A description of a Solid Oxide Fuel Cell (SOFC) combined Gas Turbine (GT) hybrid system is given. Modeling of all the components of the hybrid system is briefly presented. A decentralized control structure using PI controllers is designed and is considered as a part of the system. An Unscented Kalman Filter (UKF) is applied to estimate the state vector and the simulation results are presented. ...

Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are often used in target tracking, but the required Posterior Density Function (PDF) is still approximated by a Gaussian, which may be a gross distortion of the true underlying structure and lead to filter divergence when performing EKF or UKF. Because the uncertainty of process model in bearing only tracking is small compared with ...

Face detection and tracking are of the most challenging problems of the object tracking field because of the large variability of faces and facial expressions. In this paper, two different algorithms for face tracking based on unscented Kalman filter (UKF) are proposed. The first proposed algorithm is UKF based on Viola-Jones algorithm. Viola-Jones is extremely fast feature computation, efficie...

Multiple sensor fusion for robot localisation and navigation has attracted a lot of interest in recent years. This paper describes a sensor based navigation approach using an interval analysis (IA) based adaptive mechanism for an Unscented Kalman filter (UKF). The robot is equipped with inertial sensors (INS), encoders and ultrasonic sensors. An UKF is used to estimate the robot position using ...

Particle filters are an alternative to approximate the Kalman filter for nonlinear problems. This paper intends to assess the potential of Particle Filter (PF) and its variants in the context of the state estimation problem of a three phase induction motor. The conventional Particle Filter (SIR-PF), and particle filters that employ importance sampling through proposal distributions such as Part...

Abstract Aiming to improve the position and velocity precision of INS/GNSS system during GNSS outages, a novel that combines unscented Kalman filter (UKF) nonlinear autoregressive neural networks with external inputs (NARX) is proposed. The NARX-based module utilized predict measurement updates UKF outages. A new offline approach for selecting optimal NARX suggested tested. This based ...

This paper addresses the problem of integration of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) for the purpose of developing a low-cost, robust and highly accurate navigation system for unmanned surface vehicles (USVs). A tightly-coupled integration approach is one of the most promising architectures to fuse the GNSS data with INS measurements. However, the re...

Due to the randomness and uncertainty in atmospheric environment, accompanied by a variety of unknown noise. Accurate prediction PM 2.5 concentration is very important for people prevent injury effectively. In order predict more accurately this hybrid modelling method support vector regression adaptive unscented Kalman filter (SVR-AUKF) proposed case incorrect or Firstly, model was established ...

The aim of this paper is to present a novel approach for the design and implementation of an onboard nonlinear state estimation system for an autonomous aerial vehicle. The tasks of such a system include collection of measurement data from different navigation sensors, and estimation of all the quantities describing the system’s state of motion based on the system dynamics and the measurement d...

This paper addresses the problem of state estimation for nonlinear systems by means of the unscented Kalman filter (UKF). Compared to the traditional extended Kalman filter, the UKF does not require the local linearization of the system equations used in the propagation stage. Important results using the UKF have been reported recently but in every case the system equations used by the filter w...