Neural-Adaptive Finite-Time Formation Tracking Control of Multiple Nonholonomic Agents With a Time-Varying Target

Abstract

This paper investigates the leader-following formation tracking problem (FTP) for multiple nonholonomic agent systems (MNASs) in the presence of external disturbances and parametric uncertainties, where both the kinematics and dynamics of the agents are taken into consideration. A novel finite-time distributed controller-estimator algorithm (DCEA) is designed to handle such a challenging problem. Based on Lyapunov stability method, the sufficient conditions for finite-time stability of the closed-loop system are derived. Finally, the simulation results are presented to demonstrate the effectiveness and the robustness of the proposed DCEA.

Keywords

• Multiple nonholonomic agent system (MNAS)
• leader-following formation tracking problem (FTP)
• radial basis function (RBF) neural network
• distributed controller-estimator algorithm (DCEA)