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array algorithm for filtering of discrete-time Markovian jump linear systems

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2007年第7期52卷 1293-1296页

作者： Terra, Marco H. Ishihara, Joao Y. Junior, Antonio P. Univ Sao Paulo Dept Elect Engn BR-13566590 Sao Carlos SP Brazil Univ Brasilia Dept Elect Engn BR-70919970 Brasilia DF Brazil

This note develops an array algorithm for optimal filtering of discrete-time Markovian jump linear systems (DTMJLSs). The known advantages of this kind of algorithm, which was originally developed for normal state-space systems, remain valid when it is applied to linear systems subject to Markovian jumps. It is numerically more stable in the sense that it presents better conditioning and reduced dynamical range. A numerical example, based on fixed-point implementations, is presented in order to demonstrate the advantage of this algorithm.

关键词： array algorithm discrete time filtering linear systems Markovian jump

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array algorithm for filtering of discrete-time Markovian jump linear systems

Array algorithm for filtering of discrete-time Markovian jum...

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American Control Conference 2006

作者： Terra, Marco H. Ishihara, Joao Y. Junior, Antonio P. Univ Sao Paulo Dept Elect Engn CP359 BR-13566590 Sao Carlos SP Brazil Univ Brasilia Dept Elect Engn BR-70919970 Brasilia DF Brazil

ISBN: (纸本)1424402093

This paper addresses computational issues of linear minimum mean square error estimators for discrete-time Markovian jump linear systems. It is developed an array algorithm for increasing the advantages of a recursive filter found in the literature. The known advantages of this kind of algorithm, that was originally developed for normal state-space systems, remain valid when it is applied to linear systems subject to Markovian jumps. It is numerically more stable in sense that it presents better conditioning and reduced dynamical range. A numerical example, based on fixed-point implementations, is presented in order to demonstrate the advantage of this algorithm.

关键词： array algorithm discrete-time filtering linear systems Markovian jump

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Information filtering and array algorithms for descriptor systems subject to parameter uncertainties

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2007年第1期55卷 1-9页

作者： Henrique Terra, Marco Yoshiyuki Ishihara, Joao Carlos Padoan, Antonio, Jr. Univ Sao Paulo Dept Elect Engn BR-13566590 Sao Carlos SP Brazil Univ Brasilia Dept Elect Engn BR-70919970 Brasilia DF Brazil

This paper presents information filters in Riccati recursions and in array algorithms for descriptor systems subject to parameters uncertainties. The filters are developed in filtered and predicted forms. The inversion of the state matrix is avoided in the new information recursive formulas. Therefore, it turns out clear that the invertibility of the state matrix, usually considered in the state-space information recursions, is not necessary. A numerical example is provided to illustrate the performance of the proposed robust array algorithms.

关键词： array algorithm descriptor systems information filter Kalman filter

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Information filtering and array algorithms for discrete-time Markovian jump linear systems subject to parametric uncertainties

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INFORMATION SCIENCES 2016年第0期369卷 287-303页

作者： de Jesus, Gildson Q. Inoue, Roberto S. Terra, Marco H. Univ Estadual Santa Cruz Dept Sci & Technol Ilheus BA Brazil Fed Univ SaEo Carlos Dept Elect Engn Saeo Carlos SP Brazil Univ Saeo Paulo Dept Elect Engn Saeo Carlos SP Brazil

In this paper we present robust information filters for discrete-time Markovian jump linear systems subject to uncertainties in the parameters. We provide recursive estimations to deal with jumps, uncertainties, and unknown initial conditions of the Markovian states. The difficulty in defining initial conditions for this class of systems where the Markov chain is also unknown, justifies the use of information type filters. As an alternative computation method we develop array and fast array algorithms to estimate these uncertain informations. We present numerical examples to demonstrate the efectiveness of the array algorithms proposed. We present also simulation results related with the application of the robust information filter to solve mobile robot localization problems. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Robust estimation array algorithm Information filter Markovian jump Discrete-time Mobile robot

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Information Filtering and array algorithms for Discrete-Time Markovian Jump Linear Systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2009年第1期54卷 158-162页

作者： Terra, Marco Henrique Ishihara, Joao Yoshiyuki Jesus, Gildson Univ Sao Paulo Dept Elect Engn BR-13566590 Sao Carlos SP Brazil Univ Brasilia Dept Elect Engn BR-70919970 Brasilia DF Brazil

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump l... 详细信息

关键词： array algorithm discrete-time information filter linear systems Markovian jump

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Information filtering and array algorithms for discrete-time Markovian jump linear systems

Information filtering and array algorithms for discrete-time...

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26th American Control Conference

作者： Terra, Marco H. Ishihara, Joao Y. Jesus, Gildson Univ Sao Paulo Dept Elect Engn CP 359 BR-13566590 Sao Carlos SP Brazil Univ Brasilia Dept Elect Engn BR-70919970 Brasilia DF Brazil

ISBN: (纸本)9781424409884

This paper develops information filter and array algorithms for the linear minimum mean square error estimator (LMMSE) for discrete-time Markovian jump linear systems (MJLSs). A numerical example to show the advantage of the array algorithm in fix-point implementations is presented in order to demonstrate the advantage of this approach.

关键词： information filter array algorithm discrete-time linear systems Markovian jump

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A fast-array Kalman filter solution to active noise control

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2005年第2-3期19卷 125-152页

作者： Fraanje, R Sayed, AH Verhaegen, M Doelman, NJ Delft Univ Technol Delft Ctr Syst & Control NL-2628 CD Delft Netherlands

A Kalman filter solution to active control and its fast-array implementation are provided. The adaptive control problem is formulated as a state-estimation problem and no interchanging of the adaptive filter and the secondary-path is imposed. Moreover, no estimate of the disturbance signal is needed, and we exploit the structure in the state-space matrices to derive a fast-array implementation. A minimum variance estimate of the controller coefficients and the secondary path state is obtained. When there is no uncertainty in the secondary path, state equivalence with the modified filtered-RLS algorithm is proven. Using exponential forgetting, the analysis shows that in the generation of the filtered reference signal in the modified filtered-RLS, exponential forgetting should be incorporated too. Simulations show the superiority in convergence of the fast-array Kalman algorithm over the fast-array modified filtered-RLS algorithm. Copyright (c) 2004 John Wiley & Sons, Ltd.

关键词： adaptive filters state-space array algorithm Kalman RLS tracking algorithm structured state-space model

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RLS-Laguerre lattice adaptive filtering: Error-feedback, normalized, and array-based algorithms

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2001年第11期49卷 2565-2576页

作者： Merched, R Sayed, AH Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

This paper develops several lattice structures for RLS Laguerre adaptive filtering including a posteriori and a priori based lattice filters with error-feedback, array-based lattice filters, and normalized lattice filters. All structures are efficient in that their computational cost is proportional to the number of taps, albeit some structures require more multiplications or divisions than others. The performance of all filters, however, can differ under practical considerations, such as finite-precision effects and regularization. Simulations are included to illustrate these facts.

关键词： array algorithm error feedback Laguerre network lattice filter normalized lattice order-recursive filter regularized least-squares RLS algorithm

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