Abstract
SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.
Abstract
The evaporator used in the pharmaceutical industry is for drug preparation.
The purpose of the evaporator in drug manufacturing is to extract the water content in
the material through the heating process. In this research, the SISO evaporator is taken,
which contains temperature as input and dry matter content as output. The
mathematical modelling of the drug preparation evaporator is done with the help of the
system identification method. Controlling and maintaining the temperature inside an
evaporator is a tedious process. In this regard, the Neural Network predictive controller
(NNPC) is designed and implemented for drug preparation. It helps to predict the
future performance of the evaporator and tune the control signal based on that. The
setpoint tracking challenge is given to the designed controller. For analysing the
performance of the controller, the error metrics, such as integral square error (ISE),
integral absolute error (IAE), integral time square error (ITSE), and integral time,
absolute error (ITAE), are employed. The time-domain specification, such as rise time,
settling time, and overshoot, is also used to better understand controller performance.
From the above two analyses, the conclusion is made that the predictive controller is
performing well in comparison with the conventional PID controller in the drug
preparation pharmaceutical industry.
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Authors:Bentham Science Books