In this work a robust current control strategy is developed in order to counteract the imbalance forces of a rotor which is levitated by an active magnetic bearing (AMB) system. A model-based and physics based design procedure for active imbalance rejection is presented, which solely derives from the configuration of a given AMB system such as physical parameters, rotational speed and controller capacity. An output feedback controller is developed which eliminates the synchronous vibrations by applying synchronous forces at the AMB force locations. The controller is developed by making use of the sliding mode control (SMC) formalism. Within the boundary layer the controller is equivalent to a MIMO proportional-derivative (PD) controller with an output reference trajectory. The active vibration suppression forces are obtained as a control rule, which implement the tracking of a reference trajectory in the output space. The time-varying reference trajectory is obtained as the particular solution of a first-order linear ODE with periodic forcing function, where the periodic forcing function is the generalized synchronous imbalance excitation forces. For a given AMB system and known unbalance, the achievable rotational speeds such that the AMB system can be operated, are derived. Within the boundary layer, which is the main operation range, the MIMO PD controller is parameterized by the rotational speed.
- Dynamic Systems and Control Division
Robust Active Imbalance Rejection for Active Magnetic Bearing-Rotor Systems Available to Purchase
Yunt, K. "Robust Active Imbalance Rejection for Active Magnetic Bearing-Rotor Systems." Proceedings of the ASME 2016 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Mechatronics and Controls in Advanced Manufacturing; Modeling and Control of Automotive Systems and Combustion Engines; Modeling and Validation; Motion and Vibration Control Applications; Multi-Agent and Networked Systems; Path Planning and Motion Control; Robot Manipulators; Sensors and Actuators; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamic Controls; Vehicle Dynamics and Traffic Control. Minneapolis, Minnesota, USA. October 12–14, 2016. V002T22A004. ASME. https://doi.org/10.1115/DSCC2016-9697
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