A Hybrid Intelligent Controller for Control of Strip Tension and Looper Height in Tandem Finishing Mill

Strip tension control is crucial in the tandem finishing mills for its safe operation. Most of the industrial applications are of nonlinear. Fuzzy logic controller is the most useful approach to achieve the adaptive ness in the case of nonlinear system. Since fuzzy logic control provides a systematic method of incorporating human expertise and implementing non-linear system. Neural networks are integrated with fuzzy logic which forms a neuro fuzzy system. Genetic algorithm is used to search optimal fuzzy rules and membership functions of neuro fuzzy system in order to give optimal output and hence form the hybrid intelligent controller (HIC). This paper demonstrates the effectiveness of HIC in optimizing the looper height in steel rolling mills compared with conventional controllers, FLC. The simulation result depicts that HIC quickly restore the speed of the main drive and hence looper height is quickly reduced to its optimal (zero) value which intern ensures the safety working condition of steel rolling mills.