Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
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Abstract
In this study, the performance of inverted pendulum has been Investigated using neural network control theory. The proposed controllers used in this study are NARMA-L2 with resilient backpropagation and Levenberg Marquardt backpropagation algorithm controllers. The mathematical model of Inverted Pendulum on a Cart driving mechanism have been done successfully. Comparison of an inverted pendulum with NARMA-L2 with resilient backpropagation and Levenberg Marquardt backpropagation algorithm controllers for a control target deviation of an angle from vertical of the inverted pendulum using two input signals (step and random). The simulation result shows that the inverted pendulum with NARMA-L2 with resilient backpropagation controller to have a small rise time, settling time and percentage overshoot in the step response and having a good response in the random response too. Finally, the inverted pendulum with with NARMA-L2 with resilient backpropagation controller shows the best performance in the overall simulation result.
How to cite this article:
Nuriye Hassen, Messay Tadese and Mustefa Jibril. Inverted Pendulum Control using NARMA-L2 with Resilient Backpropagation and Levenberg
Marquardt Backpropagation Training Algorithm.
DOI: https://doi.org/10.36478/jeasci.2021.324.330
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2021.324.330