On the performance enhancement of self-tuning adaptive control for time-varying machining processes

This paper investigates efficient approaches to improve the performance of a self-tuning adaptive control system for time-varying machining processes. The milling process is a typical time-varying system because of variations of the cutting conditions, e.g., the change of cutting depths and variation of the cutting materials. On the other hand, the milling processes are considered as typically non-minimum phases since one or more zeros of discrete-time models of milling processes may be located outside the unit circle. In this paper, an efficient method, using the pole assignment method, is presented to design a self-tuning adaptive controller for time-varying and non-minimum phase milling processes, and an effective method to select appropriate design parameters in order to improve its performance has been proposed. Its effectiveness has been verified in experiments on controlling milling processes with varying cutting depth. The experimental results illustrate that improved control performances can be obtained using the appropriate design parameters selected according to the principles and criteria presented here.