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This paper demonstrates the design and simulation results of model based controllers for AMB systems, subjected to uncertain and changing dynamic seal forces. Specifically, a turbocharger with a hole-pattern seal mounted across the balance piston is considered. The dynamic forces of the seal, which are dependent on the operational conditions, have a significant effect on the overall system dynamics. Furthermore, these forces are considered uncertain. The nominal and the uncertainty representation of the seal model are established using results from conventional modelling approaches, i.e. Computational Fluid Dynamics (CFD) and Bulkflow, and experimental results. Three controllers are synthesized: I) An H∞ controller based on nominal plant representation, II) A μ controller, designed to be robust against uncertainties in the dynamic seal model and III) a Linear Parameter Varying (LPV) controller, designed to provide a unified performance over a large operational speed range using the operational speed as the scheduling parameter. Significant performance improvement is shown for robust control, incorporating model uncertainty, compared to nominal model based control.

Significant dynamic forces can be generated by annular seals in rotordynamics and can under certain conditions destabilize the system leading to a machine failure. Mathematical modeling of dynamic seal forces are still challenging, especially for multiphase fluids and for seals with complex geometries. This results in much uncertainty in the estimation of the dynamic seal forces, which often leads to unexpected system behavior. This paper presents the results of a method suitable for on-site identification of uncertain dynamic annular seal forces in rotordynamic systems supported by active magnetic bearings (AMB). An excitation current is applied through the AMBs to obtain perturbation forces and a system response, from which the seal coefficients are extracted by utilizing optimization and a priori information about the mathematical model structure and its known system dynamics. As a study case, the method is applied to a full-scale test facility supported by two radial AMBs interacting with one annular center-mounted test seal. Specifically, the dynamic behavior of a smooth annular seal with high preswirl and large clearance (worn seal) is investigated in this study for different excitation frequencies and differential pressures across the seal. The seal coefficients are extracted and a global model on reduced state-space modal form is obtained using the identification process. The global model can be used to update the model-based controller to improve the performance of the overall system. This could potentially be implemented in all rotordynamic systems supported by AMBs and subjected to seal forces or other fluid film forces.

Proper design of feedback controllers is crucial for ensuring high performance of active magnetic bearing (AMB) supported rotor dynamic systems. Annular seals in those systems can contribute significant forces, which, in many cases, are hard to model in advance due to complex geometries of the seal and multiphase fluids. Hence, it can be challenging to design AMB controllers that will guarantee robust performance for these kinds of systems. This paper demonstrates the design, simulation, and experimental results of model-based controllers for AMB systems, subjected to dynamic seal forces. The controllers are found using H∞ and μ synthesis and are based on a global rotor dynamic model in which the seal coefficients are identified in situ. The controllers are implemented in a rotor-dynamic test facility with two radial AMBs and one annular seal with an adjustable inlet pressure. The seal is a smooth annular type, with large clearance (worn seal) and with high preswirl, which generates significant cross-coupled forces. The H∞ controller is designed to compensate for the seal forces and the μ controller is furthermore designed to be robust against a range of pressures across the seal. In this study, the rotor is nonrotating. Experimental and simulation results show that significant performance can be achieved using the model-based controllers compared to a reference decentralized proportional-integral-derivative (PID) controller and robustness against large variations of pressure across the seal can be improved by the use of robust synthesized controllers.

In this paper, a method for identifying uncertain parameters in a rotordynamic system composed of a flexible rotating shaft, rigid discs and two radial active magnetic bearings is presented. Shaft and disc dynamics are mathematically described using a Finite Element (FE) model while magnetic bearing forces are represented by linear springs with negative stiffness. Bearing negative stiffness produces an unstable rotordynamic system, demanding implementation of feedback control to stabilize the rotordynamic system. Thus, to identify the system parameters, closed-loop system identification techniques are required., The main focus of the paper relies on how to effectively identify uncertain parameters, such as stiffness and damping force coefficients of bearings and seals in rotordynamic systems. Dynamic condensation method, i.e. pseudo-modal reduction, is used to obtain a reduced order model for model-based control design and fast identification., The paper elucidates how nodal parametric uncertainties, which are easily represented in the full FE coordinate system, can be represented in the new coordinate system of the reduced model. The uncertainty is described as a single column vector of the system matrix A of the full FE model while it is represented as several elements spread over multiple rows and columns of the system matrix of the reduced model. The parametric uncertainty, for both the full and reduced FE model, is represented using Linear Fractional Transformation (LFT). In this way the LFT matrices represent the mapping of the uncertainties in and out of the full and reduced FE system matrices. Scaling the LFT matrices easily leads to the amplitudes of the uncertainty parameters., Youla Parametrization method is applied to transform the identification problem into an open-loop stable problem, which can be solved using standard optimization methods., An example shows how to decouple and identify an uncertainty in the linear bearing stiffness of a reduced FE rotordynamic system.

A method for identifying uncertain parameters in Active Magnetic Bearing (AMB) based rotordynamic systems is introduced and adapted for experimental application. The Closed Loop Identification (CLI) method is utilised to estimate the current/force factors Ki and the displacement/force factors Ks as well as a time constant Τe for a first order approxima-tion of unknown actuator dynamics. To assess the precision with which CLI method can be employed to estimate AMBparameters the factors Ki, estimated using the CLI method, is compared to Ki factors attained through a Static Loading(SL) method. The CLI method and SL method produce similar results, indicating that the CLI method is able to performclosed loop identification of uncertain AMB parameters.