LAUSR

Abstract This paper investigates the fixed-time formation tracking control problem for multi-agent systems with model uncertainties and in absence of leader’s velocity measurements. For each follower, a novel fixed-time cascaded leader state observer (FTCLSO) without velocity measurements is first designed to reconstruct the states of the leader. Then, radial basis function neural networks (RBFNNs) are adopted to approximate the model uncertainties online. Based on the proposed FTCLSO and RBFNNs, a novel fixed-time formation control scheme is constructed to address the time-varying formation tracking problem by utilizing fixed-time nonsmooth backstepping technique. The fixed-time convergence of the formation tracking error is guaranteed through Lyapunov stability analysis. Finally, simulation results demonstrate the effectiveness of the proposed formation tracking control scheme.