Model identification of rotary inverted pendulum using artificial neural networks

Deepak Chandran, Bipin Krishna, V. I. George, I. Thirunavukkarasu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

System Identification has been widely used in obtaining the mathematical model of nonlinear systems. Nonlinear system identification is challenging because of its complexity and unpredictability. The nonlinear system considered in this paper is Rotary Inverted Pendulum which is unstable and non-minimum phase system. Inverted pendulum is a well-known benchmark system in control system laboratories which is inherently unstable. In this work full dynamics of the system is derived using classical mechanics and Lagrangian formulation. Artificial neural network is used to identify the model.

Original languageEnglish
Title of host publication2015 International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages146-150
Number of pages5
ISBN (Electronic)9781479972470
DOIs
Publication statusPublished - 28-09-2015
EventInternational Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015 - Noida, India
Duration: 12-03-201513-03-2015

Conference

ConferenceInternational Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015
CountryIndia
CityNoida
Period12-03-1513-03-15

Fingerprint

Pendulums
Nonlinear systems
Identification (control systems)
Neural networks
Mechanics
Mathematical models
Control systems

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Energy Engineering and Power Technology

Cite this

Chandran, D., Krishna, B., George, V. I., & Thirunavukkarasu, I. (2015). Model identification of rotary inverted pendulum using artificial neural networks. In 2015 International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015 (pp. 146-150). [7281385] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RDCAPE.2015.7281385
Chandran, Deepak ; Krishna, Bipin ; George, V. I. ; Thirunavukkarasu, I. / Model identification of rotary inverted pendulum using artificial neural networks. 2015 International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 146-150
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Chandran, D, Krishna, B, George, VI & Thirunavukkarasu, I 2015, Model identification of rotary inverted pendulum using artificial neural networks. in 2015 International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015., 7281385, Institute of Electrical and Electronics Engineers Inc., pp. 146-150, International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015, Noida, India, 12-03-15. https://doi.org/10.1109/RDCAPE.2015.7281385

Model identification of rotary inverted pendulum using artificial neural networks. / Chandran, Deepak; Krishna, Bipin; George, V. I.; Thirunavukkarasu, I.

2015 International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 146-150 7281385.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - System Identification has been widely used in obtaining the mathematical model of nonlinear systems. Nonlinear system identification is challenging because of its complexity and unpredictability. The nonlinear system considered in this paper is Rotary Inverted Pendulum which is unstable and non-minimum phase system. Inverted pendulum is a well-known benchmark system in control system laboratories which is inherently unstable. In this work full dynamics of the system is derived using classical mechanics and Lagrangian formulation. Artificial neural network is used to identify the model.

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Chandran D, Krishna B, George VI, Thirunavukkarasu I. Model identification of rotary inverted pendulum using artificial neural networks. In 2015 International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 146-150. 7281385 https://doi.org/10.1109/RDCAPE.2015.7281385