This paper discusses the issue of adjusting the temperature of steam exiting a superheater in an environment that is affected by perturbations due to the sudden and significant fluctuations in the inlet steam temperature. Using the superheater at the Magnitogorsk Iron & Steel Works as an example, we highlight that a slow response to the aforementioned perturbations in the systems that adjust for deviations leads to undesired rises and drops in the outlet steam temperature. We review the current suggestions on adjusting the temperature of steam exiting a superheater and determine the main reasons behind the drop in adjustment quality. These reasons are related to a significant lag and the variability of the control object’s features, which make preemptive perturbation control difficult. In order to control such environments, we propose a system with two degrees of freedom, which combines a proportional-integral controller and a fuzzy logic-based controller. In the system that we are proposing, the changes in the controlled parameter (depending on the input value) are adjusted within the main loop that has a standard controller and negative feedback, while the perturbations are removed by using a secondary loop, which also has negative feedback, a fuzzy logic-based controller, and a simulation of the object without the component that accounts for the lag. For situations when the information on the object’s features is precise, we describe the specifics of the loops’ interaction, specifically in cases when the task processing loop does not respond to the perturbations in the inlet steam temperature, thus allowing for setting up the loops’ controllers separately. In situations when the inlet steam temperature is experiencing perturbations, the impact of the lag on adjustment quality only becomes evident when the trajectory of the transition process shifts along the time scale by a lag value, which is completely in line with the Smith predictor principles. The system is focused on synthesizing the fuzzy logic rules and refining the parameters of the simulation used for adjustment purposes, based on the results of automated computer-aided control simulation. We propose a structural modification of the control system that makes it possible to compensate for any residual control errors caused by the non-linear structure of the fuzzy controller; this reduces the number of requirements for those set-up parameters where the value selection is based on the needs of simulation modeling, which requires a lot of computing resources. We demonstrate the results of simulation experiments that compare the efficiency of control using the system suggested and the efficiency of control using a system with a standard controller only. The computer simulation was performed in the MATLAB Simulink environment. We reaffirm that a combined control system performs better when adjusting the steam temperature.
Boosting GWs in supersolid inflation