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Robust Identification (robust + identification)

Distribution by Scientific Domains

Chemistry	40%

Selected Abstracts

Robust identification of piecewise/switching autoregressive exogenous process

AICHE JOURNAL, Issue 7 2010
Xing Jin
Abstract A robust identification approach for a class of switching processes named PWARX (piecewise autoregressive exogenous) processes is developed in this article. It is proposed that the identification problem can be formulated and solved within the EM (expectation-maximization) algorithm framework. However, unlike the regular EM algorithm in which the objective function of the maximization step is built upon the assumption that the noise comes from a single distribution, contaminated Gaussian distribution is utilized in the process of constructing the objective function, which effectively makes the revised EM algorithm robust to the latent outliers. Issues associated with the EM algorithm in the PWARX system identification such as sensitivity to its starting point as well as inability to accurately classify "un-decidable" data points are examined and a solution strategy is proposed. Data sets with/without outliers are both considered and the performance is compared between the robust EM algorithm and regular EM algorithm in terms of their parameter estimation performance. Finally, a modified version of MRLP (multi-category robust linear programming) region partition method is proposed by assigning different weights to different data points. In this way, negative influence caused by outliers could be minimized in region partitioning of PWARX systems. Simulation as well as application on a pilot-scale switched process control system are used to verify the efficiency of the proposed identification algorithm. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source]

Robust control from data via uncertainty model sets identification

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 11 2004
S. Malan
Abstract In this paper an integrated robust identification and control design procedure is proposed. The plant to be controlled is supposed to be linear, time invariant, stable, possibly infinite dimensional and a set of noise-corrupted input,output measurements is supposed to be available. The emphasis is placed on the design of controllers guaranteeing robust stability and robust performances, and on the trade-off between controller complexity and achievable robust performances. First, uncertainty models are identified, consisting of parametric models of different order and tight frequency bounds on the magnitude of the unmodelled dynamics. Second, Internal Model Controllers, guaranteeing robust closed-loop stability and best approximating the ,perfect control' ideal target, are designed using H,/,-synthesis techniques. Then, the robust performances of the designed controllers are computed, allowing one to determine the level of model/controller complexity needed to guarantee desired closed-loop performances. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Charge derivatization by 4-sulfophenyl isothiocyanate enhances peptide sequencing by post-source decay matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

JOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 4 2003
Lyuben N. Marekov
Abstract High-sensitivity, rapid identification of proteins in proteomic studies normally uses a combination of one- or two-dimensional electrophoresis together with mass spectrometry. The simplicity and sensitivity of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) have increased its application in recent years. The most common method of ,peptide fingerprinting' often may not provide robust identification. Normally additional sequence information by post-source decay (PSD) MALDI-TOFMS provides additional constraints for database searches to achieve highly confident results. Here we describe a derivatization procedure to facilitate the acquisition of such sequence information. Peptide digests from a skin-expressed protein were modified with 4-sulfophenyl isothiocyanate. The resulting peptides carry a fixed negative charge at the N-terminal end and the resulting PSD spectrum is dominated by C-terminal y-type ions. The sequence information in most cases can be obtained manually or with simple programming tools. Methods of optimizing the procedure and increasing the sensitivity are discussed. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Biogeography of the ubiquitous marine bacterium Alteromonas macleodii determined by multilocus sequence analysis

MOLECULAR ECOLOGY, Issue 18 2008
ELENA IVARS-MARTÍNEZ
Abstract Twenty-three isolates of the widely distributed marine bacteria Alteromonas macleodii have been analysed by multilocus sequence analysis combined with phylogenetic and multivariate statistical analyses. The strains originated from the Pacific Ocean, Mediterranean Sea, English Channel, Black Sea and Thailand. Using the nucleotide sequences of nine loci for each of the 23 isolates, a robust identification was achieved of different clades within the single species. Strains generally clustered with the depth in the water column from which the isolate originated. Strains also showed more recombination with isolates from the same vicinity, suggesting that genetic exchange plays a role in diversification of planktonic marine prokaryotes. This study thus shows for the first time for a large set of isolates of a species of planktonic marine prokaryotes that multilocus sequence analysis overcomes the problems associated with the analysis of individual marker genes or presence of extensive recombination events. It can thus achieve intraspecific identification to the level of genotypes and, by comparison with relevant environmental data, ecotypes. [source]

Application of a Bayesian Approach to the Tomographic Analysis of Hopper Flow

PARTICLE & PARTICLE SYSTEMS CHARACTERIZATION, Issue 4 2005
Krzysztof Grudzien
Abstract This paper presents a new approach to the analysis of data on powder flow from electrical capacitance tomography (ECT) using probability modelling and Bayesian statistics. The methodology is illustrated for powder flow in a hopper. The purpose, and special features, of this approach is that ,high-level' statistical Bayesian modelling combined with a Markov chain Monte Carlo (MCMC) sampling algorithm allows direct estimation of control parameters of industrial processes in contrast to usually applied ,low-level', pixel-based methods of data analysis. This enables reliable recognition of key process features in a quantitative manner. The main difficulty when investigating hopper flow with ECT is due to the need to measure small differences in particle packing density. The MCMC protocol enables more robust identification of the responses of such complex systems. This paper demonstrates the feasibility of the approach for a simple case of particulate material flow during discharging of a hopper. It is concluded that these approaches can offer significant advantages for the analysis and control of some industrial powder and other multi-phase flow processes. [source]