Application of the Dynamic Iterative Learning Control to the Heteroplanar Active Magnetic Bearing. Issue 2 (2020) - Hladowski, Lukasz; Mystkowski, Arkadiusz; Galkowski, Krzysztof; Rogers, Eric; Chu, Bing
Abstract: Heteroplanar active magnetic bearings have numerous applications, where one example is a high-temperature gas-cooled reactors. Rotor imbalance, however, may cause problems for critical parts of the system in the form of repetitive periodic vibrations. This is known problem and periodic component extraction is widely used in active magnetic bearing unbalance control laws. More recently, iterative learning control has been considered as an alternative and this paper gives new results on this approach. In particular, a new control law in the 2D systems setting is developed and the results of a simulation based study using the model of a test rig are given, where such a study is an essential step prior to experimental validation.