A Multi-Model Robust Control Design for Uncertain AMB Systems

Modern turbomachinery equipped with active magnetic bearings (AMBs) requires sophisticated controllers to ensure safe and efficient operation. These controllers often rely on complex plant models refined through frequency-domain measurements. However, accurately identifying rotor resonances and anti-resonances can be challenging due to noise, limited rotor-mode observability and controllability, and interference from stator excitations. To address these issues, a robust updating method has been employed to iteratively refine uncertain stiffness parameters and generate multiple rotor models that account for measurement uncertainties. These models enable the design of robust controllers capable of managing a wide range of uncertainties, ensuring reliable performance under real-world conditions. This study reports the experimental results derived from a collaboration with an industrial partner, where the proposed technique was successfully applied to a turboexpander for oil and gas applications. The experimental validation highlights the method practicality and effectiveness in managing uncertainties, making it a valuable tool for industrial applications.