We present adaptive learning control algorithms which use Markov parameters. Since in the algorithm, the control input and the model parameter are updated at each iteration, it is applicable to unknown systems in a class. In order to overcome the effect of a disturbance, Markov parameters of the inverse model is also introduced. The effectiveness of the algorithm is illustrated by means of a numerical simulation and experimental application to an active vibration isolation system.