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System Identification of an Inverted Pendulum Using Adaptive Neural Fuzzy Inference System

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Harmony Search and Nature Inspired Optimization Algorithms

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 741))

Abstract

The objective of this paper is to illustrate the efficiency of adaptive neural fuzzy inference system (ANFIS) in identifying a nonlinear single-input multiple-output (SIMO) system. The SIMO system used for demonstration is cart-inverted pendulum, which is well known for its highly nonlinear, unstable, and under-actuated nature. The ANFIS model of cart-inverted pendulum (CIP) is designed in Matlab Simulink environment using input–output data obtained from nonlinear mathematical model. The simulation responses for different initial conditions are obtained from ANFIS model which are further compared to the mathematical model of the system. It was observed that within the trained operating range, ANFIS model exactly replicated the nonlinear mathematical model of the system while a little deviation is observed outside the trained operating range. Thus, the authors propose to use ANFIS for system identification from experimental input–output data when the system parameters are unknown or uncertain.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Thapar Institute of Engineering and Technology, Patiala, 147004, India

    Ishan Chawla & Ashish Singla

Authors
  1. Ishan Chawla
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  2. Ashish Singla
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Corresponding author

Correspondence to Ashish Singla .

Editor information

Editors and Affiliations

  1. School of Engineering and Technology, BML Munjal University, Gurgaon, Haryana, India

    Neha Yadav

  2. Department of Sciences and Humanities, National Institute of Technology, Srinagar, Uttarakhand, India

    Anupam Yadav

  3. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  4. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  5. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, Korea (Republic of)

    Joong Hoon Kim

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Chawla, I., Singla, A. (2019). System Identification of an Inverted Pendulum Using Adaptive Neural Fuzzy Inference System. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_77

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