This article investigates the practical finite-time consensus for a class of heterogeneous multi-agent systems composed of first-order and second-order agents with heterogeneous unknown nonlinear dynamics and external disturbances in an undirected communication topology. To reduce the system updates, we propose an event-triggered approach. By defining auxiliary states, an adaptive distributed event-triggered control is designed to achieve practical finite-time consensus. Unknown nonlinear dynamics for each agent are estimated using radial basis function neural network. The stability of the overall closed-loop system is studied through the Lyapunov criterion. It is proven that by applying the proposed control scheme, the local neighbor position error and the velocity error between any two agents converge to a small region in finite time. Furthermore, it is shown that the Zeno behavior is ruled out. Finally, applicability and effectiveness of the proposed control scheme is verified and validated by two examples.

This study deals with the adaptive finite-time consensus problem of heterogeneous multi-agent systems composed of first-order and second-order agents with unknown nonlinear dynamics and asymmetric input dead-zone under connected undirected topology. Under the proposed protocol and adaptive laws, a sliding mode variable for every agent converges to a compact set in finite time, and also the position errors and the velocity errors (for second-order agents) between any two agents converge to a small desired neighborhood of the origin in finite time. Each agent requires its states and the relative positions of its neighbors. By applying sliding mode control, the external disturbances, and the imperfect approximation of neural networks are rejected. The unknown terms of the agents’ dynamics are approximated using radial basis function neural networks. The adaptive compensator plus dead-zone is applied to overcome the asymmetric input dead-zone. Based on Lyapunov stability theory, analysis is led on stability. Different from the previous works, the global information graph is not used in the proposed protocol. Finally, our approach is examined for two examples to evaluate its performance.

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This paper investigates the practical finite-time consensus problem for heterogeneous multi-agent systems with unknown nonlinear dynamics, the asymmetric input dead zone, and external disturbances under directed topology. The model of heterogeneous multi-agent systems is composed of first-order and second-order dynamics. First, we show that under the proposed protocol, the sliding mode surface converges to a compact set in finite time. Then, we prove that the position errors and the velocity errors (for second-order agents) between any two agents reach a small desired neighborhood of the origin in finite time. In this approach, adaptive neural networks are employed to compensate for the nonlinear dynamics of agents. By applying sliding mode control, the external disturbances and the imperfect approximation of neural networks are rejected. The approach of the adaptive compensator plus dead zone is applied to overcome the asymmetric input dead zone. Besides, our proposed protocol is fully distributed, which means that the global graph information is not required beforehand by adaptive control gains. The effectiveness of our proposed protocol is finally validated through numerical simulations.