Fadaptive Backstepping Control of Active Magnetic Bearings

A new control methodology, adaptive backstepping control (ABC), is applied to a linearized model of an active magnetic bearing (AMB). Our control objective is to regulate the deviation of the magnetic bearing from its equilibrium position in the presence of an external disturbance. The control approach is based on adaptive backstepping control, which is a combination of a recursive Lyapunov controller and adaptive laws. In this thesis, two types of adaptive backstepping methods are used. The first method is based on full-state feedback, for which all three states in the linearized AMB model (velocity, position, and current) are used to construct the control law. The second method is adaptive observer-based backstepping control (AOBC) where only one feedback signal (position) is employed. An exponentially convergent estimator is developed for the second adaptive controller to observe other states. It is proved that the adaptive backstepping controlled AMB system is asymptotically stable around the system\u27s equilibrium point. Simulation results demonstrate fast and stable system response. They also verify the effectiveness and robustness of the adaptive backstepping control methods against external disturbances and system parameter variation