Chaotic Genetic Algorithm for Wavefront Correction in Adaptive Optics

Chaotic genetic algorithm (CGA) is presented as an optimization algorithm for sensorless adaptive optics system to compensate atmospheric wave aberration. Chaos search strategy is incorporated into standard genetic algorithm by the logistic function that possess convergent, bifurcating, and chaotic characteristics during evolution to control the convergence of genetic algorithm. A real number encoding method is adopted in the search process and CGA is used to control a 61-actuator deformable membrane mirror (DM).The algorithm uses light intensity detected on the focal plane as the objective function to optimize, and the simulation results show CGAperforms faster than GA and thus can effectively be used in AO systems.