Author(s)

Yilong Yao ¹, Zhao Zhang ¹, Jianhui Shi ², Ruquan Liang ²

Affiliation(s)

¹ School of Automation and Electrical Engineering, Linyi University, Linyi, China
² School of Mechanical and Vehicle Engineering, Linyi University, Linyi, China

Corresponding Author

Jianhui Shi

ABSTRACT

The controlled cooling technology for hot-rolled strip steel is a critical factor in determining the quality and performance of finished steel products. The coiling temperature, as a key control parameter, directly impacts the stability of the post-rolling cooling system. To ensure precise temperature regulation of the steel plate during the cooling process after hot-rolled strip steel production and to address the challenges posed by system complexity and time delays, this paper introduces a control method utilizing a Smith Predictor integrated with a Fuzzy PID controller specifically for the post-rolling cooling system. First, Drawing from relevant temperature control experience and practical considerations, a mathematical model for the post-rolling cooling temperature control system was developed. Then, a PID temperature controller was designed using this model, with the PID parameters adaptively tuned via a fuzzy control algorithm. Additionally, the Smith predictor algorithm was introduced to compensate for system delay. Finally, a simulation model was developed using MATLAB's Simulink module, and comparative simulations were conducted. The results demonstrate that under Smith-Fuzzy PID control, the system exhibits minimal overshoot and steady-state error, the shortest settling time, enhanced stability, and overall improved control performance. The system shows strong adaptive capabilities in the post-rolling cooling process of hot-rolled strip steel, effectively achieving the desired steady-state characteristics.

KEYWORDS

Hot-rolled strip steel, post-rolling cooling, Smith predictor algorithm, fuzzy PID, MATLAB

CITE THIS PAPER

Yilong Yao, Zhao Zhang, Jianhui Shi, Ruquan Liang, Research on Post-Rolling Cooling System Temperature Control Based on Smith-Fuzzy PID. Journal of Materials, Processing and Design (2024) Vol. 8: 89-100. DOI: http://dx.doi.org/10.23977/jmpd.2024.080211.

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