Control of Magnetic Levitation System Based on NARMA-L2 Controller under Load Variation (Published)
Magnetic suspension or magnetic levitation (Maglev) is a technology that enables objects to float in the air using the action of magnetic fields, annulling physical contact and friction. This project explores the principles, modeling and control mechanisms of basic maglev system based on MATLAB simulation. A prototype model was developed and simulate based on real implementation components (using electromagnets, position sensors and a feedback control system) in other to stabilize a ferromagnetic object (ball) in mid-air. The project demonstrates clearly the feasibility of Maglev technology in applications such as high-speed transportation, vibration-free platforms and contactless bearings. The maglev system was mathematically modeled and simulated using MATLAB software. Results achieved indicate that a neural Network Based controller called Non-Autoregressive Moving Average Level 2 controller (NARMA L2) effectively stabilizes the levitated object under controlled conditions. Validation was made using Proportional-Integral-Derivative (PID) controller which indicate the effectiveness of the NARMA L2 over PID controller in maintaining equilibrium