State estimation and estimator based predictive control of nonlinear autonomous hybrid systems poses a challenging problem as these systems involve discontinuities that are introduced by switching of the discrete variables. In this paper, we propose a state estimation scheme for an autonomous hybrid system using an ensemble Kalman filter (EnKF), which belongs to the class of particle filters an...

This paper develops a result on the design of robust steady-state estimator for a class of uncertain discrete-time systems with Markovian jump parameters. This result extends the steady-state Kalman filter to the case of norm-bounded time-varying uncertainties in the state and measurement equations as well as jumping parameters. We derive a linear state estimator such that the estimation-error ...

A state estimator design is presented for a Mars rover prototype. Odometry estimates are obtained by utilizing the f u l l kinematics of the vehicle including the nonlinear internal kinematics of the rover rocker-bogey mechanism as well as the contact kinematics between the wheels and the ground. Additional sewing using gyroscopes, acclerometers and visual sensors allows for robust rover motion...

Using the technique of smoothed perturbation analysis, we consider steady-state performance measures for continuous-time Markov chains and derive a derivative estimator that can be estimated from a single sample path of the chain under consideration. The estimator is applicable to multi-class queueing networks, for which previous in nitesimal perturbation analysis estimators failed. A simple mu...

One of the fundamental tenets in deregulation of the power system is to provide fair and open access to transmission facilities. This requires that market participants, both power brokers and generation companies, have complete and timely information as to the transmission availability. The present system of posting available transmission capacities (ATC) is useful but limited because there is ...

In this paper a new integrated observer-based fault estimation and accommodation strategy for discretetime piecewise linear (PWL) systems subject to actuator faults is proposed. A robust estimator is designed to simultaneously estimate the state of the system and the actuator fault. Then, the estimate of fault is used to compensate for the effect of the fault. By using the estimate of fault and...

This paper presents a fault classification method for transmission lines based on voltage phasors using classification and regression trees (CART). The proposed method is intended to aid system operators in understanding the outputs of a PMU only state estimator. Faults are classified into four categories when the estimator is positive sequence and into ten categories when the estimator is thre...

A reduced complexity multiple-input multiple-output (MIMO) channel estimator known as the polynomial-predictor-based vector generalized least mean squares (VGLMS) estimator is developed. It is a simplification of a previously developed polynomial-predictor-based vector generalized recursive least squares (VGRLS) estimator, achieved by replacing the online recursive computation of the ‘intermedi...

A novel robust estimator is proposed for extracting a single complex sinusoid and its parameter (frequency) from measurements corrupted by white noise. This estimator is called an H1 sinusoidal estimator (HSE), which is derived by applying an H1 filter to a noisy sinusoidal model with the state-space representation. Simulations demonstrate that the HSE is more robust to the nature of observatio...

This work presents a method for contact state estimation using fuzzy clustering to learn contact probability for full, six-dimensional humanoid contacts. The data required for training is solely from proprioceptive sensors endeffector contact wrench sensors and inertial measurement units (IMUs) and the method is completely unsupervised. The resulting cluster means are used to efficiently comput...