Novel Online Speed Profile Generation for Industrial Machine Tool Based on Flexible Neuro-Fuzzy Approximation

作者：Rutkowski Leszek^*; Przybyl Andrzej; Cpalka Krzysztof

来源：IEEE Transactions on Industrial Electronics, 2012, 59(2): 1238-1247.

DOI：10.1109/TIE.2011.2161652

• Control systems
• fuzzy neural networks
• intelligent control

Reference trajectory generation is one of the most important tasks in the control of machine tools. Such a trajectory must guarantee a smooth kinematics profile to avoid exciting the natural frequencies of the mechanical structure or servo control system. Moreover, the trajectory must be generated online to enable some feed rate adaptation mechanism working. This paper presents the online smooth speed profile generator used in trajectory interpolation in milling machines. Smooth kinematic profile is obtained by imposing limit on the jerk-which is the first derivative of acceleration. This generator is based on the neuro-fuzzy system and is able to adapt online the current feed rate to changing external conditions. Such an approach improves the machining quality, reduces the tool wear, and shortens total machining time. The proposed trajectory generation algorithm has been successfully tested and can be implemented on a multiaxis milling machine.

• 出版日期2012-2