Event-Triggered Adaptive Bipartite Containment Control for Stochastic Multiagent Systems

2021 ◽  
pp. 1-10
Author(s):  
Yanhui Zhang ◽  
Jian Sun ◽  
Hongyi Li ◽  
Wei He
Keyword(s):  
Multiagent Systems ◽  
Containment Control ◽  
Event Triggered

$\mathcal{H}_{\infty}$ Containment Control of Multiagent Systems Under Event-Triggered Communication Scheduling: The Finite-Horizon Case

2020 ◽  
Vol 50 (4) ◽  
pp. 1372-1382 ◽  
Author(s):  
Wei Chen ◽  
Derui Ding ◽  
Xiaohua Ge ◽  
Qing-Long Han ◽  
Guoliang Wei
Keyword(s):  
Multiagent Systems ◽  
Finite Horizon ◽  
Containment Control ◽  
Communication Scheduling ◽  
Horizon Case ◽  
Event Triggered

Containment Control of Linear Multiagent Systems With Stochastic Disturbances via Event-Triggered Strategies

2020 ◽  
Vol 14 (4) ◽  
pp. 4810-4819 ◽  
Author(s):  
Wencheng Zou ◽  
Yueying Huang ◽  
Choon Ki Ahn ◽  
Zhengrong Xiang
Keyword(s):  
Multiagent Systems ◽  
Stochastic Disturbances ◽  
Containment Control ◽  
Event Triggered

scholarly journals Fully Distributed Event-Triggered Containment Control of Uncertain Multiagent Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Zhaodong Liu ◽  
Zhi Liu ◽  
Xuewu Qian ◽  
Ancai Zhang ◽  
Zhenxing Li
Keyword(s):  
Control Problem ◽  
Multiagent Systems ◽  
Containment Control ◽  
Numerical Example ◽  
Uncertain Dynamics ◽  
Relative Information ◽  
Global Topology ◽  
Zeno Behavior ◽  
Topology Information ◽  
Event Triggered

This paper investigates the event-triggered containment control problem of a class of uncertain nonlinear multiagent systems (MASs). By employing the local relative information, we design an adaptive event-triggered containment algorithm. The proposed containment algorithm can cope with the unavailability of global topology information and uncertain dynamics of follower agents. Therefore, the presented containment algorithm is free of global topology information, i.e., the designed algorithm is fully distributed. In addition, it is proved that Zeno behavior will not occur. At last, a numerical example is given to verify our event-triggered containment algorithm.

scholarly journals Observer-Based Event-triggered Adaptive Containment Control for Multiagent Systems With Prescribed performance

2021 ◽  
Author(s):  
Rui Xu ◽  
Xin Wang ◽  
Yuhao Zhou
Keyword(s):  
Multiagent Systems ◽  
Nonlinear Function ◽  
Dynamic Surface Control ◽  
The Novel ◽  
Containment Control ◽  
Dynamic Surface ◽  
Prescribed Performance ◽  
The Neural Network ◽  
Control Resource ◽  
Event Triggered

Abstract This paper focuses on the problem of the observer-based event-triggered adaptive containment control for a class of nonlinear multiagent systems (MASs) with prescribed performance. First, the radial basis function neural networks (RBFNNs) are adopted to approximate the uncertain smooth nonlinear function, and the neural network-based state observer is designed to estimate the unmeasurable state. Besides, to reduce the control resource assumption and get a better balance between the system performance and network constraints, the switching threshold based event-triggered control strategy is introduced. Based on this, the novel distributed containment controller is designed by utilizing the adaptive backstepping technique and the dynamic surface control (DSC) technique to guarantee that the output of each follower converges to the convex hull formed by multileader. Moreover, the containment errors can be converged to the prescribed boundary and all signals in closed-loop system are semi-global uniformly ultimately bounded (SGUUB) as well. Finally, the simulation example is carried out to illustrate the efficiency of the proposed controller.

Leader-Following Consensus for a Class of Nonlinear Multiagent Systems Under Event-Triggered and Edge-Event Triggered Mechanisms

2020 ◽  
pp. 1-12
Author(s):  
Huaguang Zhang ◽  
Juan Zhang ◽  
Yuliang Cai ◽  
Shaoxin Sun ◽  
Jiayue Sun
Keyword(s):  
Multiagent Systems ◽  
Leader Following ◽  
Event Triggered

Output-Based Event-Triggered Cooperative Robust Regulation for Constrained Heterogeneous Multiagent Systems

2020 ◽  
pp. 1-12
Author(s):  
Peng Wang ◽  
Shuzhi Sam Ge ◽  
Xiaobing Zhang ◽  
Di Yu
Keyword(s):  
Multiagent Systems ◽  
Robust Regulation ◽  
Event Triggered
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