Composite materials provide distinctive advantages in manufacture of advanced products because of attractive features such as high strength and light weight. They are easily damaged unless machining is performed properly. A typical damage is delamination during drilling when the drilling force exceeds a threshold value at critical stages, e.g. at the entry and the exit of a drill bit. This project is concerned with the modeling of machining processes of composite materials and the development of model-based intelligent control strategies for machining of such materials by analysis, simulation and experiments. The intelligent controller must minimize delamination while minimizing the time required to make each hole. The primary controlled variable is the drilling force. The force feedback loop gain and the reference force must be adjusted as functions of the drill position to ensure that delamination and excessive machining time are avoided. A series of experiments have been conducted to develop a mathematical model, which relates cutting parameters to measurable quantities such as the drilling force and torque, and initiation of delamination. A linear dynamic model is applied to predict the drilling force as a function of the drill feedrate. An adaptive strategy is used to estimate the linear model parameters in real time so that it may be applied to the whole drilling process even under the situation of large variation of operation range. A supervisory controller structure is proposed to achieve this control objective. An adaptive predictive control strategy is added to the supervisory controller to improve the performance. (Ye Sheng, October 1999)