System Identification of Nonlinear Inverted Pendulum Using Artificial Neural Network

被引:0
|
作者
Gautam, Pooja [1 ]
机构
[1] Rajasthan Tech Univ, Univ Coll Engn, Dept Elect Engn, Kota 324010, Rajasthan, India
关键词
Artificial Neural Network; nonlinear system; inverted pendulum; system identification;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
System identification is the process of developing a mathematical model of a system using input and output knowledge of system. Identification of nonlinear system is well known problem due to its unpredictability and complexity. The nonlinear system for identification is Inverted Pendulum in this work which is well known benchmark system in control system theory due to it's highly nonlinear and unstable characteristics. In this work Lagrangian approach has been used for system dynamic modelling. Artificial neural network is utilized for model identification.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] System Identification of Rotary Double Inverted Pendulum Using Artificial Neural Networks
    Chandran, Deepak
    Krishna, Bipin
    George, V. I.
    Thirunavukkarasu, I.
    [J]. 2015 INTERNATIONAL CONFERENCE ON INDUSTRIAL INSTRUMENTATION AND CONTROL (ICIC), 2015, : 612 - 617
  • [2] Optimal Control of Inverted Pendulum System Using ADALINE Artificial Neural Network with LQR
    Gautam, Pooja
    [J]. 2016 INTERNATIONAL CONFERENCE ON RECENT ADVANCES AND INNOVATIONS IN ENGINEERING (ICRAIE), 2016,
  • [3] Model Identification of Rotary Inverted Pendulum Using Artificial Neural Networks
    Chandran, Deepak
    Krishna, Bipin
    George, V. I.
    Thirunavukkarasu, I.
    [J]. 2015 INTERNATIONAL CONFERENCE ON RECENT DEVELOPMENTS IN CONTROL, AUTOMATION AND POWER ENGINEERING (RDCAPE), 2015, : 146 - 150
  • [4] System Identification of an Inverted Pendulum Using Adaptive Neural Fuzzy Inference System
    Chawla, Ishan
    Singla, Ashish
    [J]. HARMONY SEARCH AND NATURE INSPIRED OPTIMIZATION ALGORITHMS, 2019, 741 : 809 - 817
  • [5] Identification Inverted Pendulum System Using Multilayer and Polynomial Neural Networks
    Orozco, L. M. L.
    Lomeli, G. R.
    Moreno, G. J. R.
    Perea, M. T.
    [J]. IEEE LATIN AMERICA TRANSACTIONS, 2015, 13 (05) : 1569 - 1576
  • [6] IMPLEMENTATION OF SLIDING MODE CONTROL WITH ARTIFICIAL NEURAL NETWORK TO THE ROTARY INVERTED PENDULUM SYSTEM
    Aydin, Muhammet
    Yakut, Oguz
    Alli, Hasan
    [J]. SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2013, 5 (01): : 39 - 50
  • [7] Rotary Inverted Pendulum Identification for Control by Paraconsistent Neural Network
    de Carvalho, Arnaldo, Jr.
    Justo, Joao Francisco
    Angelico, Bruno Augusto
    de Oliveira, Alexandre Manicoba
    da Silva Filho, Joao Inacio
    [J]. IEEE ACCESS, 2021, 9 : 74155 - 74167
  • [8] Control of a sliding inverted pendulum using a neural network
    Huang, SJ
    Huang, CL
    [J]. INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 1996, 9 (2-3) : 67 - 75
  • [9] System identification for nonlinear maneuvering of large tankers using artificial neural network
    Rajesh, G.
    Bhattacharyya, S. K.
    [J]. APPLIED OCEAN RESEARCH, 2008, 30 (04) : 256 - 263
  • [10] Modeling of Inverted Pendulum on a Cart by Using Artificial Neural Networks
    Korkmaz, Deniz
    Bal, Cafer
    Gokbulut, Muammer
    [J]. 2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2015, : 2642 - 2645