| Summary: | 博士 === 國立中正大學 === 機械工程所 === 96 === Since traditional CNC (Computer Numerical Control) machines only provide linear and circular interpolations, CAM (Computer Aided Manufacturing) systems have to generate many small linear and circular NC blocks for the parts. This approach suffers from the problems such as feedrate fluctuation, acceleration discontinuity, and a large volume of data transmission. The problems could significantly reduce machining accuracy under high-speed machining.
To achieve high-speed and high-accuracy machining, motion controller of machine tool with look-ahead and learning functions have been adopted in this dissertation. Three methodologies for motion control of machine tool are proposed. The first methodology is to propose a dynamic-based NURBS (Non-Uniform Rational B-Spline) interpolator with real-time look-ahead algorithm. The second methodology is to propose a FPGA-based motion controller. The third methodology is to propose a command-based iterative learning control (ILC) algorithm.
The dynamics-based NURBS interpolator with real-time look-ahead algorithm is proposed to generate a smooth and jerk-limited acceleration/deceleration (ACC/DEC) feedrate profile. It can detect sharp corners of a NURBS curve and adjust the feedrates at the sharp corners to improve machining accuracy. The FPGA-based motion controller is proposed to improve the overall computation performance for NURBS interpolation and servo control via its parallel computing and flexible programming power. It can complete the computation task in a stringent sampling period such as 10μsec which is much better than the traditional motion controller with the same clock frequency. The command-based iterative learning control (ILC) algorithm is proposed to compensate the friction effect and to reduce tracking errors due to servo lag. In stead of updating the voltage command, the command-based ILC algorithm updates the position command to improve tracking performance without changing the feedback-feedforward control structure of motion controller.
The proposed methodologies are evaluated on an X-Y table with a PC-based motion controller and a FPGA-based motion controller. Simulations and experiment results show that the proposed methodologies achieve high-speed and high-precision motion control and significantly improve machining accuracy as compared to traditional CNC motion controller.
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