Practical Finite-Time Average Consensus Tracking Algorithm for Multi-Agent Systems with Bounded and Continuous Input

For multi-agent systems, average consensus tracking (ACT) problem has gained much attention in recent years. In this paper, we consider the scenario that system subject to actuator saturation. By combining hyperbolic tangent function and local neighborhood relative state errors, a continuous-time distributed ACT algorithm is proposed, and the proposed algorithm achieves uniform bounded tracking in finite-time with adjustable tracking accuracy. What is more, the settling time and tracking accuracy of the proposed algorithm are estimated by using analytical Lyapunov method. Compared with existing ACT algorithms, the proposed algorithm not only has bounded and continuous control input, but also has practical finite-time stability. Finally, numerical simulations are provided to verify the effectiveness of our theoretical results.