Nonconvex integer optimal robust impulsive control strategy for first-order piecewise finite precision nonlinear random early detection algorithm

Abstract

There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impulsive control strategy for stabilizing the average queue size. The objective of the control strategy is to determine the average queue size so that the average power of the impulsive control force is minimized subject to a constraint on the absolute difference between the actual average queue size and the theoretical average queue size at the equilibrium point. Computer numerical simulation results show that the proposed control strategy is effective and efficient for stabilizing the average queue size.