In this thesis, a hybrid adaptive control algorithm that controls feed rate is proposed to regulate spindle current. For this purpose, variation of steady state spindle current, time constant, and time delay were examined through experiments based on step end milling under various cutting conditions. The steady-state relationship between spindle current and feed rate can be simplified into a 1st degree equation as shown in equation. The time constant $\tau$ and time delay $t_d$ are maintained without much change in spite of various cutting conditions.
Using the above characteristics, the hybrid adaptive control algorithm composed of adjustable P control, fine control, and entry feed rate control was developed. Adjustable P control, which changes the P gain value in accordance with the cutting condition in real time, carries out large-scale control. For adjustable P control, the model of the plant was developed as a 1st order system with time delay. The P gain values obtained by the algorithm were found to have errors less than 10 %. Fine control carries out detailed control to reduce the steady state error that occurs from P control. Fine control, which complements the problems of integral feedback control, uses the static characteristic of equation. Entry feed rate control effectively decreases the peak of current produced when a tool makes contact with a workpiece. Feed rate is reduced as soon as a tool makes contact and controlled for a while by fine control.
In order to check the applicability of the hybrid adaptive control algorithm, cutting experiments were carried out under various cutting conditions, different tool diameter, and different work material. The results show that the developed hybrid adaptive control algorithm has good stability as well as excellent applicability behavior.
