Adaptive formation control of autonomous ground vehicles in leader-follower structure

In this paper an adaptive control law is designed for formation control of underactuated autonomous ground vehicles based on the leader-follower approach and kinematics equations. The follower vehicles have limited knowledge about the leader's states. The unknown term containing the velocity information of the leader is estimated using neural networks with online adaptive weight tuning laws. The decentralized formation control algorithm incorporates neural network estimation and guarantees semi-global ultimate uniform boundedness of all closed loop error signals. The stability is proven using Lyapunov technique and showed that the tracking error can be made small by appropriate choice of control parameters. The effectiveness and high precision of the formation controller is investigated via realistic, high-speed motion maneuvers.