This article proposes a novel evolutionary algorithm, called accelerated evolutionary programming (AEP), which improves evolutionary programming in terms of convergence speed and diversity. Comparison between the proposed algorithm and evolutionary programming is carried out for five widely used test functions to show the effectiveness of the proposed algorithm. The proposed algorithm is applied to the identification of a seven-parameter friction model of an X-Y table, which is adopted from the results of recent tribology studies. Based on the identified friction model, a compensator is designed for the control of the X-Y table without stick-slip motion at very low velocity. Experimental results on the X-Y table demonstrate the effectiveness of the proposed scheme. especially for very-low-speed tracking.