Study of the swelling pressure of coals and coal charges in the coking process

The maintenance of furnaces is one of the most important problems for by-product coke production. Swelling pressure is one of the least studied factors affecting the lining of coke furnace walls. The results of studies of the swelling pressure of PJSC “Koks” feedstock coal are presented in this paper. Research has been carried out to identify the dependence of the swelling pressure on the coal quality indicators, estimated during the incoming control of the central plant laboratory of PJSC “Koks”. The plastic properties of PJSC “Koks” feedstock coals were studied using Gieseler plastometer. The relationship between the swelling pressure and the maximum coal fluidity is revealed.

An improved constrained predictive functional control for industrial processes: A chamber pressure process study

An improved constrained predictive functional control for the pressure of a coke furnace is proposed in this article. In conventional constrained model predictive control, a quadratic programming problem is usually constructed to replace the original cost function and constraints to obtain the optimal control law. Under strict constraints, however, the relevant quadratic programming problem may have no feasible solutions. Unlike conventional approaches, there are several effective relaxations introduced for the constraints in the proposed scheme; then, a new cost function and the new transformed constraints are generated. With the improved constraints and cost function, there are always acceptable solutions for the quadratic programming problem under various conditions. The validity of the presented constrained model predictive control algorithm is evaluated through the regulation of the pressure of the coke furnace.

An improved constrained dynamic matrix control for temperature in an industrial coke furnace

In order to derive the feasible control law of the constrained model predictive control scheme, quadratic programming has been introduced as an effective method. It is known that the typical performance index for model predictive control strategies under various constraints can be converted into a standard quadratic programming problem; however, there may be no feasible solutions for the corresponding quadratic programming problem when the working conditions are too bad or constraints are too rigorous, the real-time control law cannot be updated and the system performance may be deteriorated. To cope with such problems, an improved quadratic programming problem in which relaxations are employed to increase the possibility of successful solutions is proposed for the constrained dynamic matrix control approach in this paper. By adopting the introduced relaxations, more degrees of relaxations are provided for the optimization process under the case of over-constrained, such that the control law is easier to yield. Case study on the temperature regulation of the coke furnace demonstrates the validity of the improved quadratic programming structure–based dynamic matrix control strategy. Simulation results show that the proposed scheme yields improved control performance.