Abstract: Fuzzy logic approach is used in this study to predict
the tractive performance in terms of traction force, and motion
resistance for an intelligent air cushion track vehicle while it operates
in the swamp peat. The system is effective to control the intelligent
air –cushion system with measuring the vehicle traction force (TF),
motion resistance (MR), cushion clearance height (CH) and cushion
pressure (CP). Sinkage measuring sensor, magnetic switch, pressure
sensor, micro controller, control valves and battery are incorporated
with the Fuzzy logic system (FLS) to investigate experimentally the
TF, MR, CH, and CP. In this study, a comparison for tractive
performance of an intelligent air cushion track vehicle has been
performed with the results obtained from the predicted values of FLS
and experimental actual values. The mean relative error of actual and
predicted values from the FLS model on traction force, and total
motion resistance are found as 5.58 %, and 6.78 % respectively. For
all parameters, the relative error of predicted values are found to be
less than the acceptable limits. The goodness of fit of the prediction
values from the FLS model on TF, and MR are found as 0.90, and
0.98 respectively.
Abstract: Fuzzy logic system (FLS) is used in this study to
predict the tractive performance in terms of traction force, and
motion resistance for an intelligent air cushion track vehicle while it
operates in the swamp peat. The system is effective to control the
intelligent air –cushion system with measuring the vehicle traction
force (TF), motion resistance (MR), cushion clearance height (CH)
and cushion pressure (CP). Ultrasonic displacement sensor, pull-in
solenoid electromagnetic switch, pressure control sensor, micro
controller, and battery pH sensor are incorporated with the Fuzzy
logic system to investigate experimentally the TF, MR, CH, and CP.
In this study, a comparison for tractive performance of an intelligent
air cushion track vehicle has been performed with the results obtained
from the predicted values of FLS and experimental actual values. The
mean relative error of actual and predicted values from the FLS
model on traction force, and total motion resistance are found as 5.58
%, and 6.78 % respectively. For all parameters, the relative error of
predicted values are found to be less than the acceptable limits. The
goodness of fit of the prediction values from the FLS model on TF,
and MR are found as 0.90, and 0.98 respectively.