Research On Optimization Of CNC Milling Parameters And Fuzzy Adaptive Control

In automated CNC machining,companies or factories need to consider machining efficiency and machining cost,so it becomes critical to coordinate the design of machining solutions and selection of cutting parameters.In this paper,the maximum productivity,minimum production cost and tool durability are used as the objective functions,and the milling speed,milling depth,milling width and feed per tooth are used as the optimization parameters,and the simulation calculation model is built based on the Non-Dominated Sorted Genetic Algorithm-2(NSGA-2)multi-objective parameter optimization method.Through the multi-objective decision process,the optimal solution of the objective function is found.Finally,by comparing the simulation experiments with the results of the objective function calculated by the empirical parameters,the machining efficiency achieves a large improvement,which proves that the studied algorithm is feasible and correct.In the machining process,the adaptive control algorithm can automatically adjust the uncertainty factors existing in the servo system of CNC machine tools and maintain excellent regulation even in the face of randomly changing working conditions and sudden changes in the internal parameters of the CNC system.However,the traditional adaptive control system needs to adjust more parameters and also needs to establish an accurate mathematical model,so the convergence speed is slow and the anti-interference is not strong.Therefore,improving adaptive control by combining more control methods is an efficient and reliable development direction.In this paper,we analyze and study three different controllers,including PI control,sliding mode control and self-turbulence control,for the speed and position of servo systems.On this basis,the compound adaptive control algorithm formed by combining with fuzzy control for improved adaptive control is used to regulate the uncertainties in the CNC system.In order to verify the rapidity and accuracy of the composite adaptive control,a simulation model of Permanent Magnet Synchronous Motor(PMSM)control system is established,which includes different control methods such as fuzzy PI control,fuzzy sliding mode control and fuzzy self-rejecting control.By comparing the simulation analysis with the traditional PMSM control system,the improved composite adaptive control system shows excellent control performance in terms of response speed,immunity and steady-state error,and can meet the control requirements of the servo system.