Smart grid is expected to make use of Internet-of-Things (IoT) networks reliably monitor its state from remote places.However, due a potentially unstable nature smart plant, in particular, when using renewable energy sources, and an unreliable wireless channel used IoT, it challenging task track the grids. This article proposes robust communication framework for estimation/tracking microgrids, ...

In order to solve the problem that measured values of key state parameters such as lateral velocity and yaw rate vehicle are easily interfered by random errors, a filter estimation method is proposed based on principle robust filtering unscented particle algorithm. Based establishment 3-DOF non-linear dynamic model Dugoff tire vehicle, adaptive filter(ARUPF) used estimate state, realize longitu...

A robust extended Kalman filter (EKF) is proposed as a method for estimation of the state of charge (SOC) of lithium-ion batteries used in hybrid electric vehicles (HEVs). An equivalent circuit model of the battery, including its electromotive force (EMF) hysteresis characteristics and polarization characteristics is used. The effect of the robust EKF gain coefficient on SOC estimation is analy...

This paper considers the design of robust`1 estimators based on multiplier theory (which is intimately related to the mixed structured singular value theory) and the application of robust`1 estimators to robust fault detection. The key to estimator-based, robust fault detection is to generate residuals which are robust against plant uncertainties and external disturbance inputs, which in turn r...

We address a state estimation problem over a large-scale sensor network with uncertain communication channel. Consensus protocol is usually used to adapt a large-scale sensor network. However, when certain parts of communication channels are broken down, the accuracy performance is seriously degraded. Specifically, outliers in the channel or temporal disconnection are avoided via proposed metho...

Robust Kalman filtering problems for discrete-time Markovian jump systems with parameter and noise uncertainty were investigated. Because of the existence of stochastic Markovian switching, the covariance matrices of system state noise and observation noise are time-varying or unmeasurable instead of stationary, meanwhile the system suffers from structure parameter uncertainty as well. By view ...

Fast state estimation and system identification are essential to the reliability of the increasingly complex power system. Current estimation, on slower, steady-state, time scales does not model dynamics; however, with the deployment of phasor measurement units, faster estimation is now possible. We introduce a robust state estimator that learns the dynamic state of the power system on fast tim...