Design of backstepping control with CNN-based compensator for active magnetic bearing system subjected to input voltage saturation

摘要

Purpose - The stability and input voltage saturation is a common problem associated with an active magnetic bearing (AMB) system. The purpose of this paper is to design a control scheme that stabilizes the single degree of freedom AMB system and also tackle the problem of input voltage saturation in the AMB system. Design/methodology/approach - The proposed control technique is a combination of two separate control schemes. First, the Backstepping control scheme is designed to stabilize and control the AMB system and then Chebyshev neural network (CNN)-based compensator is designed to tackle the input voltage saturation when the system control action is saturated. Findings - The mathematical and simulation results are presented to validate the effectiveness of proposed methodology for single-degree freedom AMB system. Originality/value -This paper introduces a CNN-based compensator with Backstepping control strategy to stabilize and tackle the problem of input voltage saturation in the 1 -DOF AMB systems.