Dynamic Modeling of a Nonlinear Two-Wheeled Robot Using Data-Driven Approach

被引:11
作者
Khan, Muhammad Aseer [1 ]
Baig, Dur-e-Zehra [2 ]
Ashraf, Bilal [1 ]
Ali, Husan [1 ]
Rashid, Junaid [3 ]
Kim, Jungeun [3 ]
机构
[1] Air Univ Islamabad, Dept Elect Engn, Aerosp & Aviat Campus Kamra, Attock 43570, Pakistan
[2] Ghulam Ishaq Khan Inst Engn Sci & Technol, Fac Elect Engn, Topi 23640, Pakistan
[3] Kongju Natl Univ, Dept Comp Sci & Engn, Cheonan 31080, South Korea
关键词
system identification; data-driven modelling; two-wheeled robot; parameter estimation; ARX; NLRAX; HEART-RATE REGULATION; IDENTIFICATION; PENDULUM;
D O I
10.3390/pr10030524
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
A system identification of a two-wheeled robot (TWR) using a data-driven approach from its fundamental nonlinear kinematics is investigated. The fundamental model of the TWR is implemented in a Simulink environment and tested at various input/output operating conditions. The testing outcome of TWR's fundamental dynamics generated 12 datasets. These datasets are used for system identification using simple autoregressive exogenous (ARX) and non-linear auto-regressive exogenous (NLARX) models. Initially the ARX structure is heuristically selected and estimated through a single operating condition. We conclude that the single ARX model does not satisfy TWR dynamics for all datasets in term of fitness. However, NLARX fitted the 12 estimated datasets and 2 validation datasets using sigmoid nonlinearity. The obtained results are compared with TWR's fundamental dynamics and predicted outputs of the NLARX showed more than 98% accuracy at various operating conditions.
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页数:9
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