Multi-Group Formation Tracking Control for Second-Order Nonlinear Multi-Agent Systems Using Adaptive Neural Networks

Abstract

This paper investigates the multi-group formation tracking (MGFT) control problem for second-order nonlinear multi-agent systems (MASs) with unknown dynamics. The objective of the MGFT control is to divide all agents into several subgroups to form different desired sub-formations while following their respective leaders. Firstly, the neural network (NN) approximator is constructed to solve the problem of unknown dynamics. Then, the distributed adaptive control protocol is designed based on the NN approximator. According to the Lyapunov stability theory and algebraic graph theory, sufficient criteria are obtained to realize the MGFT control. The semi-globally uniformly ultimately boundedness of formation errors is proved in detail. Finally, a numerical simulation example is given to confirm the validity of our theoretical results.

Keywords

• Nonlinear multi-agent systems
• formation control
• unknown dynamics
• adaptive neural networks