Advanced control strategies for Servo motors: Analysis of PID, FUZZY-PID and MPC with cuk converter integration

This research paper presents a comparative study on speed control techniques for servo motors in industrial and automation applications. The three techniques under investigation are the conventional PID control, Fuzzy PID control, and Model Predictive Control (MPC). Each method's integration with a Cuk converter for non-isolated voltage conversion and high efficiency is explored. The paper begins with the development of a mathematical model of the servo motor system to facilitate fair comparison among the three control strategies. Design considerations for the Cuk converter and tuning parameters for each control technique (PID, Fuzzy PID, and MPC) are thoroughly discussed. MATLAB Simulink is utilized for the simulation and analysis of the proposed systems under various operating conditions. The simulation results showcase the performance of each speed control approach, including accuracy, stability, and dynamic response. The study reveals valuable insights into the strengths and weaknesses of each control technique when used in conjunction with the Cuk converter for servo motor speed control. By comparing PID, Fuzzy PID, and MPC approaches, this research contributes to a comprehensive understanding of advanced speed control methodologies, aiding in the selection of the most suitable strategy for specific servo motor applications. The findings are expected to pave the way for further advancements in industrial automation and contribute to the optimization of servo motor systems across various industries.