Motion control of a mobile pendulum system using neural network

The motion of the mobile inverted pendulum system (MIPS) is controlled by a neural network controller along with PID controllers. The MIPS is required to follow the circular trajectory while maintaining the balance. The radial basis function (RBF) network is trained with the back-propagation algorithm in on-line fashion. The DSP 2812 board is developed and used for the massive calculation of neural parallel processing to achieve an on-line learning and control. Experimental studies are conducted and confirm the performance of the RBF neural network controller.