Adaptive finite-time consensus tracking for multiple uncertain mechanical systems with input saturation

This paper investigates the problem of finite-time consensus tracking for a class of multiple uncertain mechanical systems under switching topologies. In the presence of uncertainties and input saturations, a distributed observer-based adaptive finite-time tracking protocol is proposed. At the first step, a distributed observer is proposed for each mechanical system to observe the leader's state in finite time; then, an adaptive finite-time tracking protocol is designed to track the estimated state via recursive design method. Neural networks are used to approximate the unknown continuous functions. It is proved that under the designed protocol, the consensus tracking of position and velocity can be achieved in finite time. Finally, an example is given to demonstrate the effectiveness of the proposed method. Copyright (C) 2017 John Wiley & Sons, Ltd.