Numerical Analysis of Tracking Performance in Machine Tools for Disturbance Forces Compensation Using PID And NPID Controller

Abstract

In modern production, machine tool precision and reliability are critical for producing high quality goods. To meet these objectives, numerous new controllers and control algorithms have been developed, taking use of technological advancements. One key problem in preserving product quality is managing internal disturbances induced by cutting and friction forces, which can have a considerable impact on finish quality. Recent research has provided novel approaches to addressing these difficulties through improved control mechanisms.This study investigates the efficiency of nonlinear proportional-integral-derivative (NPID) controllers over typical PID controls for reducing tracking errors in machining operations. The study begins with a complete system identification procedure to precisely represent the machine tool system, which is required for effective controller design. By comparing the performance of NPID and PID controllers, the study hopes to provide insights into the best strategies for accomplishing precise and efficient machining operations, resulting in higher product quality. In the MATLAB and Simulink simulations, perturbation forces were applied at frequencies of 0.2 Hz and 0.4 Hz, with spindle speeds of 1500 rpm and 2500 rpm. At 0.2 Hz, the PID controller had maximum tracking errors (MTE) of 0.09990 mm and 0.09920 mm, which corresponded to error percentages of 0.66600% and 0.66100%. At 0.4 Hz, the MTEs were 0.17600 mm and 0.17500 mm, with error percentages of 1.17300% and 1.16600%. The NPID controller, on the other hand, demonstrated MTEs of 0.09993 mm and 0.09927 mm at 0.2 Hz, yielding error percentages of 0.66620% and 0.66180%, respectively. At 0.4 Hz, the NPID controller measured MTEs of 0.17660 mm and 0.17520 mm, with error percentages of 1.17730% and 1.16800%. The Root Mean Square Error (RMSE) statistics emphasized the performance variations amongst the controllers. The PID controller had RMSE values of 0.06958 mm at 1500 rpm, 0.06960 mm at 2500 rpm at 0.2 Hz, and 0.12410 mm at both speeds at 0.4 Hz. The NPID controller had RMSE values of 0.06954 mm at 1500 rpm, 0.06956 mm at 2500 rpm at 0.2 Hz, and 0.12380 mm at both speeds at 0.4 Hz. The results show that the NPID controller consistently beat the PID controller in terms of tracking error and RMSE minimization. This shows that the NPID controller provides more precision and better performance during machining processes