An adaptive tracking algorithm is developed to achieve quantum system control field designs. The adaptive algorithm has the advantage of operating noniteratively to efficiently find desirable controls, and has the feature of high stability by suppressing the influence of disturbances from tracking singularities. The core of the adaptive tracking control algorithm is a self-learning track switch technique which is triggered by monitoring of the evolving system trajectory. The adaptive tracking algorithm is successfully tested for population transfer. (C) 2003 American Institute of Physics.