International audienceThis paper proposes a discussion on the classification of the formulations of nonlinear Moving Horizon Estimators (MHE) of the literature into two categories: deterministic and stochastic. The stability of the dynamics of the estimation error is discussed for the MHEs in both frameworks. This paper also provides full explicit formulation of the stability conditions for the MHE in the deterministic framework, which were not given in the literature. Furthermore, robustness of MHE in both frameworks with respect to model errors is investigated through a simulation example of space object tracking. Comparison with other more classical estimators such as EKF, UKF and particle filter is also achieved
This paper presents a moving horizon algorithm with mode detection for state estimation in Markov ju...
The classical unscented Kalman filter (UKF) requires prior knowledge on statistical characteristics ...
Model Predictive Control (MPC) and constrained Moving Horizon Estimation (MHE) are both optimization...
International audienceThis paper proposes a discussion on the classification of the formulations of ...
Abstract — In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique f...
Abstract — In the past decade, moving horizon estimation (MHE) has emerged as a powerful technique f...
International audienceTrajectory estimation during atmospheric reentry of ballistic objects such as ...
We analyze the stability properties of an approximate algorithm for moving horizon estimation (MHE)....
This note proposes a new form of nonlinear state estimator, for which we can establish robust global...
International audienceIn this paper, a Moving Horizon Estimator with pre-estimation (MHE-PE) is prop...
In this paper, a constrained moving horizon estimation (MHE) strategy for linear systems is proposed...
In this paper, the robust stability and convergence to the true state of moving horizon estimator ba...
Moving horizon estimation (MHE) is a con- strained non-convex optimization problem in principle, whi...
This paper formalises the concepts of weakly and weakly regularly persistent input trajectory as wel...
In this paper, we propose a suboptimal moving horizon estimator for a general class of nonlinear sys...
This paper presents a moving horizon algorithm with mode detection for state estimation in Markov ju...
The classical unscented Kalman filter (UKF) requires prior knowledge on statistical characteristics ...
Model Predictive Control (MPC) and constrained Moving Horizon Estimation (MHE) are both optimization...
International audienceThis paper proposes a discussion on the classification of the formulations of ...
Abstract — In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique f...
Abstract — In the past decade, moving horizon estimation (MHE) has emerged as a powerful technique f...
International audienceTrajectory estimation during atmospheric reentry of ballistic objects such as ...
We analyze the stability properties of an approximate algorithm for moving horizon estimation (MHE)....
This note proposes a new form of nonlinear state estimator, for which we can establish robust global...
International audienceIn this paper, a Moving Horizon Estimator with pre-estimation (MHE-PE) is prop...
In this paper, a constrained moving horizon estimation (MHE) strategy for linear systems is proposed...
In this paper, the robust stability and convergence to the true state of moving horizon estimator ba...
Moving horizon estimation (MHE) is a con- strained non-convex optimization problem in principle, whi...
This paper formalises the concepts of weakly and weakly regularly persistent input trajectory as wel...
In this paper, we propose a suboptimal moving horizon estimator for a general class of nonlinear sys...
This paper presents a moving horizon algorithm with mode detection for state estimation in Markov ju...
The classical unscented Kalman filter (UKF) requires prior knowledge on statistical characteristics ...
Model Predictive Control (MPC) and constrained Moving Horizon Estimation (MHE) are both optimization...