Model reference adaptive control of machine tool design real-time estimation and control

Machining processes are unpredictable. Changes in machining parameters, such as material properties and cutting conditions, may cause deterioration of system performance and most important system stability. This problem can be solved if the process parameters were estimated on-line, and used by the controller, to accurately decide on necessary changes that maintain stability and achieve optimal performance.; A mathematical model is derived to predict tool chatter and cutting force in milling processes. Parameters involved in the mathematical model are estimated under changing machining conditions by an on-line estimation algorithm. A model reference series-parallel estimation strategy is used. By applying the proposed method, variations in the machining process are compensated for by subsequent changes in both the feed velocity and the spindle speed. Changes of feed velocity and spindle speed are carried out by a model reference parallel-parallel adaptive control strategy. The adaptive control strategy modifies the spindle speed and feed velocity to minimize tool chatter, keep the cutting force at an optimal level, and maintain stability of the whole system. The strategy of estimation and adaptation has been implemented on a computer controlled milling machine.; By applying the proposed estimation and adaptation policy, the controller effectively compensated for sudden changes in the cutting process while maintaining optimal performance. Moreover, machining performance being function of machining parameters, the simultaneous change in the feed velocity and spindle speed improves the performance of the machining process, more so than one parameter change.