Improving  H Control using new Robust Model Reference Sliding-Fuzzy Algorithm for High Speed Train Active Suspension System

Designing train active suspension system is one of the most important issues in high speed train industry. The
conventional passive suspension system can't provide requirements for development of high speed trains, according to
increasing speed of train. In this paper, to improvement of coupe oscillations against external disturbances from railway
irregularity and changing in coupe mass as compartment as parameter uncertainties, the hybrid model reference sliding
mode control with fuzzy regulator and the
 H method is used. The purpose of this paper is designing and comparison
between robust controllers for high speed train active suspension system using the improved sliding mode and  H
methods, this reduces the oscillations and lateral acceleration of coupe, improves train stability and passenger comfort,
while moving at high speeds. Motivation for the choice of robust approach in this paper is to improve the system
performance against presence of parameter uncertainties and model uncertainties and external disturbances. In sliding
mode method, sliding surface is defined as a proportional-derivative function of adaptation error. Then, the controller
has been designed in considering the parameter uncertainty. Defining the decision parameter and using a fuzzy system,
to improving performance quality of designed controller, is the innovation of this paper.  H robust controller has been
used in order to reduce the vibration of the train coupe.