An IT2FNN-Based Sliding Mode Control Approach to Formation of Multi-Agent Systems with Switching Topology

被引：0

作者：

Zuo, Wen ^{[1
]}

Wen, Fan ^{[1
]}

Gao, Yabin ^{[1
]}

Yao, Weiran ^{[1
]}

Liu, Jianxing ^{[1
]}

Wu, Ligang ^{[1
]}

机构：

[1] Harbin Inst Technol, Sch Astronaut, Harbin 150001, Peoples R China

来源：

2022 41ST CHINESE CONTROL CONFERENCE (CCC) | 2022年

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Multi-agent systems; formation control; fuzzy neural network; sliding mode control; switching topology; FUZZY-NEURAL-NETWORK;

D O I：

暂无

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 deals with the problem of robust formation control for multi-agent systems with switching topology by using a new fuzzy-neural-network based sliding mode control (SMC). A second-order nonlinear multi-agent system with uncertain velocity dynamics is formulated. In terms of the uncertain velocity dynamics term, we use an type-2 fuzzy-neuralnetwork to obtain its estimate, then an integrated SMC law based on an newly designed integral sliding variable is proposed to the formation control multi-agent systems. Besides, the convergence analysis of the formation tracking error is provided. Moreover, the analysis of the finite-time reachability of a practical sliding mode is presented based on the Lyapunov function approach. Eventually, simulation results are given to show the validity of the proposed control approach.

引用

页码：5050 / 5055

页数：6

共 22 条

[1] Fuzzy-neural sliding-mode control for DC-DC converters using asymmetric Gaussian membership functions
Cheng, Kuo-Hsiang
Hsu, Chun-Fei
Lin, Chih-Min
Lee, Tsu-Ti An
Li, Chunshien
[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2007, 54 (03) : 1528 - 1536
[2] Fixed-Time Fault-Tolerant Formation Control for Heterogeneous Multi-Agent Systems With Parameter Uncertainties and Disturbances
Cheng, Wanglei
Zhang, Ke
Jiang, Bin
Ding, Steven X.
[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2021, 68 (05) : 2121 - 2133
[3] Sliding Mode Control of Singular Stochastic Markov Jump Systems
Feng, Zhiguang
Shi, Peng
[J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2017, 62 (08) : 4266 - 4273
[4] Security for a Multi-Agent Cyber-Physical Conveyor System using Machine Learning
Funchal, Gustavo
Pedrosa, Tiago
Vallim, Marcos
Leitao, Paulo
[J]. 2020 IEEE 18TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN), VOL 1, 2020, : 47 - 52
[5] GIRARD A, 2013, IEEE T AUTOMAT CONTR, V60, P1992
[6] Bearing-Based Distributed Formation Control of Multiple Vertical Take-Off and Landing UAVs
Huang, Yi
Meng, Ziyang
[J]. IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2021, 8 (03): : 1281 - 1292
[7] Observer-Based Adaptive Sliding Mode Control for Nonlinear Stochastic Markov Jump Systems via T-S Fuzzy Modeling: Applications to Robot Arm Model
Jiang, Baoping
Karimi, Hamid Reza
Yang, Shichun
Gao, Cunchen
Kao, Yonggui
[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (01) : 466 - 477
[8] An Interval Type-2 Fuzzy-Neural Network With Support-Vector Regression for Noisy Regression Problems
Juang, Chia-Feng
Huang, Ren-Bo
Cheng, Wei-Yuan
[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2010, 18 (04) : 686 - 699
[9] An Event-Triggered Approach to Sliding Mode Control of Markovian Jump Lur'e Systems Under Hidden Mode Detections
Song, Jun
Niu, Yugang
Xu, Jing
[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 50 (04): : 1514 - 1525
[10] Membership-Function-Dependent Stability Analysis and Control Synthesis of Guaranteed Cost Fuzzy-Model-Based Control Systems
Lam, H. K.
Xiao, Bo
Yu, Yan
Yin, Xunhe
Han, Hugang
Tsai, Shun-Hung
Chen, Chin-Sheng
[J]. INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2016, 18 (04) : 537 - 549

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