Topic
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.
Papers published on a yearly basis
Papers
More filters
TL;DR: The stability and H- performance analysis of closed-loop system with fault detection observer has been translated into a convex linear matrix inequality (LMI) optimization problem and avoid the complexity of system associated with weight functions.
Abstract: This article addresses the stable fault detection observer design problem for linear time-invariant continuous-time systems in finite-frequency domain. The fault detection filter design is a synthesised optimal Luenberger observer that guarantees two requested performance indexes of fault sensitivity and stability. With the aid of generalised Kalman–Yakubovich–Popov lemma and increasing dimensions of slack variable matrix, the stability and H − performance analysis of the closed-loop system with a fault detection observer has been translated into a convex linear matrix inequality (LMI) optimisation problem to avoid the complexity of system associated with weight functions. An iterative LMI algorithm has been presented for the fault detection observer design. The effectiveness of proposed approaches is demonstrated by two numerical examples.
45 citations
TL;DR: A modified Kalman filter is introduced for the adaptation of a neural network based in the following two changes: a term of the weights adaptation is modified in the modified algorithm to assure the uniform stability, convergence of the weight error, and local minimums avoidance.
Abstract: In this research, a modified Kalman filter is introduced for the adaptation of a neural network. The modified Kalman filter is an improved version of the extended Kalman filter based in the following two changes: (1) a term of the weights adaptation is modified in the modified algorithm to assure the uniform stability, convergence of the weights error, and local minimums avoidance, (2) the activation functions are used instead of the Jacobian terms in the modified algorithm to assure the boundedness of the weights error. The suggested algorithm is applied for the chaotic systems identification.
45 citations
TL;DR: A nonlinear observer, with the feedback gain weighted by the sensitivity of the output with respect to the state, is developed for systems with nonlinear output map.
44 citations
TL;DR: In this article, a nonintrusive inverse heat transfer procedure for predicting the time-varying thickness of the protective phase-change ledge on the inside surface of the walls of a high-temperature metallurgical reactor is presented.
44 citations
TL;DR: The derivation given of the Kalman filter is based on the representation of systems by state variables and the modeling of random processes as the output of linear systems excited by white noise.
Abstract: The Kalman filter is applied to the inverse filtering or deconvolution problem. The derivation given of the Kalman filter emphasizes the relationship between the Kalman and Wiener filter. This derivation is based on the representation of systems by state variables and the modeling of random processes as the output of linear systems excited by white noise. Illustrative results indicate the applicability of these techniques to a variety of geophysical data processing problems. The Kalman filter offers exploration geophysicists additional insight into processing-problem modeling and solution.
44 citations