Decoupling Control Design for the Module Suspension Control System in Maglev Train

Abstract

An engineering oriented decoupling control method for the module suspension system is proposed to solve the coupling issues of the two levitation units of the module in magnetic levitation (maglev) train. According to the format of the system transfer matrix, a modified adjoint transfer matrix based decoupler is designed. Then, a compensated controller is obtained in the light of a desired close loop system performance. Optimization between the performance index and robustness index is also carried out to determine the controller parameters. However, due to the high orders and complexity of the obtained resultant controller, model reduction method is adopted to get a simplified controller with PID structure. Considering the modeling errors of the module suspension system as the uncertainties, experiments have been performed to obtain the weighting function of the system uncertainties. By using this, the robust stability of the decoupled module suspension control system is checked. Finally, the effectiveness of the proposed decoupling design method is validated by simulations and physical experiments. The results illustrate that the presented decoupling design can result in a satisfactory decoupling and better dynamic performance, especially promoting the reliability of the suspension control system in practical engineering application.

Decentralised PI controller design based on dynamic interaction decoupling in the closed-loop behaviour of a flotation process

“…Then again, many controller design methods are applied and published such as ANN, MPC, different optimization methods, and fuzzy logic control which seems to be the successful techniques [8], [19], [20], [23]. However, when it comes to industrial application, many industries still use proportional integral (PI) or proportional integral derivative (PID) controllers [24] as one of the first developed control strategies with simple structure and well-known tuning rules. This makes them easy to maintain dominance in practical engineering applications for several decades [24], [25].…”

“…However, when it comes to industrial application, many industries still use proportional integral (PI) or proportional integral derivative (PID) controllers [24] as one of the first developed control strategies with simple structure and well-known tuning rules. This makes them easy to maintain dominance in practical engineering applications for several decades [24], [25]. Nevertheless that more advanced control algorithms have been developed, the PI or PID controllers are always preferred unless they do not give satisfactory performance [24].…”

“…This makes them easy to maintain dominance in practical engineering applications for several decades [24], [25]. Nevertheless that more advanced control algorithms have been developed, the PI or PID controllers are always preferred unless they do not give satisfactory performance [24]. Ogunnaike et al [23] emphasises important aspects of the industrial control systems implementation, which means how the actual measurements from the process to the controller and back are performed and how the necessary computations done by the controller are carried out.…”

Method for Translation and Rotation Decoupling of Test Mass in Full-Maglev Vertical Superconducting Gravity Instruments

“…As a result, the parameters of the superconducting coils are unknown, because these parameters are directly determined by the distance between the test mass and the coils. Motion decoupling cannot be carried out because of these unknown parameters even if the displacements are detected [ 17 ]. In the FM-VSGI developed by the ARKEX Company in the United Kingdom [ 18 ], to suppress cross-coupling noise, the researchers designed superconducting circuits for adjusting the sensitive axis of the test mass.…”

Dynamics of the Bogie of Maglev Train with Distributed Magnetic Forces

“…Li et al [4] derived feedback linearization controllers with acceleration feedback and disturbance observer for the maglev train with five bogies to improve robustness, who modeled the magnetic forces along one module of the bogie as two concentrated nonlinear forces. He et al [5] designed a decoupling controller for the maglev module which was modeled as a rigid beam with two concentrated forces applied at fixed positions. Even in the more detailed virtual prototype simulation model of maglev train, the levitation forces are modeled as concentrated ones [6].…”