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基于GA-PID参数优化的网络拥塞控制
引用本文:陆锦军,王执铨.基于GA-PID参数优化的网络拥塞控制[J].南京航空航天大学学报,2008,40(6).
作者姓名:陆锦军  王执铨
作者单位:1. 南通职业大学现代教育技术中心,南通,226007;南京理工大学自动化学院,南京,210094
2. 南京理工大学自动化学院,南京,210094
基金项目:国家自然科学基金 , 江苏省六大人才高峰 , 江苏省自然科学基金 , 南通市科技应用研究项目  
摘    要:推导了基于流体流理论的网络简化模型。基于该模型将P ID控制器应用于网络主动队列管理系统中,将遗传算法应用于P ID控制器参数优化,定义了一种新的综合调节时间、上升时间、超调量、系统误差等动静态性能指标的时域标准函数,克服了IAE,ISE标准函数中减小超调与缩短调节时间的矛盾,弥补了ISTE标准函数计算复杂的缺陷。在给定的参数空间进行组合优化搜索,迅速求得获取使性能指标优化代价函数极小化的一组P ID控制器参数。仿真结果表明,在大时滞和突发业务流的冲击情况下,该方法设计的控制器的动静态性能优于RED,P I算法。

关 键 词:网络简化模型  主动队列管理  网络拥塞  PID参数优化  遗传算法

New Control Strategy of Network Congestion Based on Optimization of GA-PID Parameters
Lu Jinjun,Wang Zhiquan.New Control Strategy of Network Congestion Based on Optimization of GA-PID Parameters[J].Journal of Nanjing University of Aeronautics & Astronautics,2008,40(6).
Authors:Lu Jinjun  Wang Zhiquan
Institution:Lu Jinjun1,2,Wang Zhiquan2
Abstract:Simplified network model based on the fluid flow theory is derived.Based on the model,PID controller is applied to active queue management(AQM) system.An advanced algorithm,i.e.,genetic algorithm,is used to optimize PID controller parameters.Then,a new performance function synthesizing system for adjusting time,rise time,overshoot,and steady state error is defined.The system solves the paradox on the demand of less overshoot and shorter steady time in integrated absolute error(IAE) and integrated square error(ISE) standards,and overcomes the defect of the complex computation in ISTE(when n=1 the ISE is called the ISTE) standard as well.It is fast to calculate a group of PID controller parameters that minimize the optimization cost function by searching the given area of controller parameters,and then the PID controller is applied to AQM system.Simulation results show that under the two conditions of large time delay and sudden business flow,the dynamic state and steady state performances of the algorithm are obviously superior to that of RED and PI algorithms.
Keywords:simplified network model  active queue management  network congestion  optimization of PID parameters  genetic algorithm
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