A Preliminary Study of Model Predictive Control of Permanent Magnet Assisted Maglev System
8th Global Power, Energy and Communication Conference, GPECOM 2026, Naples, Italy, 3 - 05 June 2026, pp.160-165, (Full Text)
- Publication Type: Conference Paper / Full Text
- Doi Number: 10.1109/gpecom70462.2026.11578643
- City: Naples
- Country: Italy
- Page Numbers: pp.160-165
- Keywords: 3DOF control, magnetic levitation, model predictive control
- İstanbul Ticaret University Affiliated: Yes
Abstract
Zero-friction operation and low noise characteristics make magnetic levitation (Maglev) systems highly desirable for advanced motion control applications. However, controlling these platforms remains challenging due to their open-loop instability and strong nonlinear dynamics. While conventional PID controllers often struggle to satisfy strict performance criteria under such conditions, Model Predictive Control (MPC) offers a systematic way to handle system constraints. This study presents a decoupled MPC architecture to stabilize and track trajectories for a 3-Degree of Freedom (DOF) Maglev system. Instead of MIMO, the vertical (z), roll (α), and pitch (β) axes are governed by three independent MPC loops, called centralized control approach. A 4 × 4 control allocation matrix then translates these virtual control efforts into physical electromagnet currents, effectively minimizing cross-coupling. The internal prediction models for the controllers rely on a linearized state-space representation derived at a 5.5 mm nominal air gap. MATLAB/Simulink simulations validate the proposed architecture, showing distinct improvements in reference tracking and disturbance rejection when compared to a baseline classical I-PD controller.