基于自适应蚁群算法的PID控制器设计  

Design of PID Control Based on Adaptive Ant Colony Algorithm

作　　者：沈春娟 SHEN Chun-juan(College of Computer Science and Technology, Nanjing Tech University, Nanjing 211816, China)

机构地区：[1]南京工业大学计算机科学与技术学院,江苏南京211816

出　　处：《仪表技术与传感器》2016年第12期126-128,156,共4页Instrument Technique and Sensor

摘　　要：针对传统的比例积分微分控制器(PID)参数整定多采用经验试凑不能得到最佳控制性能的问题,提出一种基于自适应蚁群算法的PID控制参数整定方法(AACO-PID),以增强控制器的自适应能力。仿真结果表明,AACO-PID控制方法具有调节时间短、超调量小、响应速度快等特点。与传统PID和ACO-PID相比,使用AACO-PID的系统具有更快的响应速度和稳定精度。To settle the problem of imperfect control performance from the traditional PID controller parameter setting with manual cut-and-try method, a parameter setting method based on adaptive ant colony optimization（AACO-PID） was proposed to enhance the capacity of adaptive controller.The simulation result shows that AACO-PID control method has shorter setting time, less overshoot and higher response speed.Compared with the traditional PID control and basic ACO-PID, the system has higher response speed and steady-state accuracy using AACO-PID.

关 键 词：控制器 自适应 蚁群算法 信息素 性能指标 参数整定 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]