TY  - JOUR
T1  - Inverted Pendulum Control using NARMA-L2 with Resilient Backpropagation and Levenberg
Marquardt Backpropagation Training Algorithm
AU - Jibril, Mustefa AU - Hassen, Nuriye AU - Tadese, Messay 
JO  - Journal of Engineering and Applied Sciences
VL  - 16
IS  - 10
SP  - 324
EP  - 330
PY  - 2021
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2021.324.330
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2021.324.330
KW  - resilient backpropagation
KW  -NARMA-L2
KW  -Inverted pendulum
KW  -Levenberg Marquardt backpropagation
AB  - 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.
ER  -