A new approach of quantum-inspired genetic algorithm for self-generation of fuzzy logic controller

This paper presents a new approach in generating fuzzy logic controller based on quantum-inspired genetic algorithm. The concept of quantum bits superposition is employed in the algorithm in order to improve the parallelism. A dynamic genepool is also used to preserve the genetic information of the individuals. Subsequently, a filter algorithm is applied to ensure the compactness of the generated rule base and to enforce the convergence; a quantum gate is applied on every generation. The problem balancing pole on a cart (inverted pendulum system) is used to train and test the algorithm.