Abstract
Taking a single magnet levitation system as the object, a nonlinear numerical model of the vehicle–guideway coupling system was established to study the levitation control strategies. According to the similarity in dynamics, the single magnet-guideway coupling system was simplified into a magnet-suspended track system, and the corresponding hardware-in-loop test rig was set up using dSPACE. A full-state-feedback controller was developed using the levitation gap signal and the current signal, and controller parameters were optimized by particle swarm algorithm. The results from the simulation and the test rig show that, the proposed control method can keep the system stable by calculating the controller output with the full-state information of the coupling system, Step responses from the test rig show that the controller can stabilize the system within 0.15 s with a 2 % overshot, and performs well even in the condition of violent external disturbances. Unlike the linear quadratic optimal method, the particle swarm algorithm carries out the optimization with the nonlinear controlled object included, and its optimized results make the system responses much better.
Highlights
Levitation control, as one of the most important techniques for electromagnetic suspension (EMS) vehicles, has been always drawing the worldwide experts’ attentions and favors [1, 2]
According to the similarity in dynamics, the single magnet-guideway coupling system was simplified into a magnet-suspended track system, and the corresponding hardware-in-loop test rig was set up using dSPACE
The maglev vehicle–guideway coupling system is composed of a magnet and elastic guideways
Summary
Levitation control, as one of the most important techniques for electromagnetic suspension (EMS) vehicles, has been always drawing the worldwide experts’ attentions and favors [1, 2]. Due to the guideway flexibility, the magnet couples with the elastic guideway in dynamics when levitating on it. The maglev vehicle–guideway coupling system is composed of a magnet and elastic guideways. The authors’ recent studies [12, 13] indicated that the introduction of guideway kinematic information into the controllers is conductive to the system stability, and they developed the full-state-feedback controllers using the linear quadratic regulator (LQR) algorithm. When the LQR algorithm is used, the controller parameters are calculated based on linearized models, which is different from the objective fact. In this work, taking the nonlinear vehicle–guideway coupling system as the controlled object, we develop a controller with the full states feedback method and calculate the output with the full dynamic information. A test rig for the elastic-track single magnetic levitation system is built, on which the effectiveness of the controlled strategy is verified
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