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Adaptive Neural Network Control for a Simple Pendulum Using Backstepping with Uncertainties

An adaptive neural network backstepping control for a class of uncertain nonlinear systems is presented in this paper. Three main issues will be treated: (1) unknown nonlinearities; (2) unknown system parameters; (3) external or internal disturbances. The proposed technique is applied to a simple pendulum. This latter is an unstable system which is perfectly described by a nonlinear model obtained by applying physics laws. A solution has to be found to stabilize pendulum in a desired position. A specific type of artificial neural networks (ANN) called "Multilayer Perceptron (MLP)" is used and simulation results clearly demonstrate the power of this extension.