Quantized Consensus Control for Second-Order Nonlinear Multi-agent Systems with Sliding Mode Iterative Learning Approach

2018 ◽  
Vol 19 (2) ◽  
pp. 518-533 ◽  
Author(s):  
Xiongfeng Deng ◽  
Xiuxia Sun ◽  
Ri Liu
Keyword(s):  
Sliding Mode ◽  
Second Order ◽  
Iterative Learning ◽  
Learning Approach ◽  
Multi Agent Systems ◽  
Consensus Control ◽  
Agent Systems ◽  
Multi Agent ◽  
Quantized Consensus

Adaptive iterative learning consensus control for second-order multi-agent systems with unknown control gains

2020 ◽  
Vol 393 ◽  
pp. 15-26 ◽  
Author(s):  
Guilu Li ◽  
Chang-E Ren ◽  
C.L. Philip Chen ◽  
Zhiping Shi
Keyword(s):  
Second Order ◽  
Iterative Learning ◽  
Multi Agent Systems ◽  
Consensus Control ◽  
Agent Systems ◽  
Multi Agent ◽  
Unknown Control

Iterative learning control for consensus of second-order multi-agent systems with interval uncertain topologies

2021 ◽  
Author(s):  
Liming Wang ◽  
Guoshan Zhang
Keyword(s):  
Iterative Learning Control ◽  
Optimization Problem ◽  
Sliding Mode ◽  
Weight Coefficient ◽  
Second Order ◽  
Iterative Learning ◽  
Multi Agent Systems ◽  
Optimal Weight ◽  
Agent Systems ◽  
Multi Agent

Abstract This paper is devoted to the robust consensus tracking problem of second-order nonlinear multi-agent systems (MASs) with the interval uncertain topologies. For the second-order MASs including one leader agent and multiple follower agents, a control protocol is proposed by combining the iterative learning control scheme with the sliding mode control method. By analyzing the convergence of sliding mode variables, the consensus conditions including the unknown eigenvalues and the undetermined weight coefficient are obtained. In order to deal with the difficulties of weight coefficient design caused by the unknown eigenvalues of graphs, a min-max optimization problem is formulated based on the fastest convergence of the λ-norm of sliding mode variables, then the optimal weight coefficient is obtained by solving the min-max optimization problem. Moreover, for the undirected and directed interval uncertain graphs, two algorithms about the optimal weight coefficients are proposed, respectively. Finally, three numerical simulation examples are presented to demonstrate the effectiveness of the proposed methods.

Quantized consensus control for second-order multi-agent systems with nonlinear dynamics

2016 ◽  
Vol 175 ◽  
pp. 529-537 ◽  
Author(s):  
Chang-E Ren ◽  
Long Chen ◽  
C.L. Philip Chen ◽  
Tao Du
Keyword(s):  
Nonlinear Dynamics ◽  
Second Order ◽  
Multi Agent Systems ◽  
Consensus Control ◽  
Agent Systems ◽  
Multi Agent ◽  
Quantized Consensus
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