Modeling of Inverted Pendulum on a Cart by Using Artificial Neural Networks

被引：0

作者：

Korkmaz, Deniz ^{[1
]}

Bal, Cafer ^{[2
]}

Gokbulut, Muammer ^{[3
]}

机构：

[1] Firat Univ, Elekt & Bilgisayar Egitimi Bolumu, Elazig, Turkey

[2] Firat Univ, Mekatron Muhendisligi Bolumu, Elazig, Turkey

[3] Firat Univ, Elekt & Elekt Muhendisligi Bolumu, Elazig, Turkey

来源：

2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年

关键词：

inverted pendulum; artificial neural networks; lagrange method; nonlinear modeling;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this study, mathematical model of the single bar inverted pendulum on a cart, which exhibits similar behavior to the dynamics of a robotic arm, is derived by using Lagrange method. At the same time, nonlinear model of the inverted pendulum is simulated in MATLAB environment by using Multilayer Artificial Neural Networks (MANN). MANN is trained by back propagation learning algorithm and dynamic NARX network model is selected for MANN. This model is the basis for dynamics of the robotic arm.

引用

页码：2642 / 2645

页数：4

共 50 条

[41] Modeling photosynthetically oxygenated biodegradation processes using artificial neural networks [J].

Arranz, A. ;

Bordel, S. ;

Villaverde, S. ;

Zamarreno, J. M. ;

Guieysse, B. ;

Munoz, R. .

JOURNAL OF HAZARDOUS MATERIALS, 2008, 155 (1-2) :51-57

[42] NONLINEAR MODELING OF CHROMIUM TANNING SOLUTION USING ARTIFICIAL NEURAL NETWORKS [J].

MARJONIEMI, M .

APPLIED SPECTROSCOPY, 1994, 48 (01) :21-26

[43] Recent Advances in the Modeling of Ionic Liquids Using Artificial Neural Networks [J].

Racki, Adrian ;

Paduszynski, Kamil .

JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2025, 65 (07) :3161-3175

[44] Modeling sterilization process of canned foods using artificial neural networks [J].

Gonçalves, EC ;

Minim, LA ;

Coimbra, JSR ;

Minim, VPR .

CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2005, 44 (12) :1269-1276

[45] Modeling the Biocatalytic Method of Lipid Extraction Using Artificial Neural Networks [J].

Shafrai, Anton V. ;

Prosekov, Alexander Yu. ;

Vechtomova, Elena A. .

INFORMATION, 2023, 14 (08)

[46] Surrogate Modeling of Electrical Machine Torque Using Artificial Neural Networks [J].

Tahkola, Mikko ;

Keranen, Janne ;

Sedov, Denis ;

Far, Mehrnaz Farzam ;

Kortelainen, Juha .

IEEE ACCESS, 2020, 8 :220027-220045

[47] DYNAMIC SYSTEMS MODELING USING ARTIFICIAL NEURAL NETWORKS FOR AGRICULTURAL MACHINES [J].

Dorokhov, A. S. ;

Sibirev, A., V ;

Aksenov, A. G. .

INMATEH-AGRICULTURAL ENGINEERING, 2019, 58 (02) :63-74

[48] Modeling of the river ecological status with macrophytes using artificial neural networks [J].

Gebler, D. ;

Szoszkiewicz, K. ;

Pietruczuk, K. .

LIMNOLOGICA, 2017, 65 :46-54

[49] Modeling of reflectance properties of ZnO film using artificial neural networks [J].

Yuksek, A. G. ;

Tuzemen, E. Senadim ;

Elagoz, S. .

JOURNAL OF OPTOELECTRONICS AND ADVANCED MATERIALS, 2015, 17 (11-12) :1615-1628

[50] Using Artificial Neural Networks for Predictive Modeling of Graduates' Professional Choice [J].

Gerasimovic, Milica ;

Stanojevic, Ljiljana ;

Bugaric, Ugljesa ;

Miljkovic, Zoran ;

Veljovic, Alemoije .

NEW EDUCATIONAL REVIEW, 2011, 23 (01) :175-188

← 1 2 3 4 5 →