Type-2 fuzzy consensus control of nonlinear multi-agent systems: An LMI approach

被引:10
|
作者
Afaghi, Ali [1 ]
Ghaemi, Sehraneh [1 ]
Ghiasi, Amir Rikhtehgar [1 ]
Badamchizadeh, Mohammad Ali [1 ]
机构
[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
关键词
LEADER-FOLLOWING CONSENSUS; CHAOTIC SYSTEMS; SYNCHRONIZATION;
D O I
10.1016/j.jfranklin.2021.03.024
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers a class of nonlinear fractional-order multi-agent systems (FOMASs) with time-varying delay and unknown dynamics, and a new robust adaptive control technique is proposed for cooperative control. The unknown nonlinearities of the systems are online approximated by the introduced recurrent general type-2 fuzzy neural network (RGT2FNN). The unknown nonlinear functions are estimated, simultaneously with the control process. In other words, at each sample time the parameters of the proposed RGT2FNNs are updated and then the control signals are generated. In addition to the unknown dynamics, the orders of the fractional systems are also supposed to be unknown. The biogeography-based optimization algorithm (BBO) is extended to estimate the unknown parameters of RGT2FNN and fractional-orders. A LMI based compensator is introduced to guarantee the robustness of the proposed control system. The excellent performance and effectiveness of the suggested method is verified by several simulation examples and it is compared with the other methods. It is confirmed that the introduced cooperative controller results in a desirable performance in the presence of time-varying delay, unknown dynamics, and unknown fractional-orders. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:4326 / 4347
页数:22
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