@article{70,
  keywords = {Feed drive, Identification, Modeling, Virtual CNC},
  author = {Kaan Erkorkmaz and Wilson Wong},
  title = {Rapid identification technique for virtual CNC drives},
  abstract = {<p>This paper presents a technique for rapid identification of machine tool drives by conducting a short G-code test. The proposed strategy uses commanded and measured axis profiles and requires minimal intervention to the servo control loop. The drive system is identified as a whole, including the feed mechanism, motor, amplifier, and the control law. The methodology is fairly general and applicable to linear or ball screw drives, controlled with commonly used controllers like P, PI, PID, P-PI Cascade or Adaptive Sliding Mode Control; with or without feedforward dynamic or friction compensation. In order to guarantee the stability of identified dynamics, bounds are imposed on the pole locations. The identified models can be used in a Virtual CNC system for predicting the contouring and tracking errors to different part programs. Simulation and experimental case studies are presented, where tracking and contour errors are successfully predicted using drive models identified with the proposed strategy.</p>
},
  year = {2007},
  journal = {International Journal of Machine Tools and Manufacture},
  volume = {47},
  pages = {1381-1392},
  issn = {0890-6955},
  url = {https://www.sciencedirect.com/science/article/pii/S0890695506002021},
  doi = {https://doi.org/10.1016/j.ijmachtools.2006.08.025},
}