Noncircular cutting on a lathe using tool position and differential motor current

• Published in: International journal of machine tools & manufacture 1999-02, Vol.39 (2), p.209-227
• Main Authors: Hwang, C.L., Shi, Y.D.
• Format: Article
• Language: English
• Subjects: Applications; Applied sciences; Cutting; Engineering techniques in metallurgy. Applications. Other aspects; Errors; Exact sciences and technology; Fuzzy control; Machine tools; Mathematical models; Mechanical engineering. Machine design; Metals. Metallurgy; Neural networks; Neural-network modeling; Noncircular cutting on lathe; Nonlinear control systems; Servomotors; Surface roughness
• ISSN: 0890-6955; 1879-2170
• DOI: 10.1016/S0890-6955(98)00035-2

In this paper, noncircular cutting on a lathe (NCL) using the signals of tool position and differential motor current is developed. First, a neural-network is used to learn a weighted combination of tool position and differential motor current of a voice coil servomotor system (VCSS). The differential motor current is achieved from the difference between motor current under real cutting and that under air cutting. Then a nonlinear inverse control based on the learned model is designed to obtain an acceptable cutting error. Although the nonlinear inverse control is accomplished from the consideration of tool position under real cutting, its performance cannot be ensured as the NCL is subjected to the uncertainties (e.g. noise, different cutting conditions, aging of system components). Under these circumstances, a fuzzy sliding-mode control is then synthesized with the previous nonlinear inverse control to reduce the cutting error. The experimental results of NCL using the proposed control including profile error of finished workpiece and surface roughness of finished workpiece, are better than those without the consideration of motor current.