Formation control of mobile agents with second-order nonlinear dynamics in unknown environments containing obstacles

2016 ◽  
Author(s):  
Jie Huang ◽  
Ming Cao ◽  
Ning Zhou ◽  
Yan Li
Keyword(s):  
Nonlinear Dynamics ◽  
Mobile Agents ◽  
Formation Control ◽  
Second Order ◽  
Unknown Environments

Adaptive second-order consensus of networked mobile agents with nonlinear dynamics

Automatica ◽  
2011 ◽  
Vol 47 (2) ◽  
pp. 368-375 ◽  
Author(s):  
Housheng Su ◽  
Guanrong Chen ◽  
Xiaofan Wang ◽  
Zongli Lin
Keyword(s):  
Nonlinear Dynamics ◽  
Mobile Agents ◽  
Second Order

Control of Multiple Mobile Agents Via Artificial Potential Functions and Random Motion

2007 ◽  
Author(s):  
Manish Kumar ◽  
Devendra P. Garg ◽  
Randy Zachery
Keyword(s):  
Potential Function ◽  
Mobile Agents ◽  
Formation Control ◽  
Cluster Formation ◽  
Limited Range ◽  
Random Motion ◽  
Potential Functions ◽  
Random Behavior ◽  
Artificial Potential Function ◽  
Multiple Mobile Agents

This paper investigates the effectiveness of designed random behavior in cooperative formation control of multiple mobile agents. A method based on artificial potential functions provides a framework for decentralized control of their formation. However, it implies heavy communication costs. The communication requirement can be replaced by onboard sensors. The onboard sensors have limited range and provide only local information, and may result in the formation of isolated clusters. This paper proposes to introduce a component representing random motion in the artificial potential function formulation of the formation control problem. The introduction of the random behavior component results in a better chance of global cluster formation. The paper uses an agent model that includes both position and orientation, and formulates the dynamic equations to incorporate that model in artificial potential function approach. The effectiveness of the proposed method is verified via extensive simulations performed on a group of mobile agents and leaders.

scholarly journals Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xuejing Lan ◽  
Zhenghao Wu ◽  
Wenbiao Xu ◽  
Guiyun Liu
Keyword(s):  
Neural Network ◽  
Nonlinear Dynamics ◽  
Shape Control ◽  
Formation Control ◽  
Adaptive Neural Network ◽  
Multirobot System ◽  
Control Scheme ◽  
Narrow Space ◽  
The Stability ◽  
Unknown Nonlinear Dynamics

This paper considers the region-based formation control for a swarm of robots with unknown nonlinear dynamics and disturbances. An adaptive neural network is designed to approximate the unknown nonlinear dynamics, and the desired formation shape is achieved by designing appropriate potential functions. Moreover, the collision avoidance, velocity consensus, and region tracking are all considered in the controller. The stability of the multirobot system has been demonstrated based on the Lyapunov theorem. Finally, three numerical simulations show the effectiveness of the proposed formation control scheme to deal with the narrow space, loss of robots, and formation merging problems.

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