State estimation for nonlinear systems with delayed output measurements

In this paper, we consider the problem of state estimation for nonlinear systems when the output measurements are delayed. We assume an observer is available that takes the delayed outputs and estimates the delayed states of the system. We propose a novel predictor that takes the delayed estimates from the observer and fuses them with the current input measurements of the system to compensate for the delay. We provide a rigorous stability analysis for globally Lipschitz systems demonstrating that the prediction of the system state converges (asymptotically/exponentially) to the current system trajectory if the observer state converges (asymptotically/exponentially) to the delayed system state. The predictor is omputationally simple as it is recursively implementable with a set of delay differential equations. We demonstrate the performance of the proposed predictor via simulation studies

Velocity aided attitude estimation on SO(3) with sensor delay

This paper provides a nonlinear attitude estimation method for vehicles performing high acceleration maneuvers when measurements of linear velocity and the ambient magnetic field are delayed. Linear velocity is measured using the Global Positioning System (GPS) and the delays of GPS and magnetometer measurements are assumed to be known constants. Our proposed method consists of a delayed observer coupled with a dynamic predictor. The delayed observer uses delayed measurements and provides estimates of delayed attitude and velocity states that are in turn used in the predictor to generate estimates of the current attitude and velocity. A key contribution of the paper is effective use of the underlying symmetries of the system in order to design a generic predictor that can be coupled to different observers. We prove exponential convergence of the predicted attitude and velocity for a specific observer choice drawn from the literature