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针对循环流化床(CFB)锅炉热工被控对象的特点及遗传算法存在的问题,提出一种用于热工过程建模的改进遗传算法,此算法引入模糊集理论,实现交叉概率和变异概率的模糊自整定,有效抑制了算法早熟,提高了算法的全局搜索能力。利用阶跃响应法获得现场特性曲线,基于模糊遗传算法得到典型负荷处的传递函数,将建模结果用于现场控制器的设计。对主汽温系统现场控制器进行内模控制整定,并进行了仿真研究和实际应用,结果表明该方案有较好的鲁棒性和抗干扰能力。
Aimed at the characteristics of thermal controlled object in CFB boiler and the existing problems in genetic algorithm, an improved genetic algorithm for thermal process modeling is proposed. The algorithm introduces fuzzy set theory to realize crossover probability and mutation The fuzzy self-tuning of probability can effectively restrain the premature algorithm and improve the global search ability of the algorithm. Using the step response method to obtain the on-site characteristic curve, the transfer function at the typical load is obtained based on the fuzzy genetic algorithm, and the modeling result is used in the design of the field controller. The internal model control of the main steam temperature system controller is set, and the simulation research and practical application are carried out. The results show that the scheme has good robustness and anti-interference ability.