Izvorni znanstveni članak

https://doi.org/10.17559/TV-20220417095645

Distributed Adaptive Control for a Class of Heterogeneous Nonlinear Multi-Agent Systems with Nonidentical Dimensions

Bo Qin orcid.org/0000-0002-3686-3612 ; School of Automation, Xi'an Key Laboratory of Advanced Control and Intelligent Process, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
Yongqing Fan ; School of Automation, Xi'an Key Laboratory of Advanced Control and Intelligent Process, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
Yang Gao ; Beijing Aerospece Institute for Metrology and Measurement Technology, Beijing 100744, China

Sažetak

A novel feedback distributed adaptive control strategy based on radial basis neural network (RBFNN) is proposed for the consensus control of a class of leaderless heterogeneous nonlinear multi-agent systems with the same and different dimensions. The distributed control, which consists of a sequence of comparable matrices or vectors, can make that all the states of each agent to attain consensus dynamic behaviors are defined with similar parameters of each agent with nonidentical dimensions. The coupling weight adaptation laws and the feedback management of neural network weights ensure that all signals in the closed-loop system are uniformly ultimately bounded. Finally, two simulation examples are carried out to validate the effectiveness of the suggested control design strategy.

Ključne riječi

distributed control; heterogeneous multi-agent systems; radial basis function neural network (RBFNN); uniformly ultimately bounded (UUB)

Hrčak ID:

281666

URI

https://hrcak.srce.hr/281666

Datum izdavanja:

15.10.2022.

Posjeta: 498 *