Anti-Swing and Position Control of Double Inverted Pendulum (DIP) on Cart Using Hybrid Neuro-Fuzzy Controllers

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Author(s)

Ashwani Kharola 1,*

1. Department of Mechanical Engineering, Graphic Era University, Dehradun-248001, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2016.07.03

Received: 25 Sep. 2015 / Revised: 20 Feb. 2016 / Accepted: 15 Apr. 2016 / Published: 8 Jul. 2016

Index Terms

DIP, MF's, Fuzzy logic reasoning, Neural networks, MSE, Matlab, Simulink, FLC's

Abstract

This paper illustrates a comparison study for control of highly non-linear Double Inverted Pendulum (DIP) on cart. A Matlab-Simulink model of DIP has been built using Newton's second law. The Neuro-fuzzy controllers stabilizes pendulums at vertical position while cart moves in horizontal direction. This study proposes two soft-computing techniques namely Fuzzy logic reasoning and Neural networks (NN's) for control of DIP systems. The results shows that Fuzzy controllers provides better results as compared to NN's controllers in terms of settling time (sec), maximum overshoot (degree) and steady state error. The regression (R) and mean square error (MSE) values obtained after training of Neural network were satisfactory. The simulation results proves the validity of proposed techniques.

Cite This Paper

Ashwani Kharola, "Anti-Swing and Position Control of Double Inverted Pendulum (DIP) on Cart Using Hybrid Neuro-Fuzzy Controllers", International Journal of Information Technology and Computer Science(IJITCS), Vol.8, No.7, pp.16-21, 2016. DOI:10.5815/ijitcs.2016.07.03

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