Research on Magnetic Suspension Control Scheme Based on Feedback Linearization under Low Track Stiffness

Abstract

The problem of vehicle–guideway coupled self-excited vibration is common in maglev train systems, which has a serious impact on the stability of maglev trains. The lower the track stiffness, the more likely it is to occur, the greater the harm to the maglev system, and the greater the difficulty in suppressing the vibration. To solve this problem, many conventional control schemes rely on the estimation of electromagnetic forces. However, considering the magnetic leakage flux in the suspension air gap and other reasons, the empirical electromagnetic force model is inaccurate, which increases the difficulty of suspension control under low track stiffness. Therefore, a more accurate electromagnetic force model based on least squares fitting is proposed in this paper, which can estimate the electromagnetic force more accurately without increasing the computational cost. On this basis, a control scheme based on feedback linearization theory was designed, and the control effect was tested on an experimental platform with low track stiffness. The experimental results showed that the proposed control scheme could achieve stable suspension with low track stiffness and could effectively solve the vehicle–guideway coupled vibration problem with a strong anti-interference ability. The research in this paper is of great significance for solving the problem of vehicle–guideway coupled vibration under low track mass/stiffness, which is believed to be used in the light-weight girders in the next generation of commercial maglev systems. This work also has an important reference value for suspension control algorithms based on electromagnetic force feedback.

A Review of Levitation Control Methods for Low- and Medium-Speed Maglev Systems

“…This method involves substituting the rated operating point air gap with a measurable air gap and disregarding the impact of nonlinear factors, such as leakage inductance. Zhang et al [46] adopted the feedback linearization method in a vehicle-bridge interaction system to establish a linearized levitation system model and designed a levitation control method. To validate the performance of the proposed method, experiments were conducted on a levitation platform characterized by low track stiffness.…”

“…The proposed controller was verified on a full-scale Internet of Things (IoT) maglev train system at Tongji University. In addition, sliding mode robust adaptive control [109], robust control [71], feedback linearization control [46], double loop PID considering control gain perturbation [86], and GA tuned super-twisting-SMC (ST-SMC) [97] have been proposed to suppress the vibration of the coupling system.…”

“…However, a small deformation of the guideway cannot be eliminated for precise controller design. Thus, the electromagnetguideway coupling model is established [45][46][47][48][49], where the guideway is simplified as a Bernoulli-Euler beam. This simplification is justified because the length of the guideway is significantly larger than its other dimensions.…”

Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller

“…In some cases, the control parameters calculated by simple models cannot be fully applicable to the actual vehicle models, and the suspension control of the complete vehicle-track-bridge vibrations is more complex than the single-electromagnet control. The effects of vehicle-guideway coupling vibrations on the stability of maglev trains become stronger with lower track stiffness, leading to higher possibilities of coupling vibrations and more difficulties in vibration suppression (Zhang et al, 2022). Considering the increasing priority given to the construction of high-speed maglev trains, establishing accurate models for maglev train-guideway coupling vibrations and investigating highly effective suspension control technologies are significant.…”