Implementation of Evolving Neural Network Controller for Inverted Pendulum System

진화형 신경회로망에 의한 도립진자 제어시스템의 구현

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions, At the same time, the fine tunings of their gain parameters are also troublesome, Thus, in this paper, an Evolving Neural Network ControlleY(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm (RVEGA) was presented for stabilization of an IP system with nonlinearity, This proposed ENNC was described by a simple genetic chromosome. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.