Fuzzy Observer-Based Control for the Traction Dual Rectifiers in High-Speed Train

This paper proposes a fuzzy-observer-based control algorithm to improve the efficiency of traction dual rectifiers of high-speed trains and address the low-frequency oscillation issue induced by the interaction of the DC-link voltage controller with the traction dual rectifiers circuit parameters. The proposed observer checks for the errors in the system model by estimating the system premise variables, and the fuzzy controller then accurately compensates the estimated variables. The method is deduced from the Takagi-Sugeno fuzzy logic model, which is described by a class of IF-THEN fuzzy systems. Fast computation with high precision is what makes them superior to proportional-integral-derivatives controllers. Their capability to deal with nonlinearity in time-varying systems makes them a suitable choice for traction dual rectifier control. The simulation model is formed in SIMULINK, and the waveforms are checked with a conventional fuzzy controller, predictive control, and conventional proportional-integral control. The proposed method can achieve better performance, such as fast transient, more damping, and small overshoot. Furthermore, the method can maintain stability when the system is subjected to external disturbance. In the end, hardware-in-the-loop experiments are performed to validate the proposed control algorithm.