Optimized Positioning Control for Cutting Force Compensation in Milling Operations

Ramu, Visnu (2025) Optimized Positioning Control for Cutting Force Compensation in Milling Operations. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

This research presents the design, implementation, and evaluation of a Super-Twisting Sliding Mode Controller (STSMC) for precise cutting force disturbance compensation in a milling machine drive system. Addressing the limitations of conventional PID-based controllers in high-precision milling, the STSMC was developed to enhance tracking accuracy and suppress chattering under nonlinear and dynamic disturbance conditions. A detailed system identification process, utilizing experimental data and frequency response analysis, was performed to model the ball screw-driven axis accurately. The STSMC was then formulated in MATLAB/Simulink, incorporating both a switching surface and nonlinear control laws to enable robust trajectory tracking. To improve performance, three optimization algorithms, Grid Search, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) were employed to fine tune the controller gains L andW. Real world disturbance data collected under varying depths of cut (0.6 mm, 1.0 mm, and 1.4 mm) at a spindle speed of 2720 rpmwere used to simulate realistic operating conditions. Controller performance was evaluated using tracking error, RMSE, ITAE, FFT analysis, and classical frequency-domain methods such as Bode and Nyquist plots. Results show that optimization methods, particularly PSO, significantly outperformed manual tuning, demonstrating superior robustness, faster convergence, and improved error suppression. The findings validate the integration of intelligent control and optimization strategies for next-generation precision milling applications.