Abstract
ABSTRACTIn this article, the software and hardware control architecture for a novel high-temperature three-phase electric air heating furnace is presented. It consists of a multiple-input single-output (MISO) nonlinear plant designed to heat air at flow rates in a range between 10 and 60 Nm3/h, from ambient temperature up to 1000 °C.A divide-and-conquer (D&C) approach is applied. It consists in discretizing the air flow rates and working temperatures in intervals where the system behaviour is considered as single-input single-output (SISO) linear plant. Process identification techniques have been used to obtain empiric models for different operation ranges of the electric furnace. The controller parameters have been calculated using the Ziegler–Nichols tuning method.The resulting output air temperature control is composed of a set of 12 PI and PID controllers. The switch among controllers as a function of air flow rates and temperatures is carried out using programming logic and gain scheduling technique, respectively. The resulting multiple controller has been tested under real conditions and the results are presented and discussed.
Highlights
Temperature control is a challenging issue in technological processes in many branches of industry
There is no comparison with a PID controller, but the results indicate that 15 out of the 20 simulated controllers have an average overshoot of 20 C
The graphical user interface (GUI) is organized into five different screens; the first one is related to the experiment management; second, third and fourth screens are displaying the information acquired from the test rig related to the air heating furnace, the preheaters and the reactor, respectively; and, the fifth screen displays the pressure and gas analysis data
Summary
Temperature control is a challenging issue in technological processes in many branches of industry. In [6], a temperature controller is developed based on the combination of fuzzy and PID control. In [8], the fuzzy adaptive control is combined with a grey prediction control to develop a grey prediction fuzzy adaptive control In these three studies, advanced controllers for furnaces without air flow heating are simulated as well as the pertinent conventional PID control for comparison purposes. The air flow used is not indicated, but the study is based on the model obtained from an open-loop step response from 30 to 55 C. This model is used to design a PID control strategy.
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