Back to Search Start Over

Adaptive Swarm Control Within Saturated Input Based on Nonlinear Coupling Degree.

Authors :
Yu, Dengxiu
Long, Jia
Chen, C. L. Philip
Wang, Zhen
Source :
IEEE Transactions on Systems, Man & Cybernetics. Systems; Aug2022, Vol. 52 Issue 8, p4900-4911, 12p
Publication Year :
2022

Abstract

In this article, an adaptive swarm control within saturated input based on the nonlinear coupling degree is proposed. Swarm control is a forward study in kinematics and dynamics of the swarm system. However, the coupling degree in the previous work can only manifest whether the agents in the swarm being connected or not, ignoring the connection strength. As a result, the nonlinear coupling degree is proposed, which is more suitable for practical engineering than the previous coupling degree. Based on the nonlinear coupling degree, we put forward novel swarm kinematics and dynamics. Besides, the effects of input saturation and nonlinear dynamics should be considered for this novel swarm control based on the nonlinear coupling degree. Therefore, we introduce the backstepping method to design an adaptive swarm controller. With this controller, the input saturation auxiliary system is designed to reduce the effects of input saturation, and a radial basis function neural network (RBF-NN) is introduced to approximate the nonlinear dynamics. To overcome the differential explosion in the backstepping method, a command filter is put forward to reduce the amount of calculation and reduces the difficulty of the controller design. It is proved that the proposed controller ensures stability based on the Lyapunov stability theory. Finally, the simulation results of a multiagent system composed of six omnidirectional mobile robots illustrate the validity of the proposed controller. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21682216
Volume :
52
Issue :
8
Database :
Complementary Index
Journal :
IEEE Transactions on Systems, Man & Cybernetics. Systems
Publication Type :
Academic Journal
Accession number :
158186096
Full Text :
https://doi.org/10.1109/TSMC.2021.3102587