A fuzzy logic controller to control nutrient dosage in a fed-batch baker's yeast process
A fuzzy logic controller designed to control glucose feeding in a fed-batch baker's yeast process is presented. Feeding is carried out in portions and the controller determines the time at which glucose should be added and computes the size of the portion to provide the maximum glucose uptake rate. Moreover, the controller detects and prevents the occurrence of overdosage. The experimental results indicate that yield and specific growth rate obtained with the controller approached 55% and 0.13 h−1, respectively.
An adaptive fuzzy logic controller using the respiratory quotient as an indicator of overdosage in the baker's yeast process
The baker's yeast process was optimised with a fuzzy logic controller, which is capable of detecting (with the respiratory quotient as indicator) and eliminating overdosage. The controller was developed to enable automatic modification of the set value for the respiratory quotient according to glucose concentration in the broth. With this controller, a cell yield of 55% (w/w) from glucose and a maximum specific growth rate of 0.16 h−1 were obtained.
Prediction of a representative point for rail temperature measurement by considering longitudinal deformation
Monitoring rail temperature is very important for determining the safe running speed of trains and to prevent buckling. In general, the maximum variation of the internal rail temperature can be >7 ℃ depending on the point of measurement. However, there is as yet no sufficient information about how to predict the measurement point to represent the thermal deformation due to temperature distribution. In this study, the authors report a new point, called the representative measurement point, at which the rail temperature can be measured. This point considers the average deformation of the rail through structural analysis by adopting experimental and actual rail temperature data. The authors designed and installed a measurement system similar to an actual rail environment. Using the system, various data were acquired (internal/surface rail temperature and weather data) for 10 months. On the basis of these data, an analysis was done to calculate the average deformation point through thermal analysis. Finally, the representative measurement point was proposed as the position at which the average deformation point converges regardless of weather or seasons. The authors believe that the method described herein is advantageous in that it could be used in a high-accuracy temperature-monitoring system and for predicting thermal deformation and buckling.