基于增益自适应Smith预估器的鲁棒AQM拥塞控制算法

根据Lyapunov渐近稳定定理，提出了一种基于增益自适应Smith预估器的鲁棒主动队列管理（AQM）拥塞控制算法（GAS-PI）．该算法结构简单，具有良好的鲁棒性和网络控制性能，同时克服了大时滞给队列稳定性造成的不利影响．仿真结果表明：采用GAS-PI算法，对于限制系统振荡超调量的作用非常明显，同时能使网络具有更快的响应速度及更平稳的队列——在HTTP扰动和负载变动较大的情况下，算法使得缓存队列迅速收敛到稳定值；当网络时延增大时，算法能使网络的动态性能依然保持良好．

Robust AQM Congestion Control Algorithm Based on Gain Adaptive Smith Predictor

A robust AQM(Active Queue Management) congestion control algorithm(GAS-PI) is proposed on the basis of the gain adaptive Smith predictor and according to the Lyapunov asymptotic stability theorem.This algorithm is of simple structure,good robustness and excellent network control performance.Moreover,it overcomes the negative impact on the queue stability caused by the large delay.Simulated results indicate that,by the proposed GAS-PI algorithm,the overshoot of queue can be effectively decreased,and a higher responsive speed as well as a steadier queue can be obtained,that is,the buffer queue quickly converges to the equilibrium point when the network is of HTTP disturbance and great overload change,and the dynamic performance of large-delay networks remains in good condition.