Research On Intelligent Control System For Water-Curtain Cooling Process Based On Quality Feedback

The plate steel is an important kind of steel products essential for steel industry, and the watercuitain cooling technology is a key process to improve the quality of plate steel products. Due to the highly complex mechanism of watercurtain cooling process of rolled steel, it is difficult to be accurately modeled mathematically and it is hard to obtain ideal cooling effects only by traditional control theories and strategy; The fuzzy control theory and its applications offer a new pilot approach and a powerful tool for solving this kind of complex control problems; And genetic algorithms provides an effective way for optimization problems.At first, the plant of watercurtain cooling process is thoroughly analyzed and researched theoretically in this thesis, the hierarchical intelligent control system scheme for watercurtain cooling process based on genetic algorithms is put forward, and genetic algorithms, fuzzy control and hierarchical intelligent control theories and methods are applied to modeling and control of the watercurtain cooling process, the fuzzy models for controlled flow plants of upper and lower watercurtains at control level are built, the control simulation research is conducted for the double closed-loop fuzzy control strategy for flow ratio, results show that the built model is reliable, the proposed scheme is feasible and control performance meets the requirements of production process. Then genetic algorithms and fuzzy control technology are organically integrated to adjust and optimize control rules in the fuzzy controller, A double closed-loop fuzzy control system for the flow ratio of watercurtain cooling system based on genetic algorithms is designed, simulation results indicate that the optimized control system significantly outperforms the previous one in such performance indexes as overshoot, settling time, steady-state error as well as controlled cooling effects, and the effectiveness of the integration of fuzzy control and genetic algorithms for optimization problem is verified. At last, the primary controlled cooling parameters that influence the controlled cooling effects are analyzed in depth theoretically, the computational models of the set values for principal controlled cooling process parameters are established.