Constrained linear state estimation - a moving horizon approach

By C. V. Rao, James B. Rawlings, Jay H. Lee. at - Automatisierungstechnik, 2001

601 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/aff0059161d2d44c8696b1dfd7879a4d3f0588bf

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In Control and Systems Engineering

Citations in the corpus

Critical Evaluation of Extended Kalman Filtering and Moving-Horizon Estimation (2005, background): “Rao, Rawlings, and Lee 25 explored estimating this cost for constrained linear systems with the corresponding cost for an unconstrained linear system.”
A tutorial review of economic model predictive control methods (2014, methodology): “As another approach to output feedback EMPC, moving horizon estimation (MHE) based on least squares techniques has become a popular state estimation technique because of its ability to handle nonlinear systems, account for the presence of disturbances, and account for constraints on decision variabl”
Bounded error moving horizon state estimator for non-linear continuous-time systems: application to a bioprocess system (2005, methodology): “[ ] =[2, 5]×[1, ]×[ 2 , 5] contains the solution of the CSP.”
On unscented Kalman filtering with state interval constraints (2010, methodology): “…Elsevier’s archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright On unscented Kalman filtering with state interval constraints Bruno O.S. Teixeira a,*, Leonardo A.B. Tôrres a, Luis A. Aguirre a, Dennis S. Bernstein b a Department of Electronic…”
Architectures for distributed and hierarchical Model Predictive Control - A review (2009, methodology): “for this problem by resorting to the ideas underlying the moving horizon estimators described in [66,83,84].”
Minimax approaches to robust model predictive control (2003, methodology): “A more natural way to incorporate the estimation problem in the minimax MPC framework is to solve the dual estimation problem over a finite horizon backwards in time, along the lines of (Michalska and Mayne, 1995) and (Rao et al., 2000).”
A General-Purpose Software Framework for Dynamic Optimization (Een algemene softwareomgeving voor dynamische optimalisatie) (2013, background): “Such LTV-OCP with quadratic objective are a structured form of quadratic programs (QP) and originate from a wide class of problem formulations in optimal control, notably in solution algorithms for linear-quadratic model predictive control (MPC) problems [159], linear moving horizon estimation (MHE)”
Using Inertial Sensors for Position and Orientation Estimation (2017, unknown): “ethods, where a batch of states x t L 1:t+L 2 , with L 1 and L 2 being positive integers, is estimated using the measurements y 1:t. This is related to xed-lag smoothing and moving horizon estimation [66, 113]. The topic of how to estimate the conditional probability distributions for position and o”
Ltd Registered in England and Wales Registered Number : 1072954 Registered office : (2004, unknown): “Furthermore, to obtain state estimates satisfying (48) at a given tolerance by solving an optimisation problem online, we also present an unscented extension of the constrained Kalman filter (CKF) for linear systems, which is a special case of MHE with unitary horizon (Rao et al. 2001).”