Particle swarm optimization based tuning of a modified smith predictor for mould level control in continuous casting

Mould level variations are a serious productivity and quality problem in continuous casting process. This work proposes a level control structure based on the Aström's modified Smith predictor able to improve the bulging effect rejection. Unlike conventional methods, this control strategy decouples the disturbance rejection from the setpoint response and therefore can be independently optimized. Using this scheme, the bulging rejection specifications are reformulated as a H∞ problem and the tuning parameters are designed through the particle swarm optimization approach. Simulation results confirm that the proposed architecture is more effective than the other ones currently implemented in real plants.