Regular Papers

International Journal of Control, Automation and Systems 2022; 20(3): 769-779

Published online March 11, 2022

https://doi.org/10.1007/s12555-020-0283-2

© The International Journal of Control, Automation, and Systems

Adaptive Finite-time Consensus for Second-order Nonlinear Multi-agent Systems with Input Quantization

Jiabo Ren, Baofang Wang, and Mingjie Cai*

Qingdao University

Abstract

In this paper, the adaptive finite-time consensus (FTC) control problem of second-order nonlinear multiagent systems (MASs) with input quantization and external disturbances is studied. With the help of finite time control technology, a novel distributed adaptive control protocol is constructed to achieve FTC performance for second-order nonlinear MASs by using the recursive method. The control input is quantized through a hysteresis quantizer, which reduces the communication rate of arbitrary two agents. The unknown functions are approximated by adopting the radial basis function neural networks. Under the consensus protocols and adaptive laws, it can be proved that velocity errors of arbitrary two agents reach a small region of zero in finite time as well as position errors. Finally, the effectiveness of the proposed method is illustrated via a simulation example.

Keywords Adaptive control, finite-time consensus, input quantization, multi-agent systems.

Article

Regular Papers

International Journal of Control, Automation and Systems 2022; 20(3): 769-779

Published online March 1, 2022 https://doi.org/10.1007/s12555-020-0283-2

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive Finite-time Consensus for Second-order Nonlinear Multi-agent Systems with Input Quantization

Jiabo Ren, Baofang Wang, and Mingjie Cai*

Qingdao University

Abstract

In this paper, the adaptive finite-time consensus (FTC) control problem of second-order nonlinear multiagent systems (MASs) with input quantization and external disturbances is studied. With the help of finite time control technology, a novel distributed adaptive control protocol is constructed to achieve FTC performance for second-order nonlinear MASs by using the recursive method. The control input is quantized through a hysteresis quantizer, which reduces the communication rate of arbitrary two agents. The unknown functions are approximated by adopting the radial basis function neural networks. Under the consensus protocols and adaptive laws, it can be proved that velocity errors of arbitrary two agents reach a small region of zero in finite time as well as position errors. Finally, the effectiveness of the proposed method is illustrated via a simulation example.

Keywords: Adaptive control, finite-time consensus, input quantization, multi-agent systems.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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