State-Constraints Adaptive Backstepping Control for Active Magnetic Bearings With Parameters Nonstationarities and Uncertainties

Abstract

In this article, a state-constraints adaptive backstepping control (ABC) strategy is proposed and presented to accomplish precise rotor displacement control for a kind of nonlinear active magnetic bearing (AMB) system considering the presence of parameters nonstationarities and uncertainties. Since the control properties of the AMB system is strong nonlinear, uncertain, and nonstationary owing to external disturbance and the variation of geometry and material dependent on operation condition, a nonlinear AMB system model with switched parameters is established to describe the AMB dynamics. Subsequently, a nonlinear ABC algorithm is designed for the rotor position control of radial magnetic bearing. For the purpose of making the rotor displacement confined to a prescribed range in consideration of physical limitations and security concerns, barrier Lyapunov function (BLF) is founded to construct the adaptive backstepping controller. Thus, the proposed BLF-based adaptive backstepping controller is able to restrict the position states without exceeding the prescriptive constraint spaces and then to improve the system performance. Additionally, the extended development for n-order controller and the stability proof is given in this article as well. Simulation and experiment results demonstrate the effectiveness and the potential application of the proposed control approach.