基于改进遗传算法的PID参数优化在闪蒸罐压力控制中的应用

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英文篇名：Application of the PID parameter optimization based on improved genetic algorithm in pressure control of flash tank 作者：周勇 ; 邓仕英 英文作者：Zhou Yong;Deng Shiying;School of Information Engineering,Engineering and Technology College of Yangtze University;School of Petroleum and Chemical Engineering,Engineering and Technology College of Yangtze University; 关键词：遗传算法 ; 高斯分布 ; 自适应 ; 比例-积分-微分 ; 压力控制 ; 闪蒸罐 英文关键词：genetic algorithm;;gaussian distribution;;adaptation;;PID;;pressure control;;flash tank 中文刊名：XXGY 英文刊名：Modern Manufacturing Engineering 机构：长江大学工程技术学院信息工程学院;长江大学工程技术学院石油与化学工程学院; 出版日期：2019-02-18 出版单位：现代制造工程 年：2019 期：No.461 基金：国家高新技术863计划资助项目(2003AA302330);; 云南省教育厅科学研究基金项目(2016YJS020);; 长江大学工程技术学院基金项目(2018ky08) 语种：中文; 页：XXGY201902025 页数：6 CN：02 ISSN：11-4659/TH 分类号：140-145

摘要

由于在加氢裂化过程中闪蒸罐压力控制存在非线性、大滞后等问题,运用常规比例-积分-微分(Proportion-IntegralDerivative,PID)控制效果较差,虽然传统遗传算法可以优化PID参数,提高控制精度,但是收敛速度慢,整定时间长,限制了其在闪蒸罐压力控制中的应用。针对以上问题,提出了一种通过改进遗传算法优化PID参数的新型方法,该方法以传统遗传算法为基础,通过对适应度值的自适应缩放、交叉率和变异率分别按Sigmoid函数和高斯分布函数自适应调整等策略来提高遗传算法的全局搜索能力和收敛速度,从而实现对PID控制参数的优化。仿真结果表明,用改进遗传算法优化后的闪蒸罐压力PID控制具有更好的自适应性和鲁棒性,使系统调节时间减少到86 s,超调量减少到0. 141 8%,有效地改善了系统的动、静态特性。
        Because of the non-linearity and large hysteresis in the flash tank pressure control during the hydrocracking process,the conventional Proportion-Integral-Derivative( PID) control is less effective. Although the traditional genetic algorithm can optimize the PID parameters and improve the control accuracy,it has a slow convergence speed and a long dynamic response time,which limit its application in flash tank pressure control. Aiming at these problems,a new method for optimizing PID parameters by improving genetic algorithm was proposed. Based on the traditional genetic algorithm,the global searching capability and convergence speed of genetic algorithm are improved by adaptively scaling fitness values,the crossover rate and mutation rate are adjusted adaptively according to Sigmoid function and Gaussian distribution function,In order to achieve the optimal PID control parameters setting. The simulation results show that the flash tank pressure PID control with improved genetic algorithm has better self-adaptability and robustness,accommodation time and overshoot separetely descrease to 86 s and 0. 141 8 %,and improve the dynamic performance and static performance of the system.

引文

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