Adaptive Neural Network Leader-Follower Formation Control for a Class of Second-Order Nonlinear Multi-Agent Systems With Unknown Dynamics

Abstract

In this article, an adaptive leader-follower formation control on the basis of neural network (NN) is developed for a class of second-order nonlinear multi-agent systems with unknown dynamics. Unlike the first-order formation control that only needs to govern the position states, the second-order formation control needs to govern both the position and velocity variables. Hence the second-order formation is more challenging and interesting than the first-order case. In the control design, the adaptive NN approximator is employed to compensate the nonlinear uncertainties, so that the control design difficulty coming from the unknown dynamics is effectively overcome. Through Lyapunov stability analysis, it is demonstrated that the proposed control method can complete the control tasks. To further demonstrate the effectiveness, the formation method is implemented to a numerical simulation, and it shows the desired results.

Keywords

• Nonlinear multi-agent systems
• formation control
• double integral dynamic
• neural networks