Adaptive learning control of sculptured surface machining based on NN and GA

The adaptive learning control for on-line optimization of sculptured surface machining process was presented. An adaptive learning neural network (NN) is used for the nonlinear relationship between process input and process state to optimize the cutting parameters by genetic algorithms (GA). It consists of a machine tool with open-architecture CNC, multi-sensors, real-time controller, learning model and optimizing model. The experimental results show that the proposed system can avoid chatter vibration and achieve high quality and high efficiency.