Optimization Of PID And Lead Lag Controller Parameters By Using Particle Swarm Optimization (PSO) Technique For Precise Positioning Machine Tools

Mohamed Zain, Zarina (2020) Optimization Of PID And Lead Lag Controller Parameters By Using Particle Swarm Optimization (PSO) Technique For Precise Positioning Machine Tools. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Recently, the utilization of Computer Numerical Control (CNC) machines become an essentiality in the manufacturing sec tor especially in automation sector, fabrication sector and aerospace sector. The development of technology towards Industrial Revolution 4.0 has additionally engendered advanced CNC machines that are capable of processing involute product and additionally has multiple axes to achieve an intricate design. However, as advanced as any machine , machine tool play critical part. In term of machine tool , there are immensely colossal demands on tracking accuracy , robustness, low cost, better surface quality speed and high flexibility. Nevertheless, in the presence of disturbance that leads to lack of precision positioning of machine tool and this will also contribute to inaccuracy. Besides the tracking performance of its drive system also become one of the factor that lead to in accuracy of the machine tool. Therefore this research present in uses of Proportional Integrated Derivative (PID) and Lead Lag controller for ameliorating the accuracy of the tracking performance. In this cases, the controller has been tasted on XY Table Ball -screw drive system because XY Table Ball -screw drive system is a basic structure of CNC machine. The main feature is that the smallest gain is need to be achieve when the largest error is produced. The stability of the controller was proven by using Bode Plot in Matlab Software. The controller will validate via simulation using Matlab Software. Those controller will help to compensate the disturbance force that exist during the cutting operation with spindle speed of 1500 rpm , 2500 rpm , 3500 at tracking frequency of 0.2 Hz and 0.4 Hz. The effectiveness of the proposed controller is identified based on the maximum tracking error and root mean square error (RMSE). The results of the proposed controller show a better tracking accuracy is by using Lead Lag controller. The recommendation for next research is use the other method to find the optimal parameter such as Ziegler- Nicholas (ZN).

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