Master's thesis of Engineering: Model predictive control of magnetic bearing system

Magnetic bearing systems have received much attention in the research community for the past decades. Its inherent nonlinearity and open-loop instability present challenges for controller design. This thesis investigates and designs model predictive control (MPC) systems for an experimental Active Magnetic Bearing (AMB) laboratory system. A host-target development environment of real-time control system with hardware in the loop (HIL) is used for implementation of the predictive control systems. In this thesis, both continuous and discrete time model predictive controllers are studied. In the Örst stage, local MPC controllers are applied to control the AMB system; and in the second stage, concept of supervisory controller design is then investigated and implemented.