Identification of servo-driven inverted pendulum system using neural network

Abstract

In the present work, artificial neural network (ANN) has been used to identify a servo-driven inverted pendulum system. The inverted pendulum is a benchmark problem of nonlinear multivariable system with inherent instability. The multi variable system has been considered with servomotor supply voltage as the input and four states of the system being the outputs. An LSVF controller has been used to stabilize the system for identification in closed loop. Here the non linear model of the inverted pendulum has been simulated. The Levenberg-Marquardt back-propagation method has been used for the non linear system identification via Feed-forward Neural Network (FNN). The neural network is trained using the error between the model's outputs and the plant's actual outputs. The results show good match between predicted and actual outputs.