Disturbance force estimation for CNC machine tool feed drives by structured neural network topologies

摘要

This paper presents efficient structured neural network for the feed drives of CNC vertical machining centers so as to estimate the milling forces accurately. The proposed estimation paradigm is known to have significant limitations when one of the feed drive motors is stalled due to strong friction in guideways. Thus, this paper proposes a general estimator topology, which exclusively utilizes model-reference based estimation scheme to overcome this limitation.