Work

Research on the Improvement of Feedback Linearization Control in Suspension System Countering Inductance Variation

Year: 2019

Type: article

Abstract: The safety of the magnetic levitation (maglev) train is closely related to the control performance of the suspension module. However, during operation, the working conditions vary and are vulnerable to the external disturbances. In this work, a large‐scale variation of the inductance of the magnetic levitation operation under different air gap conditions is considered, where the transfer function of the system changes nonlinearly. On the basis of the classical feedback linearization method, the algorithm of the first‐order derivative for a single equilibrium point is improved, and then a multiequilibrium point feedback linearization method subject to the variation of the inductance is derived. The proposed linearization method can decouple the inductance from the air gap dynamics in any state of levitation, thus, reducing the model error. Using a general linear controller, the closed‐loop control performance of the nonlinear hybrid excitation suspension system is run in MATLAB®. The simulation results show that the proposed method achieves good dynamic performance under various operating conditions and it improves the robust performance of the system.

Source: Mathematical Problems in Engineering

DOI: 10.1155/2019/5747812

Authors: Liwei Zhang, Yue Zhang, Chao Zhang, He Zhao

Institution: Beijing Jiaotong University

Language: English

Topic: Magnetic Bearings and Levitation Dynamics

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,550