AN EFFICIENT CONTROLLING SYSTEM FOR MAINTAINING THE TEMPERATURE OF CONTINUOUS STIRRED TANK HEATER

Abstract

Designing an efficient controller for controlling and
maintaining the Continuous Stirred Tank Heater (CSTH) is one of
the demanding and crucial process in recent days. For this reason,
different controlling strategies such as Proportional Integral
Derivative (PID), Proportional (P), and Fuzzy Logic Control
(FLC) are developed in the traditional works. It mainly focuses to
control the tank based on its temperature level, but it failed to
reduce the error and settling time. The increased settling time can
affect the chemical reactions inside the tank, so it must be
maintained at certain level. Thus, this work aims to develop an
optimal strategy, namely, Tri-Energy based Neural Network
Controller (TENNC) for controlling and maintaining the
temperature of CSTH. It is developed based on the material
balance and energy balance of the tank and jacket. In this design,
the output of system is compared with the input of system for
estimating the error value, based on this, the controller obtains the
desired output. Moreover, it focused to increase the efficiency and
reduce the operating cost of the controller. The major benefits of
this design are, it enabled an automated control system with
increased efficiency and reduced man power. In simulation, the
traditional PID, PC and FLC controlling strategies based on the
measures of time, amplitude, and error. The results showed the
effectiveness of the proposed controller design.