Nonlinear Model Predictive Congestion Control for Networks

This paper addresses congestion control for networks. The main focus is the modeling and compensation of nonlinear disturbance in the network, which is seldom considered in the literature. A new congestion control method is presented to compensate for the effects of nonlinear disturbance, uncertainty, time-varying delay, and input constraint. A state feedback congestion controller is designed via model predictive control approach. The stability of the closed-loop system is analyzed by using Lyapunov-Krasovskii functional. The effectiveness and feasibility of the proposed controller are verified by simulation results.