scholarly journals Adaptive Leader-Following Consensus of Multi-Agent Systems with Unknown Nonlinear Dynamics

Entropy ◽  
2014 ◽  
Vol 16 (9) ◽  
pp. 5020-5031 ◽  
Author(s):  
Junwei Wang ◽  
Kairui Chen ◽  
Qinghua Ma
Keyword(s):  
Nonlinear Dynamics ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Leader Following ◽  
Multi Agent ◽  
Unknown Nonlinear Dynamics

Adaptive Coordination Control of Multi-Agent Systems with Switching Topologies and Unknown Nonlinear Dynamics

2013 ◽  
Vol 278-280 ◽  
pp. 1413-1416
Author(s):  
Gao Yang Liu ◽  
Hui Yu ◽  
Yi Zhang
Keyword(s):  
Nonlinear Dynamics ◽  
Stability Analysis ◽  
Convergence Analysis ◽  
Lyapunov Theory ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Leader Following ◽  
Multi Agent ◽  
Unknown Nonlinear Dynamics

In this paper, we study the leader-following adaptive consensus problem for multi-agent systems with unknown nonlinear dynamics. The topologies of the networks are switching. A novel adaptive consensus algorithm is proposed by using linear parameterizations of unknown nonlinear dynamics of all agents. By stability analysis and parameter convergence analysis of the proposed algorithm, adaptive consensus can be realized based on neighboring graphs. The stability analysis is based on algebraic graph theory and Lyapunov theory, the PE condition plays a key role in parameter convergence analysis. Example is given to validate the theoretical results.

Active disturbance rejection consensus control of uncertain high-order nonlinear multi-agent systems

2019 ◽  
Vol 42 (3) ◽  
pp. 604-617
Author(s):  
Maopeng Ran ◽  
Qing Wang ◽  
Chaoyang Dong
Keyword(s):  
Nonlinear Dynamics ◽  
Control Method ◽  
High Order ◽  
Multi Agent Systems ◽  
Extended State ◽  
Consensus Control ◽  
Total Uncertainty ◽  
Agent Systems ◽  
Multi Agent ◽  
Unknown Nonlinear Dynamics

In this paper, we consider the consensus control problem for uncertain high-order nonlinear multi-agent systems in a leader-follower scheme. Each follower node is modeled by a high-order integrator incorporating with unmeasurable states and unknown nonlinear dynamics. First, the total uncertainty that lumps the unknown nonlinear dynamics and the mismatch of control is viewed as an extended state of the agent. By using local information from neighborhood set, a distributed extended state observer (ESO) is designed to estimate not only the unmeasurable agent states but also its total uncertainty. Then, based on the output of the ESO, a novel consensus control law is proposed, in which the total uncertainty is canceled out in the feedback loop in real time. We show that, with the application of the proposed approach, the ESO estimation errors and the disagreement error vectors between the leader and the followers can be made arbitrarily small. A simulation example is given to illustrate the effectiveness of the proposed consensus control method.

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