Nonlinear Bayesian state estimation: A review of recent developments
Online estimation of the internal states is a perquisite for monitoring, control, and fault
diagnosis of many engineering processes. A cost effective approach to monitor these …
diagnosis of many engineering processes. A cost effective approach to monitor these …
Moving horizon estimation meets multi-sensor information fusion: Development, opportunities and challenges
Since the proposal of moving horizon (MH) estimation in 1960s, the MH estimation approach
has drawn ever-increasing research interests due mainly to its inherent capability of …
has drawn ever-increasing research interests due mainly to its inherent capability of …
A real-time algorithm for moving horizon state and parameter estimation
A moving horizon estimation (MHE) approach to simultaneously estimate states and
parameters is revisited. Two different noise models are considered, one with measurement …
parameters is revisited. Two different noise models are considered, one with measurement …
Maximum likelihood principle and moving horizon estimation based adaptive unscented Kalman filter
The classical unscented Kalman filter (UKF) requires prior knowledge on statistical
characteristics of system noises for state estimation of a nonlinear dynamic system. If the …
characteristics of system noises for state estimation of a nonlinear dynamic system. If the …
How to not make the extended Kalman filter fail
R Schneider, C Georgakis - Industrial & Engineering Chemistry …, 2013 - ACS Publications
In an effort to assess the performance of newer estimation algorithms, many prior
publications have presented comparative studies where the Extended Kalman Filter (EKF) …
publications have presented comparative studies where the Extended Kalman Filter (EKF) …
Nonlinear moving horizon estimation in the presence of bounded disturbances
MA Müller - Automatica, 2017 - Elsevier
In this paper, we propose a new moving horizon estimator for nonlinear detectable systems.
Similar to a recently proposed full information estimator, the corresponding cost function …
Similar to a recently proposed full information estimator, the corresponding cost function …
Assessing the impact of EKF as the arrival cost in the moving horizon estimation under nonlinear model predictive control
M Valipour, LA Ricardez-Sandoval - Industrial & Engineering …, 2021 - ACS Publications
In this work, we investigate the performance of nonlinear model predictive control (NMPC)
and moving horizon estimation (MHE) in a feedback control system subject to different …
and moving horizon estimation (MHE) in a feedback control system subject to different …
Distributed moving horizon state estimation for nonlinear systems with bounded uncertainties
In this work, we propose a distributed moving horizon state estimation (DMHE) design for a
class of nonlinear systems with bounded output measurement noise and process …
class of nonlinear systems with bounded output measurement noise and process …
Simultaneous state and parameter estimation: the role of sensitivity analysis
State and parameter estimation is essential for process monitoring and control. Observability
plays an important role in both state and parameter estimation. In simultaneous state and …
plays an important role in both state and parameter estimation. In simultaneous state and …
Constrained particle filter approach to approximate the arrival cost in moving horizon estimation
Abstract Moving Horizon Estimation (MHE) is an efficient state estimation method used for
nonlinear systems. Since MHE is optimization-based it provides a good framework to handle …
nonlinear systems. Since MHE is optimization-based it provides a good framework to handle …