Neuro-Control Robustness Analysis of an Inverted Pendulum Using the Bee Algorithm

Abstract

In this paper, the Bee Algorithm is used to train a Neural Network. This is done by altering the connections and biases of the Neural Network (NN) so that the desired output from the input is obtained. The merging between the two concepts is tested to control an inverted pendulum which is a benchmark for testing control theories. The trained NN is used to stabilize the pendulum in its upright position. The NN is trained by comparing its response to that of a state feedback controller. The Bee Algorithm succeeded in training the NN for it to have the desired output. Moreover, the effect of changing the parameters of both the neural network and the bee algorithm is also studied.