This thesis studies various linear and non-linear control approaches for active railway
suspensions. The aim of the study is to improve the system performance of active
secondary suspensions in response to different track features. The primary motivation
for active suspension on railway vehicles is to improve suspension performance and
thereby run faster or provide a better ride quality. The problem of discriminating
between the random track and deterministic track input is a fundamental problem for
the design of active secondary suspensions on railway vehicle. The basic requirement
of an active suspension system is to improve the ride quality without increasing the
suspension deflection unacceptably when the vehicle negotiates on both straight track
and deterministic track features.
This thesis presents and compares different control strategies of active suspension
systems for railway vehicles. Firstly, a number of linear approaches for filtering the
absolute velocity signal are theoretically examined in order to optimise the trade-off
between the random and deterministic input requirements. What can be achieved with
linear filters is initially determined. This is quantified by the degradation in the
straight track ride quality needed to restrict the maximum deflection to an acceptable
level as a vehicle traverses the transition to a typical railway gradient, and a range of
filter types, frequencies and absolute damping rates are assessed in order to explore
the boundary of what can be achieved through linear means. Secondly, some nonlinear
Kalman-Filter methods are investigated to further improve the suspension
performance. Finally, a comparison between linear and non-linear strategies is
studied
