Robust adaptive control of machining operations

Machining parameters are often selected for worst-case cutting condition scenarios, based on the experience of operators, in order to avoid machine failures. This significantly limits the productivity of traditional computer numerical controlled (CNC) machining operations. Machining operations are especially susceptible to environmental noise and are also highly non-linear due to the complex nature of cutting operations. In order to improve the productivity and accuracy of machining operations in milling, an adaptive control algorithm can be used to provide optimal machining parameters by adapting to changes in cutting conditions such as depths of cut and disturbances. In this paper, a discrete-time sliding mode control algorithm is designed to maintain a desired peak cutting force in the presence of parametric uncertainty for a time-varying slot milling process. The controller, which is designed using conventional and decoupled disturbance estimation method, provides optimal cutting parameters automatically so that the desired productivity and constrained finished surface can be achieved. The models of the cutting process and machine dynamics, including parametric uncertainty, are also presented. The simulated cutting process and control results indicate that the discrete-time sliding mode control with parameter estimation performs well with high robustness.