Adaptive consensus protocol for networks of multiple agents with nonlinear dynamics using neural networks

2011 ◽  
Vol 14 (5) ◽  
pp. 1328-1339 ◽  
Author(s):  
Yang Liu ◽  
Yingmin Jia
Keyword(s):  
Nonlinear Dynamics ◽  
Neural Networks ◽  
Multiple Agents ◽  
Consensus Protocol

Nonlinear dynamics and machine learning of recurrent spiking neural networks

2021 ◽  
Author(s):  
Oleg V. Maslennikov ◽  
Mechislav M. Pugavko ◽  
Dmitrii S. Shchapin ◽  
Vladimir I. Nekorkin
Keyword(s):  
Nonlinear Dynamics ◽  
Machine Learning ◽  
Neural Networks ◽  
Spiking Neural Networks

scholarly journals Eigenvalue Based Approach for Global Consensus in Multiagent Systems with Nonlinear Dynamics

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Wei Qian ◽  
Lei Wang
Keyword(s):  
Nonlinear Dynamics ◽  
Multiagent Systems ◽  
Multiagent System ◽  
Symmetric Matrix ◽  
Algebraic Connectivity ◽  
Communication Graph ◽  
Consensus Protocol ◽  
Global Consensus ◽  
The Common ◽  
Analytical Result

This paper addresses the global consensus of nonlinear multiagent systems with asymmetrically coupled identical agents. By employing a Lyapunov function and graph theory, a sufficient condition is presented for the global exponential consensus of the multiagent system. The analytical result shows that, for a weakly connected communication graph, the algebraic connectivity of a redefined symmetric matrix associated with the directed graph is used to evaluate the global consensus of the multiagent system with nonlinear dynamics under the common linear consensus protocol. The presented condition is quite simple and easily verified, which can be effectively used to design consensus protocols of various weighted and directed communications. A numerical simulation is also given to show the effectiveness of the analytical result.

Nonlinear dynamics and machine learning of recurrent spiking neural networks

2021 ◽  
Author(s):  
Oleg V. Maslennikov ◽  
Mechislav M. Pugavko ◽  
Dmitrii S. Shchapin ◽  
Vladimir I. Nekorkin
Keyword(s):  
Nonlinear Dynamics ◽  
Machine Learning ◽  
Neural Networks ◽  
Spiking Neural Networks

Neural-networks-based distributed output regulation of multi-agent systems with nonlinear dynamics

2014 ◽  
Vol 125 ◽  
pp. 81-87 ◽  
Author(s):  
Jia Liu ◽  
Zengqiang Chen ◽  
Xinghui Zhang ◽  
Zhongxin Liu
Keyword(s):  
Nonlinear Dynamics ◽  
Neural Networks ◽  
Output Regulation ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Nonlinear-dynamics theory of up-down transitions in neocortical neural networks

2012 ◽  
Vol 85 (2) ◽  
Author(s):  
Maryam Ghorbani ◽  
Mayank Mehta ◽  
Robijn Bruinsma ◽  
Alex J. Levine
Keyword(s):  
Nonlinear Dynamics ◽  
Neural Networks
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