期刊文献+

基于自适应全局滑模控制的非线性主动队列管理 被引量:3

Nonlinear active queue management based on adaptive global sliding mode control
原文传递
导出
摘要 针对传输控制协议(TCP)网络系统存在不确定参数和非响应流干扰的情况,基于自适应全局滑模控制,设计一种非线性主动队列管理算法.采用全局滑模控制消除了滑模控制的到达阶段,保证了网络系统在整个控制过程的鲁棒性.采用径向基函数(RBF)网络直接逼近系统的总不确定可有效地减小估计误差.由于没有使用符号函数或饱和函数,不仅可以有效抑制系统的抖振,而且系统的响应更加平稳.仿真结果表明,该算法具有较好的鲁棒性和较快的系统响应. For the transmission control protocol(TCP) network systems in the presence of uncertain parameters and unresponsive flows, a nonlinear active queue management algorithm is presented based on adaptive global sliding mode control. The global sliding mode control is used to eliminate the arrival stage of sliding mode control and ensure the robustness of network systems in the whole control process. The radial basis function(RBF) network is used to directly approximate the lumped uncertainties of the systems so that the estimation error is effectively reduced. Because the sign function and the saturation function are not used, not only the system chattering is effectively eliminated, but also the system response is smoother. Simulation results show that the proposed algorithm has good robustness and fast system response.
出处 《控制与决策》 EI CSCD 北大核心 2012年第10期1557-1560,1565,共5页 Control and Decision
基金 国家自然科学基金项目(60274009) 国家高技术研究发展计划项目(2004AA412030)
关键词 TCP网络 拥塞控制 RBF网络 自适应 全局滑模控制 TCPnetworks congestion control RBFnetwork adaptive global sliding modecontrol
  • 相关文献

参考文献13

  • 1Doucet A, Godsill S, Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering[J]. Statistics and Computing, 2000, 10(3): 197-208.
  • 2Bar-Shalom Y, Li X R. Multitarget-multisensor tracking principles and techniques[M]. New Orleans: University of New Orleans, 1995: 40-60.
  • 3Mustiere F, Bolic M, Bouchard M. Rao-Blackwellised particle filters: Examples of applications[C]. Canadian Conf on Electrical and Computer Engineering. Ottawa, 2006:1196-1200.
  • 4Matti Vihola. Rao-Blackwellised particle filtering in random set multitarget tracking[J]. IEEE Trans on Aerospace and Electronic Systems, 2007, 43(2): 689-705.
  • 5Nando de Freitas. Rao-Blackwellised particle filtering for fault diagnosis[C]. Proc of IEEE Aerospace Conf. Montana, 2002, 4: 1767-1772.
  • 6Arnaud Doucet, Neil J Gordon, Vikram Krishnamurthy. Particle filters for state estimation of jump Markov linear systems[J]. IEEE Trans on Signal Processing, 2001, 49(3): 613-624.
  • 7Mustiere F, Bolic M, Bouchard M. A modified Rao- Blackwellised particle filter[C]. IEEE Int Conf on Acoustics, Speech and Signal Processing. Toulouse, 2006, 3: 21-24.
  • 8尹建君,张建秋,林青.Unscented卡尔曼滤波-卡尔曼滤波算法[J].系统工程与电子技术,2008,30(4):617-620. 被引量:19
  • 9Julier S, Uhlmann J, Durrant-Whyte H F. Anew method for the nonlinear transformation of means and covariances in filters and estimators [J]. IEEE Trans on Automatic Control, 2000, 45(3): 477-482.
  • 10Arasaratnam I, Haykin S. Cubature Kalman filter[J]. IEEE Trans on Automatic Control, 2009, 54(6): 1254-1269.

二级参考文献10

  • 1Doucet A, Godsill S, Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering[J]. Statistics and Computing, 2000 (10) : 197 - 208.
  • 2Doucet A. On sequential simulation-based methods for Bayesian filtering[R]. Technical report CUED/F-INFENG/TR 310, Cambridge University Engineering Department, 1998.
  • 3Mustiere F, Bolic M, Bouchard M. Rao-Blackwellised particle filters: examples of applications[C]//IEEE Canadian Conference on Electrical and Computer Engineering ( CCECE).Ottawa, Canada, 2006.
  • 4Doucet A, Freitas N, Gordon N J. Sequential Monte Carlo in practice[M]. New York : Springer, 2001.
  • 5Freitas N. Rao-blackwellised particle filtering for fault diagnosis[C]// IEEE Aerospace Conference Proceedings, 2002,4 : 1767 - 1772.
  • 6Julier S J, Uhlmann J K. A new extension of the Kalman filter to nonlinear systems[C]//Proc. of AeroSense : The l lth International Symposium on Aerospace/Defence Sensing, Simulation and Controls, SPIE, Orlando, Florida, USA, 1997:182- 193.
  • 7Merwe R, Doucet A, Freitas N, Wan E. The unscented particle filter[R]. Technicalreport CUED/F-INFENG/TR 380, Cambridge University Engineering Department, 2000.
  • 8Morelande M R, Ristic B. Reduced sigma point filtering for partially linear models[C]//ICASSP, 2006 : 37 - 40.
  • 9Mustiere F, Bolic M, Bouchard M. A modified Rao-blackwellised particle filter[C]//IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, France, 2006:21 - 24.
  • 10Steven M K.统计信号处理基础-估计与检测理论[M].罗鹏飞,张文明,刘忠,译.北京:电子工业出版社,2003:477-478.

共引文献18

同被引文献29

  • 1Quet P F, Ozbay H. On the design of AQM supporting TCP flows using robust control theory [ J ]. IEEE Transactions on Automatic Control, 2004, 49(6) : 1031 -1036.
  • 2Alvarez T, Salim A. How to reduce congestion on TCP/AQM networks with simple adaptive PID controllers[ C ]//UKACC International Confer- ence on Control. Piscataway, NJ, USA: IEEE, 2012: 30-35.
  • 3Jamali S, Hashemi S N, Moghadam A M. On the use of a full information feedback to stabilize RED [ J ]. Journal of Network and Computer Applications, 2013, 36 (2) : 858 - 869.
  • 4Gao W B, Wang Y, Homaifa A. Discrete time variable structure control systems[ J]. IEEE Transactions on Industrial Electronics, 1995, 42 (2): 117-122.
  • 5Chen C K, Liao T L, Yan J J. Active queue management controller design for TCP communication networks: Variable structure control ap- proach[J]. Chaos, Solitons & Fractals, 2009, 40(1): 277-285.
  • 6Joshi R C, Thakar V K. Congestion control in communication networks using discrete sliding mode control[ C ]//Proceedings of the 31 st Chi- nese Control Conference. Piscataway, NJ, USA : IEEE, 2012 : 5553 - 5557.
  • 7Zhang X Z, Wang Y N. Design and performance analysis of a sliding-mode prediction based active queue management[ J ]. Information Tech- nology Journal, 2013, 12(7) : 1309 - 1317.
  • 8Guan X P, Yang B, Zhao B, et al. Adaptive fuzzy sliding mode active queue management algorithms[ J ]. Telecommunication Systems, 2007, 35(1) : 21 -42.
  • 9Qu x L, Hao Z X, Zhang X Z. A novel adaptive sliding mode congestion control algorithm for TCP networks via T-S model approach[ J]. In- ternational Review on Computers and Software, 2011,6 (5) : 840- 847.
  • 10Wang H W, Yu C, Jing Y W. Observer-based sliding mode control for Internet network congestion control [ C ]//Chinese Control and Decision Conference. Piscataway, NJ, USA: IEEE, 2010:3258 - 3262.

引证文献3

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部