Model predictive control of an active magnetic bearing suspended flywheel energy

Flywheel Energy Storage (FES) is rapidly becoming an attractive enabling technology in \npower systems requiring energy storage. This is mainly due to the rapid advances made in Active \nMagnetic Bearing (AMB) technology. The use of AMBs in FES systems results in a drastic increase \nin their efficiency. Another key component of a flywheel system is the control strategy. In the past, \ndecentralised control strategies implementing PID control, proved very effective and robust. In this \npaper, the performance of an advanced centralised control strategy namely, Model Predictive Control \n(MPC) is investigated. It is an optimal Multiple-Input and Multiple-Output (MIMO) control strategy \nthat utilises a system model and an optimisation algorithm to determine the optimal control law. A \nfirst principle state space model is derived for the purpose of the MPC control strategy. The designed \nMPC controller is evaluated both in simulation and experimentally at a low operating speed as a proof \nof concept. The experimental and simulated results are compared by means of a sensitivity analysis. \nThe controller showed good performance, however further improvements need to be made in order \nto sustain good performance and stability at higher speeds. In this paper advantages of incorporating a \nsystem model in a model-based strategy such as MPC are illustrated. MPC also allows for incorporating \nsystem and control constraints into the control methodology allowing for better efficiency and reliability \ncapabilities