Adaptive Finite-Time Cooperative Motion Control of Nonlinear Multi-AGV Systems: Algorithm and Experiment

This paper addresses the formation control problem for the uncertain second-order nonlinear multi-automatic guided vehicle systems(MAGVs). An adaptive finite-time formation control scheme is developed, which considers both the obstacle avoidance and the MAGVs collision avoidance. The proposed strategy is suitable for practical applications in the smart manufacturing field. By applying the virtual structure method, and the artificial potential functions, the desired velocity input for achieving the cooperative motion is obtained. Then, the adaptive tracking control strategy is proposed recursively by combining the fractional dynamic surface and the backstepping method. In addition, the radial basis function neural networks are introduced to estimate the unknown function. Based on the finite-time stability theory, the tracking errors of the systems converge into an arbitrary small bounded set in the finite-time. Lastly, the simulation and experiment results demonstrate the effectiveness of the proposed control scheme.