphs (2013, methodology): “Compared to the distributed adaptive protocols in [12], [13] for undirecte d graphs, a distinct feature of the adaptive protocol in this technical note is that monotonically incre asing functions, inspired by the changing supply function notion in [16], are introduced to provide ex tra freedom for d”
• Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism (2017, background): “For MAS (1), the communication topology modeled by G is assumed to satisfy the following assumption, which is common in addressing cooperative behaviors of MASs, see, e.g., [29], [30], [32], and [33].”
• Cooperative Optimal Control for Multi-Agent Systems on Directed Graph Topologies (2014, methodology): “Methods for computing the coupling gain using adaptive control techniques were given in [19].”
• Distributed robust consensus control of multi-agent systems with heterogeneous matching uncertainties (2013, background): “In the previous related works [9,10,29,20,19,11,22,23], the agents are identical linear systems and free of uncertainties.”
• Distributed consensus of linear multi-agent systems with adaptive dynamic protocols (2011, positive): “convergence of di and ˜vi, i = 1,··· ,N, can be shown by following similar steps in the proof of Theorem 1, which is omitted here for brevity. Remark 2. Different from the previous adaptive schemes in [21, 22, 23], which are based on the relative state information, the proposed adaptive protocols (2)”