遗传算法在三阶控制系统PID参数优化中的应用研究  

Research on Application of Genetic Algorithm in PID Parameters Optimization of Third-Order Control System

作　　者：单玉忠 SHAN Yuzhong(China Nuclear Power Engineering Co.,Ltd.,Shenzhen 518000,China)

机构地区：[1]中广核工程有限公司,广东深圳518000

出　　处：《自动化仪表》2025年第2期19-23,共5页Process Automation Instrumentation

基　　金：国家重点研发计划基金资助项目(2020YFB1711700)。

摘　　要：为进一步拓展遗传算法在控制系统比例积分微分(PID)参数优化中的应用范围,将遗传算法引入具有三阶传递函数的压水堆核电厂某流体系统水位控制过程。在更大取值范围内搜索PID控制器的特征参数的最优解。搜索到了控制性能更优、调整时间更短、稳态误差更小、最大超调量更小的特征参数,证明了遗传算法在三阶控制系统中仍然具有很好的适应性。同时,分析遗传算法种群规模、进化代数对优化结果的影响,给出了趋于稳定最优解所需的最小种群规模和最小代数的建议。该研究对遗传算法在核电厂控制领域的推广应用具有重要意义。To further expand the application scope of genetic algorithm in the optimization of proportional integral differential(PID)parameters of control system,genetic algorithm is introduced into the water level control process of a fluid system of a pressurized water reactor nuclear power plant with third-order transfer function.The characteristic parameters of the PID controller are searched for optimal solutions in a larger range of values.The characteristic parameters with better control performance,shorter adjustment time,smaller steady-state error and smaller maximum overshoot are searched for,which proves that the genetic algorithm is still well adapted in the third-order control system.Meanwhile,the effects of population size and evolutionary generations of the genetic algorithm on the optimization results are analyzed,and the minimum population size and minimum number of generations required to converge to the stable optimal solution are given as suggestions.The research is of great significance for the popularization and application of genetic algorithm in the field of nuclear power plant control.

关 键 词：遗传算法 种群规模 进化代数 稳态误差 调整时间 最大超调量 特征参数 性能指标 稳定最优解 

分 类 号：TH-39[机械工程]