A New Method Based on Improved Ant Colony Algorithm to Configure Friction Compensation Pulse Characteristic Parameters

Friction is one of the disadvantages to obtain high speed and high accuracy in servo feed system. A new optimal method based on ant colony algorithm is proposed to overcome the problem of time-consuming and poor result when determining friction compensation pulse sequences parameters at reverse points in this paper. The intelligent process can be rapidly realized by evaluating fitness function, which is composed of peak and mean errors of quadrant friction errors. An improved version of roulette strategy is introduced to improve search efficiency and avoid encountering local optimization, called improved ant colony algorithm (IACO). In addition, because of its openness and universality, it is easily embedded in CNC System. The experimental result is presented to illustrate the effectiveness of this approach in suppressing mean and peak errors at the reverse point. It is shown that the improved method has advantages of strong convergence, remarkable effect and better robustness, which promotes contour accuracy around reverse points.