Robust fuzzy observer-based control for TCP/AQM network systems with state delay

Active Queue Management (AQM) algorithms have been proposed to address performance degradations of end-to -end congestion control. However, these AQM algorithms present weaknesses for stabilizing delays in heavy loaded networks. In this paper, we describe a novel T-S fuzzy control algorithm to improve best effort TCP/IP Networks performance. In TCP networks, the packet-dropping probability function is considered as a control input. Thus, a TCP/AQM controller is modeled as a time-delay system. The robust observer-based controller is designed to achieve the desired queue size and guarantee the asymptotic stability of the operating point. For the particular TCP network mode, the Lyapunov-Krasovskii function is defined, and the system can be stabilize with the obtained the fuzzy state feedback control law by using linear matrix inequality (LMI). Simulation results show that the derived control strategy is validated.