Analysis and control of electromagnetic coupling effect of levitation and guidance systems for semi-high-speed Maglev train considering current direction

The guidance system is one of the important subsystems of high-speed maglev train. The active guidance of high-speed maglev train is achieved by the attraction between the guide way and the electromagnets mounted on the side of the carriage. The working characteristics of the guidance system vary according to the different guide ways and weather conditions. In the straight line, the guiding current is very small. When suffering from the bend or big crosswind, the guiding current will be very large. Therefore, the model of the guidance system has greater uncertainty, and the guidance controller is more difficult to design. This paper presents a method to make the high-speed maglev train to obtain a stable guidance ability in different conditions. The mathematical model of the guidance system is established, and the robust guidance controller is designed by H ∞ control theory. The simulation and experiment demonstrate that the high-speed maglev train using the designed guidance controller has relatively desirable performance and achieves stable guidance ability successfully. INDEX TERMS High-speed maglev train, guidance system, nonlinear control system, robust control, H ∞ .

Section: Analysis and Design Of Guidance Controller A Double Elmentioning

confidence: 99%

Research on the Active Guidance Control System in High Speed Maglev Train

Zhai

Hao

et al. 2019

“…Since the opening of the first maglev train in Birmingham, UK in 1984 [6], researches about maglev trains have been widespread in countries like Japan [7], South Korea [8], Germany and China [9], [10]. The currently operational maglev trains include the Shanghai Maglev Train, Changsha Maglev Express, and Beijing maglev S1, etc.…”

Section: Introductionmentioning

confidence: 99%

Data Driven State Monitoring of Maglev System With Experimental Analysis

Wang

Luo

et al. 2020

The reliability of levitation system plays an important role for the safe operation of maglev train. Monitoring the state of the levitation system helps make early judgement to adopt fault tolerant measurement preventing further damage. In this paper, a data-driven state monitoring problem for PEMS high speed maglev train is studied in detail. Firstly preliminaries about levitation system and problem formulation are described. Then a residual generation method based on system input/ouptput data is given. To tackle the varying operational condition problem, a multi-model switching strategy is proposed. For the non-Gaussian property of the system data, a Box-Cox transformation is adopted. The effectiveness of the proposed method is illustrated by experimental data analysis results.

“…Maglev train, which features in the vertical non-contract electromagnetic levitation system and horizontal linear induction motor (LIM) traction system, has the advantages of strong climbing and turning ability, no danger of derailment, free of friction and wearing, and less environmental impact [1]. Since the first trial in 1984 [2], researches about maglev train have been widespread in countries like Japan [3], South Korea [4], Germany and China [5], [6]. To meet different application requirements, there has been a variety of maglev trains, among which permanent magnet electromagnetic suspension (PEMS) type maglev train is an innovative maglev aiming at energy-saving and long time levitation without over heating of electromagnets [7].…”

Section: Introductionmentioning

confidence: 99%

Track Irregularity Disturbance Rejection for Maglev Train Based on Online Optimization of PnP Control Architecture

Wang

2019

Track irregularities, caused by reasons such as track deformation and installation error, are common in real maglev line. These disturbances brought by tracks exert an adverse influence on the performance of a maglev train levitation system. It takes a lot of maintenance costs and time to keep the tracks in a good condition. In another way, a disturbance rejection through a controller optimization method is proposed in this paper. First, the influences of the track irregularity disturbances on levitation performance are illustrated in detail. Then, an online optimization of the PnP control architecture method is adopted to reject the disturbances caused by track irregularities. The effectiveness of this method is verified through the MATLAB simulation. This method makes the levitation system adaptive to known and unknown time-varying track irregularities, saving time, and human resources. INDEX TERMS Maglev train, online optimization, PnP control architecture, track irregularity.