Extreme-learning-machine-based robust integral terminal sliding mode control of bicycle robot

被引：31

作者：

Chen, Long ^{[1
]}

Yan, Bin ^{[1
]}

Wang, Hai ^{[2
]}

Shao, Ke ^{[3
]}

Kurniawan, Edi ^{[4
]}

Wang, Guangyi ^{[1
]}

机构：

[1] Hangzhou Dianzi Univ, Sch Elect & Informat, Hangzhou 310018, Peoples R China

[2] Murdoch Univ, Ctr Water Energy & Waste, Discipline Engn & Energy, Perth, WA 6150, Australia

[3] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China

[4] Natl Res & Innovat Agcy, Res Ctr Phys, Tangerang Selatan 15314, Indonesia

来源：

CONTROL ENGINEERING PRACTICE | 2022年 / 121卷

基金：

中国国家自然科学基金;

关键词：

Balancing; Integral terminal sliding mode (ITSM); Bicycle robot (BR); Extreme learning machine (ELM); ELECTRONIC THROTTLE; AUTONOMOUS BICYCLE; STABILIZATION; SPACECRAFT; OBSERVER; SYSTEMS;

D O I：

10.1016/j.conengprac.2022.105064

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, an extreme-learning-machine (ELM)-based robust integral terminal sliding mode (ITSM) control scheme is developed for a bicycle robot (BR) to achieve balancing target. First, the bicycle robot equipped with a reaction wheel is formulated by a second-order mathematical model with uncertainties. Then, an ITSM controller is designed for the balancing control of the BR, where an ELM scheme is designed as a compensator for estimating lumped uncertainties of the system. The stability proof of the closed-loop control system is presented based on Lyapunov theory. Comparative experimental results are demonstrated to verify the superior balancing performance of the proposed control.

引用

页数：10

共 38 条

[1]

[Anonymous], 2002, IFAC P

[2] Bicycle dynamics and control [J].

Åström, KJ ;

Klein, RE ;

Lennartsson, A .

IEEE CONTROL SYSTEMS MAGAZINE, 2005, 25 (04) :26-47

[3] A robust two-stage active disturbance rejection control for the stabilization of a riderless bicycle [J].

Baquero-Suarez, Mauro ;

Cortes-Romero, John ;

Arcos-Legarda, Jaime ;

Coral-Enriquez, Horacio .

MULTIBODY SYSTEM DYNAMICS, 2019, 45 (01) :7-35

[4] Cycle-to-cycle modeling and sliding mode control of blended-fuel HCCI engine [J].

Bidarvatan, M. ;

Shahbakhti, M. ;

Jazayeri, S. A. ;

Koch, C. R. .

CONTROL ENGINEERING PRACTICE, 2014, 24 :79-91

[5] Sparse Representation-Based Augmented Multinomial Logistic Extreme Learning Machine With Weighted Composite Features for Spectral-Spatial Classification of Hyperspectral Images [J].

Cao, Faxian ;

Yang, Zhijing ;

Ren, Jinchang ;

Ling, Wing-Kuen ;

Zhao, Huimin ;

Sun, Meijun ;

Benedilasson, Jon Atli .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (11) :6263-6279

[6] Modeling and Control of an Active Stabilizing Assistant System for a Bicycle [J].

Chen, Chih-Keng ;

Trung-Dung Chu ;

Zhang, Xiao-Dong .

SENSORS, 2019, 19 (02)

[7] Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode [J].

Chen, Long ;

Liu, Jun ;

Wang, Hai ;

Hu, Youhao ;

Zheng, Xuefeng ;

Ye, Mao ;

Zhang, Jie .

NONLINEAR DYNAMICS, 2021, 104 (03) :2291-2302

[8] Continuous terminal sliding mode control using novel fuzzy neural network for active power filter [J].

Chu, Yundi ;

Hou, Shixi ;

Fei, Juntao .

CONTROL ENGINEERING PRACTICE, 2021, 109

[9]

Cruz-Ortiz D., 2021, ISA Trans.

[10] Sliding-Mode Control Scheme for an Intelligent Bicycle [J].

Defoort, Michael ;

Murakami, Toshiyuki .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2009, 56 (09) :3357-3368

← 1 2 3 4 →