Research on roll temperature compensation of variable domain fuzzy controller based on improved cat swarm optimization

Abstract

In the hot rolling process, the hot crown of the roll is determined by the roll temperature and the temperature distribution. Furthermore, the hot crown is an important factor, which causes variation in the strip gage along the plane perpendicular to the rolling direction, affecting the strip quality. However, the roll temperature response has the characteristics of nonlinearity, hysteresis and time-varying, which makes it difficult to control accurately by classical control theory and method. In order to accurately control the rolling temperature, a variable universe fuzzy controller based on improved cat swarm optimization (ICSO-VUFC) was established. Firstly, a dynamic mixture ratio and an improved tracking mode were used to improve the optimization capability of the cat swarm. In comparison with the conventional cat swarm optimization (CSO) controller, the proposed process showed better optimization performance. Secondly, a simulation analysis based on MATLAB was employed to compare the ICSO-VUFC with the conventional fuzzy controller (C-FC) and the fuzzy controller based on the improved cat swarm optimization (ICSO-FC). The results reveal that the ICSO-VUFC exhibits the best dynamic and steady performance. Finally, the temperature control accuracy of the rolled regions during different rolling passes under the three fuzzy controllers was examined and compared. The results show that the ICSO-VUFC exhibits the highest control accuracy and stability with a temperature error range of ±4 °C. Through the analysis of the strip crown, it can be seen that the control accuracy of the strip crown can be effectively improved by using ICSO-VUFC to control the roll temperature distribution.