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Modelling and intelligent control of electroslag remelting of large ingots

Abstract Modelling of the electroslag remelting process is one of the key issues related to the production of large electroslag remelting ingots, and electroslag remelting modelling is also the basis of intelligent system control methods. The electroslag remelting process is complicated because of multiple inputs, multiple outputs, non-linearity, coupling, hysteresis and the difficulty in controlling the melting rate of the electrode. We propose a lumped parameter modelling method, and its corresponding control system to improve remelting speed, control accuracy and ingot quality. In this study, a lumped parameter model of the electroslag remelting process was established based on the theory of heat transfer, soft-sensing technology and so on, and the model was then verified by performing experiments. The electroslag remelting intelligent control system was designed according to the control theory for multivariable systems, and the designed controllers were optimised based on the genetic algorithm method known as NSGAII. Simulation results show that the control system is feasible, and experimental results show that the designed control system is in agreement with the research aims.