A neuromorphic controller for a three-link biped robot

Abstract

A neural network architecture for the control of a three-link biped walking robot is developed. The neuromorphic controller, based on hierarchical structure of artificial neural networks, is trained by supervised learning. The training model is derived by applying nonlinear feedback decoupling and an optimal tracking strategy. The neurocontroller utilizes several computational features of neural networks-generalization, parameter adaptivity, and robustness. Based on a comparison of the system performance using an optimal control law, it is concluded that the neurocontroller provides superior performance in the presence of large disturbances.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>