A Real-Time Nonlinear Hammerstein Model For Bidirectional DC Motor Based on Multi-Layer Neural Networks

被引：0

作者：

Kwad, Ayad M. ^{[1
]}

Hanafi, Dirman ^{[1
]}

Bin Omar, Rosli ^{[1
]}

Rahman, Hisyam Bin Abdul ^{[1
]}

机构：

[1] Univ Tun Hussein Onn Malaysia UTHM, Fac Elect & Elect Engn FKEE, Batu Pahat 86400, Johor, Malaysia

来源：

2020 18TH IEEE STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT (SCORED) | 2020年

关键词：

black-box; block-oriented; DC motor; Hammerstein model; neural networks; nonlinear model; real-time; recursive weighted least squares; SYSTEM-IDENTIFICATION; WHITE-BOX;

D O I：

10.1109/scored50371.2020.9250988

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

System identification is finding a model that can describe the dynamic characteristic of the examined system and predict the next output depending on the collected input/output data for that system at previous times. All the real dynamic systems have a nonlinear behavior, but this non-linearity is graduating from a simple to a brutal degree; Mechatronic systems are not spared from this rule. This article presents a real-time nonlinear model for bidirectional DC motor based on block-oriented Hammerstein to avoid the Coulomb friction and its dead zone nonlinear effect with the viscous friction. The recursive weighted least squares (RWLS) method is used to train the Hammerstein network. The mean square error for the system's closest model is about 9.5 relative to fluctuated output speed from 1870 to -1035 (rpm).

引用

页码：102 / 107

页数：6

共 30 条

[1]

[Anonymous], 2009, Neural networks and learning machines

[2]

Berthier Y., 2001, BACKGROUND FRICTION, P676

[3]

Bjekic M, 2011, INT REV ELECTR ENG-I, V6, P2261

[4]

Budai C., 2017, FRICTION EFFECTS MEC

[5] Black- and white-box approaches for cascaded tanks benchmark system identification [J].

Giordano, G. ;

Sjoberg, J. .

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2018, 108 :387-397

[6]

Hanafi D., 2017, J. Telecommun. Electron. Comput. Eng, V9, P135

[7]

Hong E.Y., 2013, 2013 IEEE International Underwater Technology Symposium, P1

[8]

Hunt K. J., 2012, NEURAL NETWORK ENG D

[9] Nonlinear modeling and identification of a DC motor for bidirectional operation with real time experiments [J].

Kara, T ;

Eker, I .

ENERGY CONVERSION AND MANAGEMENT, 2004, 45 (7-8) :1087-1106

[10] White box, black box and self-organization A system-to-environment approach to leadership [J].

Kasianiuk, Krzysztof .

KYBERNETES, 2016, 45 (01) :126-140

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