Self-Tuning Control of Cutting Force for Rough Turning Operations

Abstract

Considerable developments have taken place in recent years in the versatility and sophistication of computer numerical control (CNC) controllers. Machine tool control schemes have not, however, advanced to the same extent. Control of the metal cutting process has long been advocated as a goal to pursue to improve productivity, but progress has been slow. This paper introduces a simplified generalized minimum variance approach to self-tuning which shows promise for the adaptive control of metal cutting. An experimental rig is described and the results of tests to adaptively control the vertical component of cutting force during rough turning operations by manipulating the feedrate are presented. A simulation of the rig was also developed and used as an initial testbed for adaptive control techniques.