<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>An event-triggered adaptive control algorithm is proposed for cooperative tracking control of high-order nonlinear multi-agent systems (MASs) with prescribed performance and full-state constraints. The algorithm combines dynamic surface technology and the backstepping recursive design method, with radial basis function neural networks (RBFNNs) used to approximate the unknown nonlinearity. The barrier Lyapunov function and finite-time stability theory are employed to prove that all agent states are semi-globally uniform and ultimately bounded, with the tracking error converging to a bounded neighborhood of zero in a finite time. Numerical simulations are provided to demonstrate the effectiveness of the proposed control scheme.</p>
</abstract>

An event-triggered adaptive control algorithm is proposed for cooperative tracking control of high-order nonlinear multi-agent systems (MASs) with prescribed performance and full-state constraints. The algorithm combines dynamic surface technology and the backstepping recursive design method, with radial basis function neural networks (RBFNNs) used to approximate the unknown nonlinearity. The barrier Lyapunov function and finite-time stability theory are employed to prove that all agent states are semi-globally uniform and ultimately bounded, with the tracking error converging to a bounded neighborhood of zero in a finite time. Numerical simulations are provided to demonstrate the effectiveness of the proposed control scheme.

Event–Triggered Cooperative Control for High–Order Nonlinear Multi–Agent Systems with Finite–Time Consensus

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

An event-triggered adaptive control algorithm is proposed for cooperative tracking control of high-order nonlinear multi-agent systems (MASs) with prescribed...

Event–Triggered Cooperative Control for High–Order Nonlinear Multi–Agent Systems with Finite–Time Consensus

Data publikacji: 21 wrz 2023

Zakres stron: 439 - 448

Otrzymano: 30 sie 2022

Przyjęty: 23 mar 2023

DOI: https://doi.org/10.34768/amcs-2023-0032

Słowa kluczowe
multi-agent systems, cooperative control, event-triggered control, neuro-adaptive control, prescribed performance

© 2023 Shiyin Gong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Event–Triggered Cooperative Control for High–Order Nonlinear Multi–Agent Systems with Finite–Time Consensus

Data publikacji: 21 wrz 2023

Zakres stron: 439 - 448

Otrzymano: 30 sie 2022

Przyjęty: 23 mar 2023

DOI: https://doi.org/10.34768/amcs-2023-0032

Słowa kluczowemulti-agent systems, cooperative control, event-triggered control, neuro-adaptive control, prescribed performance

© 2023 Shiyin Gong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
multi-agent systems, cooperative control, event-triggered control, neuro-adaptive control, prescribed performance