Alpha beta filter

About: Alpha beta filter is a research topic. Over the lifetime, 5653 publications have been published within this topic receiving 128415 citations.

Distributing the Kalman Filter for Large-Scale Systems

Abstract: This paper presents a distributed Kalman filter to estimate the state of a sparsely connected, large-scale, n -dimensional, dynamical system monitored by a network of N sensors. Local Kalman filters are implemented on nl-dimensional subsystems, nl Lt n, obtained by spatially decomposing the large-scale system. The distributed Kalman filter is optimal under an Lth order Gauss-Markov approximation to the centralized filter. We quantify the information loss due to this Lth-order approximation by the divergence, which decreases as L increases. The order of the approximation L leads to a bound on the dimension of the subsystems, hence, providing a criterion for subsystem selection. The (approximated) centralized Riccati and Lyapunov equations are computed iteratively with only local communication and low-order computation by a distributed iterate collapse inversion (DICI) algorithm. We fuse the observations that are common among the local Kalman filters using bipartite fusion graphs and consensus averaging algorithms. The proposed algorithm achieves full distribution of the Kalman filter. Nowhere in the network, storage, communication, or computation of n-dimensional vectors and matrices is required; only nl Lt n dimensional vectors and matrices are communicated or used in the local computations at the sensors. In other words, knowledge of the state is itself distributed.

Nonlinear observers and applications

Abstract: An Overview on Observer Tools for Nonlinear Systems.- Uniform Observability and Observer Synthesis.- Adaptive-Gain Observers and Applications.- Immersion-Based Observer Design.- Nonlinear Moving Horizon Observers: Theory and Real-Time Implementation.- Asymptotic Analysis and Observer Design in the Theory of Nonlinear Output Regulation.- Parameter/Fault Estimation in Nonlinear Systems and Adaptive Observers.

A cellular computer to implement the kalman filter algorithm

Abstract: The subject of this thesis is the development of the design for a specially-organized, general-purpose computer which performs matrix operations efficiently. The content of the thesis is summarized as follows: First, a review of the relevant work which has been done with microcellular and macrocellular techniques is made, Second, the discrete Kalman filter is described as an example of the type of problem for which this computer is efficient. Third, a detailed design for a cellular, array-structured computer is presented. Fourth, a computer program which simulates the cellular computer is described. Fifth, the recommendation is made that one cell and the associated control circuits be constructed to determine the feasibility of producing a hardware realization of the entire computer. A CELLL1TAR COMPUTER TO IMPLEMENT THE JLimAN FILTER ALGORITHM