Mixed active/passive robust fault detection and isolation using set-theoretic unknown input observers

2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIEEE This paper proposes a robust fault detection and isolation (FDI) approach that combines active and passive robust FDI approaches. Standard active FDI approaches obtain robustness by using the unknown input observer (UIO) to decouple unknown inputs from residuals. Differently, standard passive FDI approaches achieve robustness by using the set theory to bound the effect of uncertain factors (disturbances and noises). In this paper, we combine the UIO-based and the set-based approaches to produce a mixed robust FDI, which can mitigate the disadvantages and exert the advantages of the two robust FDI approaches. In order to emphasize the role of set theory, the UIO design based on the set theory is named as the set-theoretic UIO (SUIO). A quadrotor subsystem is used to illustrate the effectiveness of the proposed FDI approach.Peer ReviewedPostprint (author's final draft

Robust state estimation and fault detection combining unknown input observer and set-membership approach

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper aims to propose a new robust state-estimation and fault-detection method by combining the unknown input observer (UIO) and the set-membership estimator (SME). It is known that both the SUIO and the SME can be used to estimate the states of a system. The former aims to obtain a particular value by actively decoupling the effect of unknown inputs, while the latter can obtain state-estimation sets by prediction and correction based on the set theory. Instead of particular state values, the latter can obtain state-estimation sets guaranteeing to contain system states (i.e., robust state estimation). In this paper, we propose to use the framework of the UIO to actively decouple part of unknown inputs and then further employ the set-membership estimation method to estimate state sets and detect faults. The objective of the proposed method is to reduce the conservatism of robust state-estimation sets by using the UIO to remove the contribution of part of unknown inputs to the sizes of state-estimation sets. At the end of this paper, a numerical example is used to illustrate the effectiveness and advantages of the proposed approach.Accepted versio

Resilience of infaunal ecosystems during the Early Triassic greenhouse Earth

The Permian-Triassic mass extinction severely depleted biodiversity, primarily observed in the body fossil of well-skeletonized animals. Understanding how whole ecosystems were affected and rebuilt following the crisis requires evidence from both skeletonized and soft-bodied animals; the best comprehensive information on soft-bodied animals comes from ichnofossils. We analyzed abundant trace fossils from 26 sections across the Permian-Triassic boundary in China and report key metrics of ichnodiversity, ichnodisparity, ecospace utilization, and ecosystem engineering. We find that infaunal ecologic structure was well established in the early Smithian. Decoupling of diversity between deposit feeders and suspension feeders in carbonate ramp-platform settings implies that an effect of trophic group amensalism could have delayed the recovery of nonmotile, suspension-feeding epifauna in the Early Triassic. This differential reaction of infaunal ecosystems to variable environmental controls thus played a substantial but heretofore little appreciated evolutionary and ecologic role in the overall recovery in the hot Early Triassic ocean

Mutations in TUBB8 and Human Oocyte Meiotic Arrest

BACKGROUND Human reproduction depends on the fusion of a mature oocyte with a sperm cell to form a fertilized egg. The genetic events that lead to the arrest of human oocyte maturation are unknown. METHODS We sequenced the exomes of five members of a four-generation family, three of whom had infertility due to oocyte meiosis I arrest. We performed Sanger sequencing of a candidate gene, TUBB8, in DNA samples from these members, additional family members, and members of 23 other affected families. The expression of TUBB8 and all other β-tubulin isotypes was assessed in human oocytes, early embryos, sperm cells, and several somatic tissues by means of a quantitative reverse- transcriptase–polymerase-chain-reaction assay. We evaluated the effect of the TUBB8 mutations on the assembly of the heterodimer consisting of one α-tubulin polypeptide and one β-tubulin polypeptide (α/β-tubulin heterodimer) in vitro, on microtubule architecture in HeLa cells, on microtubule dynamics in yeast cells, and on spindle assembly in mouse and human oocytes. RESULTS We identified seven mutations in the primate-specific gene TUBB8 that were responsible for oocyte meiosis I arrest in 7 of the 24 families. TUBB8 expression is unique to oocytes and the early embryo, in which this gene accounts for almost all the expressed β-tubulin. The mutations affect chaperone-dependent folding and assembly of the α/β-tubulin heterodimer, disrupt microtubule behavior on expression in cultured cells, alter microtubule dynamics in vivo, and cause catastrophic spindle-assembly defects and maturation arrest on expression in mouse and human oocytes. CONCLUSIONS TUBB8 mutations have dominant-negative effects that disrupt microtubule behavior and oocyte meiotic spindle assembly and maturation, causing female infertility. (Funded by the National Basic Research Program of China and others.

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Towards efficient SPICE-accurate nonlinear circuit simulation with on-the-fly support-circuit preconditioners

SPICE-accurate simulation of present-day large-scale nonlinear integrated circuit (IC) systems with millions of linear/nonlinear components can be prohibitively expensive, and thus extremely challenging. In this paper, we present a novel support-circuit preconditioning (SCP) technique for tackling large-scale nonlinear circuit simulations by exploiting sparsified graphs of a given circuit network. By extracting support graphs (SGs) from the original linear circuit networks, and combining them with nonlinear devices, support-circuit preconditioner can be efficiently computed using existing matrix solvers, allowing for on-the-fly updates during transient simulations when adopted in Krylov-subspace iterative solvers. Experimental results for a variety of large-scale circuit designs show that the proposed method achieves up to 22X speedups in solving the matrices involved in DC and transient (TR) simulations, and up to 8X reduction in memory usage, when compared with the simulator powered by the state-of-the-art direct solver KLU. © 2012 ACM

A performance-guided graph sparsification approach to scalable and robust SPICE-accurate integrated circuit simulations

To improve the efficiency of direct solution methods in SPICE-accurate integrated circuit (IC) simulations, preconditioned iterative solution techniques have been widely studied in the past decades. However, it is still an extremely challenging task to develop robust yet efficient general-purpose preconditioning methods that can deal with various types of large-scale IC problems. In this paper, based on recent graph sparsification research we propose circuit-oriented general-purpose support-circuit preconditioning (GPSCP) methods to dramatically improve the sparse matrix solution time and reduce the memory cost during SPICE-accurate IC simulations. By sparsifying the Laplacian matrix extracted from the original circuit network using graph sparsification techniques, general-purpose support circuits can be efficiently leveraged as preconditioners for solving large Jacobian matrices through Krylov-subspace iterations. Additionally, a performance model-guided graph sparsification framework is proposed to help automatically build nearly-optimal GPSCP solvers. Our experiment results for a variety of large-scale IC designs show that the proposed preconditioning techniques can achieve up to 18× runtime speedups and 7× memory reduction in DC and transient simulations when compared to state-of-the-art direct solution methods