摘要
主动队列管理(AQM)算法的自适应能力和克服滞后性不良影响的能力是该文研究的重点。在分析AQM采用传统PID存在的问题的基础上,提出了一种时滞网络的自适应主动队列管理(FAGPID)算法。由模糊控制器实现PID参数对动态网络环境的在线自适应调整;成功引入灰预测算法实现反馈数据的超前预测,补偿滞后。仿真对比AQM环境中FAGPID,传统PID以及基于模糊免疫PID(FIGPID)的算法,可知FAGPID相对于FIGPID复杂度低,但FAGPID与FIGPID性能相当,均能克服滞后的影响,能快速稳定地适应动态网络环境,收敛于期望队列长度,具有较小的丢包率,优于传统PID算法。
Enhancing Active Queue Management （AQM） algorithm＇s self-adapting and overcoming network delay＇s poor effect are research emphases. After analyzing traditional PID control algorithm＇s limitation, a novel active queue management algorithm for delay network based on Fuzzy Adaptive PID control and Gray-prediction （FAGPID） is proposed, which can achieve PID parameters＇ on-line self-adapting by fuzzy control under the dynamic delay network circumstances. And, a gray-prediction algorithm is successfully introduced into feedback data＇s advanced prediction to compensate delay. Contrasted with traditional PID and FIGPID （Fuzzy Immue Gray-prediction PID） by simulations, FAGPID has equivalent performance to FIGPID and has better performance than traditional PID control. Both FAGPID and FIGPID can converge to queue size-setting value rapidly and stably, and get lesser packets loss rate, but FAGPID＇s algorithm complexity is lower.
出处
《电子与信息学报》
EI
CSCD
北大核心
2006年第10期1940-1945,共6页
Journal of Electronics & Information Technology
基金
国家"863"基金(2003AA121560)
江苏省高技术研究计划(BG2003001)资助课题
关键词
主动队列管理
时滞网络
模糊自适应
PID控制
灰预测
Active Queue Management（AQM）, Delay network, Fuzzy self-adapting, PID control, Gray-prediction
