Optimised Nonlinear Controller for Disturbance Force Compensation in Ball-Screw Drive System

Wong, Jia Yang (2024) Optimised Nonlinear Controller for Disturbance Force Compensation in Ball-Screw Drive System. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

In this research project, the focus was on exploring mechanical drive systems, specifically the Ball-Screw Drive system, alongside Rack and Pinion Drive and Linear Direct Drive System. Addressing the challenge of disturbance forces, particularly cutting forces, nonlinear feedback control methodswere emphasized. The aimwas to develop and optimize aNonlinear PID controller (NPID) tailored for cutting force compensation within the Ball-Screw Drive system, using optimization algorithms such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) to find optimal tuning parameters. Analysis at different spindle speeds revealed PSO’s significant error reduction improvements, achieving a 0.629% enhancement in tracking error, 1.014% in ITAE results, and 0.455% in RMSE results without compensation. However, GA proved most stable and optimal for compensating cutting forces at various speeds, followed by ACO. Further scrutiny highlighted GA’s effectiveness in balancing search techniques, contrasting with PSO and ACO’s occasional instability. This underscores the importance of optimization techniques in refining NPID controller parameters for improved precision and accuracy in machining operations, with potential applications in systems with nonlinear dynamics.In short, the Genetic Algorithm (GA) has achieved all the objectives of this research by showing good error reduction and cutting force compensation.