基于遗传算法优化的稀土氧化物浓度模糊控制策略研究
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作者单位:

内蒙古科技大学 自动化与电气工程学院, 内蒙古 包头 014010

作者简介:

费鹏宇(1999—),男,汉族,内蒙古锡林浩特人,硕士研究生,研究方向为稀土电解智能控制。

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中图分类号:

TF803.2+7;TP391

基金项目:

国家重点研发计划(2023YFB3506800)


Fuzzy control strategy of rare earth oxide concentration based on genetic algorithm optimization
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School of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010 , China

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    摘要:

    针对当前稀土电解工业自动化水平较低的问题,提出一种基于遗传算法(GA)优化的稀土氧化物浓度模糊控制方法,该方法结合稀土熔盐电解工艺的特点,分析槽电阻、稀土氧化物浓度以及下料速率之间的关系,以确定相应的浓度控制策略。利用遗传算法的迭代寻优能力,实现对模糊控制的量化因子与比例因子的动态调整,进而得到一个性能较好的模糊控制器。通过Simulink进行仿真验证,结果表明,当比例因子和量化因子Ke、Kec、Ku分别为0.01、0.03和7.94时系统达到最优,模糊控制器超调量为0.1%,调节时间为16s,相比于传统PID控制和模糊控制均有所改善。实际工程应用结果表明,该模糊控制方法可以将稀土氧化物浓度控制在理想区域内,能够满足现场稀土熔盐电解的工作需求。由于此方法采用遗传算法进行优化,在稀土氧化物浓度控制这种复杂系统中需要较多的计算资源和时间,后续可考虑对算法进行改进,以提高优化效率和精度。

    Abstract:

    Aiming at the current low level of automation in rare earth electrolysis industry, a fuzzy control method of rare earth oxide concentration based on genetic algorithm (GA) optimization is proposed. Combined with the characteristics of rare earth molten salt electrolysis process, the relationship between cell resistance, rare earth oxide concentration and discharging rate is analyzed to determine the corresponding concentration control strategy. The iterative optimization ability of the genetic algorithm is used to realize the dynamic adjustment of the quantization factor and the scale factor of the fuzzy control, so as to obtain a fuzzy controller with better performance. Simulation verification is carried out through Simulink, and the results show that when the scale factor and quantization factor Ke, Kec, Ku are 0.01,0.03 and 7.94 respectively, the system reaches the optimal, the overshoot of the fuzzy controller is 0.1%, and the adjustment time is 16s, which is improved compared with the traditional PID control and fuzzy control. The practical engineering application results show that the fuzzy control method can control the concentration of rare earth oxide in the ideal area, which can meet the working requirements of rare earth molten salt electrolysis on site. Because this method is optimized by genetic algorithm, more computing resources and time are needed in the complex system of rare earth oxide concentration control. In the future, the algorithm should be improved to improve the optimization efficiency and accuracy.

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费鹏宇, 王新春, 杨培宏, 等. 基于遗传算法优化的稀土氧化物浓度模糊控制策略研究[J].中国有色冶金,2025,54(1):76-84.

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  • 收稿日期:2024-09-26
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  • 在线发布日期: 2025-12-18
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