This paper proposes a state estimation methodology for invariant systems on Lie groups where outputs of the system are measured with delay. The proposed method is based on cascading an observer and a predictor. The observer uses delayed measurements and provides estimates of delayed states. The predictor uses those estimates together with the current inputs of the system to compensate for the delay and to provide a prediction of the current state of the system. We consider three classes of left-invariant, right-invariant, and mixed-invariant systems and propose predictors tailored to each class. The key contribution of the paper is to exploit the underlying symmetries of systems to design novel predictors that are computationally simple and...
In this paper we address the problem of adaptive state observation of linear timevarying systems wit...
In this paper we address the problem of adaptive state observation of linear timevarying systems wit...
In this paper we propose a new state estimation algorithm called the extended information filter on ...
Abstract not availableAlireza Khosravian, Jochen Trumpf, Robert Mahony, Tarek Hame
This thesis considers the state estimation problem for invariant systems on Lie groups with inp...
In this paper, we consider the problem of state estimation for nonlinear systems when the ou...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
This paper proposes a probabilistic approach to the prob-lem of intrinsic filtering of a system on a...
International audienceIn this paper, a state observer is proposed for a class of nonlinear systems i...
In this paper we introduce a general design approach for observers for left-invariant systems on a L...
In this paper we address the problem of adaptive state observation of linear timevarying systems wit...
In this paper we address the problem of adaptive state observation of linear timevarying systems wit...
In this paper we propose a new state estimation algorithm called the extended information filter on ...
Abstract not availableAlireza Khosravian, Jochen Trumpf, Robert Mahony, Tarek Hame
This thesis considers the state estimation problem for invariant systems on Lie groups with inp...
In this paper, we consider the problem of state estimation for nonlinear systems when the ou...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
We address the problem of constructing (globally) convergent, (reduced-order) observers for general ...
This paper proposes a probabilistic approach to the prob-lem of intrinsic filtering of a system on a...
International audienceIn this paper, a state observer is proposed for a class of nonlinear systems i...
In this paper we introduce a general design approach for observers for left-invariant systems on a L...
In this paper we address the problem of adaptive state observation of linear timevarying systems wit...
In this paper we address the problem of adaptive state observation of linear timevarying systems wit...
In this paper we propose a new state estimation algorithm called the extended information filter on ...