Research And Simulation On Parameter Self-tuning PID Controller In Feeding Servo System Of NC Machine Tool

NC machine tool is an enabling foundational facility for developing high technique and new industries. Feeding servo system is one of the most important parts of NC machine tool. The performance of the tool is related to the match of the parameters of controller used in the servo system. So, how to match the parameters rapidly and effectively is a hotspot that is studied all the time.Regarding the topic "Research and Simulation about Parameter Self-tuning Proportion-Integral-Differential(PID) Controller in Feeding Servo System of NC machine Tool" as a main subject, the mathematical model of permanent magnet synchronous motor(PMSM) and the basic principles of vector control and field-oriented were studied, and then the mathematical model and simulation model of feeding servo system of NC machine tool were set up; In order to solve the problem about the parameters self-tuning of the PID controller, two intelligent control theories, fuzzy control and neural network control, were studied in great depth, then fuzzy-PID controller and Back-Propagation (BP) neural network(NN) PID controller were set up in matlab and used for controlling the feeding servo system of NC machine tool, the simulating results indicated that the two controllers made the system strong in robustness and anti-jamming performance; Nevertheless, the theories on which fuzzy controller and neural network controller are built aren't perfect enough, their arithmetic are very complex and difficult to achieve, then the optimization of D.A.desopo method was studied in the last of the thesis. With the performance index function, which is the integral of the product of error absolute value and time (ITAE), PID self-tuning controller was designed based on D.A.desopo Method and used for controlling the feeding servo system model of NC machine tool successfully, and realized the parameters of PID controller self-tuning in feeding servo system.The results of simulation indicate that the PID parameters which were optimized by way of D.A.desopo method always make the system have good performance, caring nothing about the initial PID parameters, and the method is of great value in theory and application.