基于GA_BP遗传神经网络优化PID控制器参数研究  

Research on Optimizing PID Controller Parameters Based on GA-BP Genetic Neural Network

作　　者：刘辛 黄琼桃 周莹 李嘉玉 罗俊元 LIU Xin;HUANG Qiongtao;ZHOU Ying;LI Jiayu;LUO Junyuan(School of Electrical and Electronic Engineering,Guangdong Technology College,Zhaoqing,Guangdong 526000,China)

机构地区：[1]广东理工学院电气与电子工程学院,广东肇庆526000

出　　处：《自动化应用》2024年第21期54-58,62,共6页Automation Application

基　　金：大学生创新创业训练计划项目(S202313720016)。

摘　　要：作为一种重要的控制技术,传统PID控制器具有设计独特、运行机理精准以及出色的可靠性等优点,被广泛应用于工业控制领域。但PID控制器存在参数整定困难,在面对复杂的非线性系统时会出现控制效果不理想等情况。针对以上问题,提出一种基于遗传算法与神经网络的新型PID控制器。通过BP神经网络的在线实时调整能力提升系统稳定性,利用GA遗传算法搜寻全局最优解,提高了控制器调整速度,并能避免BP_PID控制器陷入局部极限,实现了参数自动调整和控制效果的优化,提高了控制系统的性能。As an important control technology,traditional PID controllers have the advantages of unique design,precise operating mechanism,and excellent reliability,and are widely used in the field of industrial control.However,PID controllers face difficulties in parameter tuning and have unsatisfactory control performance when dealing with complex nonlinear systems.A novel PID controller based on genetic algorithm and neural network is proposed to address the above issues.The online real-time adjustment capability of BP neural network is used to improve system stability,and GA genetic algorithm is used to search for the global optimal solution,which improves the controller adjustment speed and avoids BP-PID controller from falling into local limits,achieving automatic parameter adjustment and optimization of control effect,and improving the performance of the control system.

关 键 词：PID控制器 GA遗传算法 BP神经网络 模型优化 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]