Evolutionary Algorithms in Stabilization of Inverted Pendulum

Abstract

A novel optimization algorithm of fuzzy logic controller (FLC) using genetic algorithms is used to characterize the major design parameters of an FLC known as characteristic parameters. The characteristic parameters simplify the design of FLC which are encoded into a chromosome as an integer string. These are optimized by maximizing the evaluated fitness through genetic operations to achieve the optimized FLC .An effective Genetic Algorithm (GA) is proposed using linkage learning, or building block identification. The genes arranged to have a fitness enhancement is the essence of linkage learning. A perfect and faster extended GA is suggested using an effective method to learn distributions and then by linking them. Stabilization of Inverted pendulum pole angle is taken as test bench.