Model-free distributed integral sliding mode predictive control for multi-agent systems with communication delay

Zhang，Ji1,2; Liu，Guoping3

2024-02-07

10.1016/j.neucom.2023.127133

Neurocomputing   影响因子和分区

0925-2312

1872-8286

This paper explores the problem of distributed cooperative tracking control for networked nonlinear multi-agent systems (MASs) with communication delays. The difficulty of distributed control of subsystems across several geographic areas is addressed by utilizing MASs in this study. To overcome modeling difficulties, a model-free control algorithm is employed. To handle networked delay, a network predictive control approach is utilized. To address these issues in a unified manner, a novel distributed model-free integral sliding mode predictive control strategy is proposed. This approach requires simple data to make predictions to achieve distributed tracking performance while also actively compensating for delays. The effectiveness of the proposed method is demonstrated through simulations and experimental results.

Delay Model-free distributed control Multi-agent systems Sliding mode predictive control

SCI ; EI

英语

其他

COMPUTER SCIENCE

2-s2.0-85179896138

Scopus

1.School of Information and Control Engineering,Qingdao University of Technology,Qingdao,266525,China
2.College of Electrical Engineering and Automation,Shandong University of Science and Technology,Qingdao,266590,China
3.Center for Control Science and Technology,Southern University of Science and Technology,Shenzhen,518055,China

Zhang，Ji,Liu，Guoping. Model-free distributed integral sliding mode predictive control for multi-agent systems with communication delay[J]. Neurocomputing,2024,569.

Zhang，Ji,&Liu，Guoping.(2024).Model-free distributed integral sliding mode predictive control for multi-agent systems with communication delay.Neurocomputing,569.

Zhang，Ji,et al."Model-free distributed integral sliding mode predictive control for multi-agent systems with communication delay".Neurocomputing 569(2024).