Development of Adaptive Control for Railway Vehicles Braking System: Case study for AA-LRT
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Date
2017-06
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Addis Ababa University
Abstract
Since railway transport is one of the main modes of land transportation, stopping rail vehicles at
stations is the eventual routine of the service. The critical challenge in railway vehicles braking
system is accurately limiting train braking distance under different operation conditions, since
the train movement is on metal rail with low adhesion coefficient relative to road lines. Accurate
estimation of the braking distance will allow trains to be spaced closer together, with reasonable
confidence that they will stop without colliding each other. Therefore, a dedicated braking
control system is intensely required, which can enhance fast and reliable control actions.
Currently trams used in Addis Ababa Light Rail Transit equipped with Proportional and Integral
controller based closed loop Variable Voltage Variable Frequency drive system. The
conventional Proportional and Integral controller with fixed gain and normal feedback is unable
to achieve desired braking control performance under different disturbances.
The motive of this work is to investigate the existing train braking control system and develop a
new adaptive control mechanism that can handle disturbances and gives adequate control
response. Model reference adaptive controller tunes a given proportional and integral controller
in such a way that error between the speed command and actual speed will be minimized to
improve braking control action. A well-known Massachusetts Institute of Technology (gradient)
adaptation algorithm is used to develop the proposed adaptive control system. The existing and
the newly developed control systems are compared using MathLab environment.
According to the simulation results for disturbance handling model reference adaptive system
has 1.504 % overshoot and 1.876 rad/sec speed error which is much smaller than proportional
and integral controller with 92.7 % overshoot and 6.26 rad/sec speed error. Also model reference
adaptive controller significantly improved braking distance and time around 25% more than
proportional and integral controller by giving fast response.
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Keywords
Addis Ababa Light Rail Transit (AA- LRT), Proportional and Integral controller (PI), Variable Voltage Variable Frequency (VVVF), Model Reference Adaptive Control (MRAC), Massachusetts Institute of Technology (MIT)