Memory State Feedback Control of Maglev Vehicle Subject to Output Time-Delay Based on T-S Fuzzy Model

Abstract

Due to the characteristics of no wear, no noise and high comfort, maglev train is one of the hotspots in the field of modern vehicles. The analog signals measured by sensors are digitized by networked levitation control system. When data frames are sent to the network, network-induced delay will occur. Therefore, the time delay of the control system is inevitable. Delays can reduce the stability of the system and may lead to Hopf bifurcation. However, the vibration phenomena of maglev vehicles are closely related to the occurrence of Hopf bifurcation, which makes it possible to cause coupled vibration between vehicle and rail. Firstly, the mathematical model of maglev vehicle suspension system is established, and then it is transformed into T-S fuzzy model with global nonlinearity. Then, aiming at the time-delay phenomenon of airgap feedback, the controller with memoryless state feedback and the controller with memory state feedback are designed respectively. The simulation and experimental results show that the control law with memory state feedback can achieve stable suspension better and restrain the influence of time delay on the system.