Improvement of Operational Performance of Active Magnetic Bearing using Nonlinear LQG Controller

Abstract

Active Magnetic Bearing provides a means of supporting the body by magnetic forces without physical contact. Active magnetic bearings are inherently unstable systems due to the indirect proportionality between the attractive force and the length of the air gap. Thus, to stabilize the rotor position, a closed-loop control has to be implemented. The aim of this paper is to design a LQG controller and a nonlinear LQG controller to control the position of rotating shaft. First AMB is modeled using mathematical equations. LQG controller is a combination of Linear Quadratic Regulator (LQR) and Kalman Filter which is an optimal estimator.Extended Kalman Filter (EKF) is an extension of LQG which can be applied to nonlinear systems. It itself linearizes the model about an operating point. Using these controllers the magnetic bearing is capable to maintain the rotor position and in turn maintain the position of shaft connected to it.The performance of system with each controller is compared. This can be implemented using MATLAB/SIMULINK software.

Development of optimal controller design method to compensate for vibrations caused by unbalanced force in rotor system based on Nyquist diagram

“…Previously, various control design methods have been developed to design the control system of AMB. The representative design methods based on H ∞ (Cole et al., 2017; Lauridsen and Santos, 2017; Başaran et al., 2011) and linear quadratic regulator (Janardhanan and Mathew, 2015; Jastrzębski and Pyrhönen, 2012) can design the controller effectively by satisfying the Nyquist criterion in terms of spectrum and Euclidean norm. These design methods are suitable for designing controllers that stabilize the control system in a wide range of frequency.…”