Optimization of H<sub>∞</sub>-Control for Active Magnetic Bearing Suspended Rotor System
In rotor systems with active magnetic bearing (AMB) suspension, achieving stability and optimal performance often requires MIMO model-based control strategies. Tuning such a controller in the H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf>–framework and selecting suitable weighting functions typically requires manual tuning to meet performance and robustness criteria. This paper proposes a multi-objective genetic algorithm (MOGA) to optimize H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf>– control synthesis, focusing on maximizing damping, minimizing output sensitivity, and MIMO disk margin to ensure robustness and controller performance. Both simulation and experimental results demonstrate the effectiveness of the proposed approach resulting in a set of stable controllers selected based on the Pareto front and offering improved performance.
Authors
- Niko Nevaranta (ORCID: https://orcid.org/0000-0002-9766-0675)
- Tuomo Lindh (ORCID: https://orcid.org/0000-0002-9923-3650)
- Atte Putkonen (ORCID: https://orcid.org/0000-0002-1195-0090)
- Ibrahim Abubakar
- Muhammad Numan
Institutions
- Lappeenranta-Lahti University of Technology (FI)
Publication Details
- Published
- 2025-05-18
- DOI
- https://doi.org/10.1109/iemdc60492.2025.11060985
- Primary Topic
- Magnetic Bearings and Levitation Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00