Stabilization of an inverted pendulum by a layered neural network

This paper discusses the stabilization of an inverted pendulum by a neural network. The inverted pendulum is a typical example of an unstable and nonlinear system. Fujitsu has developed a self-learning method that enables a neural network to control an inverted pendulum by using heuristic rules. A system based on this method has been developed which generates teaching data for inversion by trial and error. Then, the neural network learns the teaching data, and acquires the control rules after a period of trial and error. The method proved its effectiveness by stably inverting a pendulum in an experimental inverted pendulum system after a period of trial and error.