Region tracking control for high-order multi-Agent systems in restricted space

In this study, decentralised region tracking control is proposed to force a group of mobile agents with highorder non-linear dynamics to track a moving target region without collisions as well as to avoid the obstacle on the track in restricted space. The decentralised controllers can also guarantee connectivity preserving of the dynamic interaction network. The control design is based on artificial potential functions, neural network (NN) approximation, adaptive backstepping techniques and Lyapunov's method. It is proved that under the adaptive NN control, the tracking error of each agent can converge to an adjustable neighbourhood of the origin, although some of them do not access the desired region directly. Simulation results are represented to illustrate the performance of the proposed approach.