Abstract
Diamond turning of brittle materials such as glass, ceramic, germanium and zinc sulfide has been of considerable research interest in recent years due to applications in optics and precision engineering systems. When diamond turning brittle materials, material removal should be kept within the ductile regime to avoid subsurface damage [1, 2]. It is generally accepted that ductile regime machining of brittle materials can be accomplished using extremely low depth of cut and feed rates. Nanometric level positioning accuracy of the machine tool axes is difficult particularly at low feed rates due to friction and backlash. Friction at extremely low feed rates is highly nonlinear due to the transition from stiction to coulomb friction, and as such is very difficult to model. In order to compensate the effect of friction and backlash of a machine tool stage, a nano-metric precision three degrees of freedom (DOF) positioner is designed and fabricated as a fast tool servo. The fast tool servo, which is an independently operated positioning device, would have a small range but high bandwidth and accuracy compared to the conventional lead-screw mechanism. The nano positioner as a fast tool servo and motor-driven feedback controller were combined in order to obtain large motion with high positioning accuracy. A CMAC neural network control algorithm was applied in order to provide on-line learning and better tracking capability compared to standard PID control algorithm. The learning controller was implemented using “C” language on DSP based PC-bus board to control both diamond turning machine and nano positioner.
Published Version
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