Inverted Pendulum Control using NARMA-l2 with Resilient Backpropagation and Levenberg Marquardt Backpropagation Training Algorithm

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.