Titlebook: Advances in Estimation, Navigation, and Spacecraft Control; Selected Papers of t Daniel Choukroun,Yaakov Oshman,Moshe Idan Conference proce

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Chemical Water and Wastewater Treatment Ve rotation of the velocity and acceleration vectors as the target maneuvers. This is more complex target maneuver than the simple turning maneuver. The inclusion of the more detailed kinematic behavior of the maneuvering target creates nonlinear equations of motion. The position, velocity, accelerat

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Jia-Qian Jiang,Nigel J. D. Grahamt data. The topic is of great practical and theoretical importance and a large number of methods have been suggested over the last decades. Reference basis is one of the main approaches to model updating. Its underlying principle is to fix certain quantities and minimize the changes of the others wh

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J. Korpij?rvi,E. Laine,H. Ahlstedtem can experience large impulsive noises far more often than the Gaussian would admit. In this paper the Cauchy probability density function (pdf) is used to develop a new class of estimation and control algorithms. First, the scalar Cauchy estimation problem is addressed which entails the generatio

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D. H. Bache,E. Rasool,D. Moffat,M. Johnsonan square error estimator and yields a linear, unbiased estimator that fuses the delayed measurements. Its performance regarding the estimation accuracy, computational workload and memory storage needs is compared to the classical Kalman filter reiteration that achieves the minimum mean square error

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Chemical Water and Wastewater Treatment VIts the level of scalar control action on-line based on direct measurements of the equivalent control obtained by a low-pass filter. It is shown that the adaptive algorithm converge in finite time, thus the chattering is reduced in amplitude and the amount of energy demanded by the controller is redu

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Simple and Complex Reaction-Diffusion Frontsation. To circumvent this issue, a set of non-inertial sensors is used to limit these errors. The fusion between additional data and INS solution is often done by means of an extended Kalman filter using a state-error model. However, the Kalman filter estimates should be used when full observability