Seasonal variation of neuro-controller training period observed in the control task of inverted pendulum

In general, computer simulations are a useful means to confirm the effectiveness of a control scheme, but the actual system is not so easy to handle. In order to overcome such underlying realistic problems, adaptability of neural networks is focused on by many researchers. In this study, an on-line training model for self-turning control is constructed based on the famous feedback error learning model, and its effectiveness is investigated through a task for controlling an inverted pendulum. As a result of several experiments, repeatable strange phenomena, such as seasonal variation of training period and reversalization of control command, are observed.