A set-valued state estimator for nonlinear dynamic systems is presented. The estimator uses the Galerkin approximation to solve Kolmogorov's equation for the diiusion of a continuous time continuous state non-linear system, as well as for implementing discrete time updates of noisy measurements. This ltering of the state is accomplished for a convex set of distributions simultaneously and a fun...

We propose an estimator for the CDF G of the sojourn time in a steady-state M/G/∞ queueing system, when the available data consists of the arrival and departure epochs alone, without knowing which arrival corresponds to which departure. The estimator is a generalization of an estimator proposed by Brown (1970), and is based on a functional relationship between G and the distribution of the time...

A state estimator design is described for discrete time systems having observably intermittent measurements. A stationary Markov process is used to model probabilistic measurement losses. The stationarity of the Markov process suggests an analagous stationary estimator design related to the Markov states. A precomputable time-varying state estimator is proposed as an alternative to Kalman’s opt...

To ensure safe and reliable battery operations, an accurate battery state of charge (SOC) estimation is critical for the battery systems used in electric vehicles and hybrid electric vehicles because of the arduous operation conditions. This paper presents a SOC estimator designed based on the unscented Kalman filter (UKF), which is very popular in the state estimation in non-linear systems. Th...

We propose a fast real-time state estimator based on the belief propagation algorithm for the power system state estimation. The proposed estimator is easy to distribute and parallelize, thus alleviating computational limitations and allowing for processing measurements in real time. In fully distributed implementation, local modules compute state estimates at the bus level (e.g., at generators...

this article examines statistical inference for  where and are independent but not identically distributed pareto of the first kind (pareto (i)) random variables with same scale parameter but different shape parameters. the maximum likelihood, uniformly minimum variance unbiased and bayes estimators with gamma prior are used for this purpose. simulation studies which compare the estimators are ...

The problem addressed in this article is the localization of a mobile robot using combination onboard sensors and ultrawideband (UWB) beacons. By discrete-time formulation system's kinematics, we identify geometric conditions that make system globally observable cast state estimation into framework least-squares optimization. observability filter thus obtained remarkably different from classic ...