Robust state estimation based on quadratic programming for network packet dropout

With the development of network, the wide use of network makes the state sensing more complex, and there inevitably exists the effect of network´s uncertainty. In this paper, a new model which considers the state estimation with the network packet dropout is proposed and this is a robust state estimation problem. In this paper a robust state estimation based on quadratic programming(RSE_QP) method is proposed. In this algorithm, with the use of ℓ₁ term to describe and handle the packet dropout, there needs some transformations to express it as a standard ℓ₁-regularized least squares problem(LSP) for convenient and fast solving. Through solving a ℓ₁-regularized LSP and associating with the Kalman filter updating procedure, the good estimated state is gained effectively even when there exists network packet dropout.